FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See Section 10 and Rule 13)
Title of invention:
A COMPUTING PLATFORM FOR DEVELOPMENT AND DEPLOYMENT OF SENSOR DATA BASED APPLICATIONS AND SERVICES
Applicant:
Tata Consultancy Services Limited A company Incorporated in India under The Companies Act, 1956
Having address:
Nirmal Building, 9th Floor,
Nariman Point, Mumbai 400021,
Maharashtra, India
The following specification particularly describes the invention and the manner in
which it is to be performed.

FIELD OF THE INVENTION
The invention generally relates to the field of smart ubiquitous computing systems, cyber-physical systems and the Internet-of-Things (IoT). More particularly, the invention relates to a method and system for enabling a unified platform capable of providing suite of services for development and deployment of sensor-based applications in the smart ubiquitous computing environment.
BACKGROUND OF THE INVENTION
Smart ubiquitous computing systems have been developed and deployed in order to observe, monitor and track the state of various physical infrastructures, state physical objects, environment, human beings and their activities and utilize these observations to provide applications and services that enrich the lives of people and help them in their day-to-day activities. The environments in which such smart ubiquitous systems are deployed are referred to as "smart spaces".
In general, smart spaces includes various categories of sensors adapted for sensing and observation of various parameters in the environment that may enable to perform analytics on them to alert the end-users about the consequence of changes in the state, if any. For example, sensors may be deployed to observe and track location of any physical object, observe weather conditions to monitor natural calamities, observe traffics on the road to enable traffic shaping and vehicle surveillance systems etc.
Observations as described above are made by sensors and increasingly more and more sensors will be embedded in physical objects and things in the smart spaces. These sensors have transducers that transform a real life event or phenomenon into

an electrical signal or digital data. In addition the sensors have computation and networking capabilities. Increasingly many of these sensors will directly or indirectly be connected to the Internet. Many of the sensors will be deployed by organizations, companies or public sector entities such as city governments or utilities or government departments. Also, many of the sensors will actually be owned and operated by private individuals. In case of private individuals, sensors embedded in mobile phones used by individuals will be an important class of sensors.
A critical requirement for development of smart ubiquitous computing environments leading to development of "smart spaces" is the ability to collect data from a large set of diverse sensors, aggregate and store the sensor data, perform specialized analytics on the data and combine and correlate observations from multiple diverse and geographically dispersed sensors. There is a need for scalable computing platforms that are able to provide these capabilities to software developers, including third party software developers, who can use the sensor data and the derived analytics to create new novel applications. Also, such platforms may be made available as web services accessed over the Internet, In such cases, these platforms can be categorized under the class of cloud computing services referred to as Platform-as-a-Service (PaaS).
In the background art, several systems have been implemented that perform the task of analysis of data captured by different category of sensors or telecommunication devices having sensing capabilities which are deployed in any smart space environment. These systems incorporate sensor devices that sense the state of various physical entities in any smart-spaces environments that could be processed and analyzed further to monitor, administer and control the services catered through these smart-spaces remotely. Though, there has been efforts made in the past for real-time data capture and analysis thereof meant for remote smart-space monitoring,

the need for a unified platform that integrates the suite of services capable of provisioning the development of real-time applications and management thereof from sensor data captured through any sensor device still exists in the art.
As of today, there are various Platform-As-A-Services (PaaS) available including Google App Engine, Heroku, and Microsoft Azure etc. However, these are limited to general purpose application development and therefore do not provide specific support for development, deployment and management of sensor-based applications. These platforms do not provide specialized services required in IOT7 Cyber Physical Systems domain. In this domain, there is a need for specialized services to cater to applications that leverages web connected sensors and sensors available as part of smart mobile devices. Sensor discovery, description, interfacing, query and tasking are some of the key requirements. Additionally, the sensor driven applications need to be event driven and therefore require capabilities such as event processing or stream processing. Further, these domains may require support for various types of databases such as RDBMS, NOSQL and Object Stores etc for scalable storage of different types of sensor observations. Also, the diversified domains may require specialized analytics and data visualization for deriving inferences and value addition. None of the above disclosed PaaS platforms provide support for all these features in a single platform.
On the other hand, there are some sensor platforms available as cloud computing services such as Pachube (Cosm), Sun Microsystem Sensor Networks etc. However these platforms mainly focus on sensor data publishing, subscription and storage services with very elementary support for application development. Additionally, there is very little support in these platforms for location based processing, spatial and spatio-temporal processing. Additionally, these sensor platforms provide no

support for crowd sourced applications to be developed and deployed on these platforms.
Further, there are some sensors and gateway device vendors in the market including companies such as Digi, Mobile Devices etc who provide a cloud based web services for remote device monitoring, management and data acquisition. However, these services cater for sensors and devices from a particular vendor only and are therefore not suitabfe for mufti-vendor generic sensor device management, data capture and observation processing. Additionally, these services have very limited support for sensor data storage and analytics and almost no support for application development and deployment.
Additionally, a behavior based machine-to-machine (M2M) platform is known in the art that facilitates communication with global sensor network to enable sensor device management and generate composite applications without direct programming. Another implementation facilitating sensor-device management in the art uses cross APIs for accessing the sensor data across different platforms in a real-time. Further, an activity management system particular to specific domain such as semiconductor manufacturing is known in the art that comprises the steps of data collection, data storage and activation of services enables for improving the operational efficiency of the semiconductor manufacturing plant. An architecture facilitating automatic generation of software code for development of sensor driven applications is disclosed in the art.
Further, a framework facilitating context-aware advertising is known in the art, wherein the framework delivers relevant contents/ads to the end-consumer in context with the consumers behavior/habits tracked through sensors deployed in a smart-space environment. Further, an application scope management platform is known

that works on the aspects of crowd sensing adapted for web-application deployment and management thereof. An enterprise resource management analytics platform enables data integration from remote resources to facilitate remote surveillance, monitoring and real-time events of agencies, organizations and communities to ensure safety and security in their campuses. Further, a system implementing graph pattern query o simplify writing Stream Processing application by application developer is known. Further, systems facilitating efficient resource management in general for processing tasks in virtualized environment are known that utilizes sharing of resources for effective task management.
However, none of the existing systems, methods, platforms or frameworks provide a unified system that facilitates sensor driven distributed application development, testing, deployment, application life cycle management, analytics service, data storage service, sensor services and modeling and simulation for analytics. Also, existing systems lack comprehensive hosting of services such as sensor service, analytics service, identity & access control service, data storage service that are required for prompt and speed-up sensor application development. Further, none of the platforms disclosed in the art facilitates real-time development and deployment of sensor-based applications using a rich suite of services that enables sensor data reusability, data normalizing and data privacy. As most of the platforms lack generic capabilities of sensor data processing, this further leads to increase in costs and effort required for development and deployment of sensor based applications. Further, since the platforms are designed with specific to particular devices thereby bounded with security and privacy policies, there is a little scope of further application developments using third-party resources.
In the background art, there have been efforts made in the past for providing vehicle telemetry applications that enables intelligent transportation services to end-user

subscribers. In general, these applications are either provided vertically by the vehicle manufacturers/OEMs etc or made available to the driver's Smartphone. In both cases, the applications development is enabled by using sensor data from various vehicle on-board/off-board sensors such as GPS, accelerometer and the like. Further, there have been efforts made in the art for implementing cloud computing technologies in the vehicle for providing vehicle telemetry applications. Further, there are vehicle to vehicle ad-hoc networks (VANETs) available in the art facilitating the provision of vehicle telemetry applications in a specific transport domain. However, the need for a single unified platform facilitating an intelligent transportation system by way of providing intelligent transport services in the platform for develop, test and deploy various telemetry applications using these services still exists in the art.
In the background art, various vehicular applications are provided on either the Smartphones of the end-users subscribed to these applications or on the telematics platforms. The applicant herein has developed few of smart vehicular applications and applied for patent. Some of these patent applications are as follows:
314/MUM/2012 by Purushothaman, Balamuralidhar et al. discloses a system, method and apparatus for vehicular communication wherein audio information is broadcasted via a smart horn embedded in the vehicle which are interpreted by the application installed at the receiving station in order to take further steps.
773/MUM/2012 by Arpan, Pal et al. discloses a system for combining the diagnostic and prognosis of the vehicle based on the driver's driving habits and its response to various road conditions.

2335/MUM/2011 by Arpan, Pal et al. discloses a system and method for managing unmanned Railway check posts wherein, when the train is in proximity of an unmanned level crossing the system notifies all the mobiles in the vicinity of said level crossing.
2751/MUM/2011 discloses a system and method facilitating damage assessment of an object by converting the visual data of the object into Multi-Dimensional (MD) representation and by identifying a set of characteristic points and a set of contour maps from the said MD representation of the object.
2036/MUM/2008 by K S Chidanand et al. discloses an invention that captures the facial image of the driver using an IR camera and further performs the steps of face detection, binarization, pupil detection and pupil tracking for determining whether the driver is sleeping.
2784/MUM/2009 by Chidanand K.S et al. discloses a cost-effective and robust method for localizing and tracking drowsiness state of the eyes of driver by using images captured by near infrared (IR) camera disposed on the vehicle.
1264/MUM/2009 by Chidanand K.S et al. discloses a sleep detection system that efficiently traces the shape of the sclera of the driver's eyes to deduce whether the driver is awake or asleep by means of a Support Vector Machine (SVM) / Artificial Neural Network.
3367/MUM/2011 by Sinha, Aniruddha et al. method and system for emitting an encoded metadata over the beyond audible frequency signal, receiving and parsing the said received encoded metadata, extracting and decoding barcode received along

with encoded metadata and retrieving the tourist information by accessing a web link received along with encoded metadata for plurality of web based services.
3550/MUM/2011 discloses a method and system for determining actual fatigue time (AFT) for an activity based upon received standard fatigue time (SFT) and a fatigue index corresponding to one or more external parameters.
2750/MUM/2011 discloses a method and system for rough vehicle detection based on sensor data received from various on-board/off-board sensors of the vehicle sensing the state of vehicular components.
2999/MUM/2011 by Chakravarty, Kingshuk et al. discloses a method and system for real-time image analytics using a cloud-computing backend server, wherein the analytics data is transferred only to authorized parties identified through tagged images received for analysis on said server.
PCT/rN2010/000581 by Jayaraman, Srinivasan et al. discloses a system for vehicle security, personalization, and cardiac activity monitoring of a driver wherein electrocardiography of a driver is monitored and registered which is used for identification of a person entering in the vehicle and personalization of vehicle based on user preferences thereby act as intruder detection towards vehicle security.
PCT/IN2010/000811 by Nag, Sudip et al. discloses a system, method and apparatus for monitoring cardiac activities of users, wherein said system includes a wearable and self-contained cardiac activity monitoring device which operates in multiple wireless modes to trace the cardiac activities effectively and perform prognosis of an ailment.

3550/MUM/2011 discloses a method and system for determining actual fatigue time (AFT) for an activity based upon received standard fatigue time (SFT) and a fatigue index corresponding to one or more external parameters.
2750/MUM/2011 discloses a method and system for rough vehicle detection based on sensor data received from various on-board/off-board sensors of the vehicle sensing the state of vehicular components.
However, all these vehicular application is unique of its kind and meant for specific activity monitoring. These are limited to providing specific applications deployed on Smartphone or any telematics platform with or without the usage of a back end server. Each of this applications act as a standalone application that can be deployed on user's Smartphone and will track a dedicated/specific activity in the smart-vehicle environment. However, these applications can be leveraged to develop and deploy various other applications in context with the vehicular domain by using the algorithms and software development logic on the basis of which each standalone application is developed. More particularly, each of These applications can be provided as various services in the platform based Intelligent Transportation system that facilitates development, testing and deploy of numerous applications by means of data and system components reusability.
Thus, in view of the above, there is a long-felt need for an efficient method and a single unified system/platform design enabling real-time analysis sensor data captured from virtually any kind of sensor device and facilitates sensor-data capture, storage and analytics thereof using a suite of services therefrom said platform. Further, there is a need for a method and system that leverages a cloud computing platform offering a suite of services designed for real-time sensor data analytics, data mining, machine learning, image and video analysis, location based services and

context-aware services in a ubiquitous computing environment. Also, there exists need in the art to provide a platform based solution for intelligent transportation solution hosting plurality of services configured to allow software developer community to develop new vehicular telemetry applications common to the domain and thereby facilitating data reusability.
OBJECTS OF THE INVENTION
The principal object of the invention is to provide a Real-Time Integrated Platform for Services & Analytics (RIPSAC) in the form of a Platform-as-a-Service (PaaS) cloud computing platform that allows quick and easy development, deployment and administration of sensor driven applications.
Yet another object of the invention is to provide a method and system for a real-time platform enabling data capture from any ubiquitous device having at least one attached sensor, the said device being connected through a communication network to the Internet.
Yet another object of the invention is to enable a method and system for storing said data with assorted formats captured from various sensor devices in a database connected to the platform.
Yet another object of the invention is to perform a scalable analytics on the stored data in the database to derive insights, inferences and visualized data therefrom thereby allowing stakeholders to take further decisions on the businesses associated with that data.

Yet another object of the invention is to provide a method and system enabling realtime development, testing and deployment of sensor-based applications thereby facilitating crowd sourcing application developments.
Yet another object of the invention is to provide a method and system enabling to develop various sensor-based applications using the suite of services of the platform by selecting appropriate algorithms, software development kits (SDKs), application program interfaces (APIs) etc bundled in said suite of services.
Yet another object of the invention is to enable a method and system for data analysis by capturing data from user inputs using crowd sourcing, and treating these data as data from software sensors.
Yet another object of the invention is to provide a method and system enabling dissemination of deployed applications on end-user computing devices subscribed to these applications and services thereof.
Still another object of the invention is enabling a method and system for appropriate privacy controls and end-user license agreements while performing the analytics on the data.
Still another object of the invention is enabling a method and system for providing the RIPSAC platform and services thereof for real-time analysis and monitoring of activities in diverse sectors including energy, utility, government, transportation, healthcare, and education etc.

Yet another principle object of the invention is to provide a method and system enabling an intelligent transportation platform hosting a plurality of bundled services to develop sensor-driven vehicle telemetry applications.
Yet another object of the invention is to enable application developers select services and algorithms thereof relevance in context with the domain of the sensor driven application to be developed from the bundled services of the platform.
Yet another object of the invention is to provide test data and development sandboxes to application developers for testing the application developed and ready for deployment in the transportation domain.
Yet another object of the invention is to plug-in the newly developed applications into the bundled of services of the platform for facilitating future application development on same domain.
Yet another object of the invention is to provide a method and system wherein said developed sensor-based applications facilitates vehicle anomaly detection and prognosis thereof focused to enable safety and security for the vehicle, driver, passengers and other road users.
Yet another object of the invention is to enable a method and system for notifying the end-users' subscribed to said intelligent transportation systems' applications regarding the anomalies in the vehicle transit.
Still another object of the invention is to enable a method and system for delivery of targeted advertisements to the occupants of the vehicle based on real-time tracking of occupant behavior and driving habits.

SUMMARY OF THE INVENTION
Before the present methods, systems, and hardware enablement are described, it is to be understood that this invention is not limited to the particular systems, and methodologies described, as there can be multiple possible embodiments of the present invention which are not expressly illustrated in the present disclosure. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only, and is not intended to limit the scope of the present invention.
In one embodiment, the present invention enables a Real-Time Integrated Platform for Services & Analytics (RIPSAC) which is a Platform-as-a-Service (PaaS) cloud computing platform that allows quick and easy development, deployment and administration of sensor driven applications. In this embodiment, the RIPSAC interfaces with a heterogeneous set of sensors and devices within a smart computing environment collecting sensor observations, storing the data in a database connected with the platform, performing scalable analytics on the data for the benefit of both the end subscribers as well as authorized third parties such as insurance companies and government regulators either within the vicinity of the smart computing environment on in a cloud, exporting de-personalized samples of that data to third party application developers to enable open software development. In this embodiment, the platform provide a suite of infrastructure services in the form of APIs and SDKs. RIPSAC provides a highly scalable platform for sensor integration, sensor data storage, analytics, rich query capabilities and visualization. The platform comprises a set of services related to sensor description, discovery, integration, sensor observation and measurement capture, storage and query in the form of APIs and libraries. In this embodiment, application developers including third-party

software developers are adapted to develop, test, deploy and manage applications in the said cloud-computing platform. In this embodiment, end-users are adapted to download apps, subscribe & unsubscribe to them, control their privacy settings, and view usage history and billing information.
In one embodiment, the present invention provides an Intelligent Transportation system based cloud-computing platform that consist of a plurality of services over the platform. In this embodiment, sensor based analytics are provided as services on the platform which include feature extraction, classification, clustering and visualization. In this embodiment, these set of services are provided on the vehicular system and also on the user's Smartphone capable of providing sensor data feeds to the platform. These services include accelerometer analytics, location based services and other such tools for developing applications. The services include bundles for feature extraction, classification and clustering along with visualization, reporting and actuation etc. In this embodiment, together these services form a bundle of intelligent transportation services deployed on the cloud-computing platform which is used to develop a number of novel applications and also provides a facilitator for developing further applications on the same domain.
In this embodiment, the intelligent transportation service (ITS) platform integrate a suite of services for enabling real-time sensor data-capture, storage, analytics, development and deployment of telemetry applications built using said services for data captured from any kind of sensor device. The platform enables availability and selection of relevant service from the suite of services bundled inside the platform to develop, test and deploy a sensor-based telemetry application that reports the subscribed computing devices the anomalies observed in the vicinity of the smart vehicular system and prognosis thereof. More particularly, in this embodiment of the invention, an intelligent transportation system is deployed using the suite of services that facilitates development and deployment of several vehicle telemetry applications

that monitor and track anomalies in the vehicles, road conditions, driving habits of the driver, environmental conditions, and passenger behaviors etc. The platform further enables data reusability to configure the existing suite of services comprising algorithms such as feature extraction, clustering, and classification etc to identify and built novel sensor-based applications.
In this embodiment, the ITS is configured to provide context-aware service to the end-consumers based on tracking of habits of the passengers in the vehicle. That is, the ITS platform is configured such that the multiple users in the vehicle premises may each automatically receive advertisements relevant to their interests, habits and behaviors tracked through various sensors deployed in the vehicle, generating the context. For example, if a user who typically sits in the passenger seat of the vehicle is interested in sports, he or she will be pushed advertisements related to various sports products such as shoes, jerseys, and sport equipments etc. If the passenger in the back seat is interested in something else (e.g. action games), appropriate ads will be targeted to him at the same time the passenger seat occupant receives the sports ads.
BRIEF DESCRIPTION OF DRAWINGS
The foregoing summary, as well as the following detailed description of preferred embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the invention, there is shown in the drawings exemplary constructions of the invention; however, the invention is not limited to the specific methods and architecture disclosed in the drawings:
Figure 1 schematically illustrates a system architecture diagram (100) displaying various hardware elements configured to perform real-time sensor data analytics in a

smart computing environment according to an exemplary embodiment of the invention.
Figure 2 is a block diagram (200) of RIPSAC platform illustrating various application developers/tenants, sensor data providers and subscribers being connected with said RIPSAC platform for accessing RIPSAC services and applications in accordance to an exemplary embodiment of the invention.
Figure 3 is a block diagram illustrating various software layers of the in-car telematics device enabling real-time analytics of telematics data in accordance with an exemplary embodiment of the invention.
Figure 4 is a block diagram illustrating the back-end software platform according to an exemplary embodiment of the invention.
Figure 5 is a block diagram illustrating an intelligent transportation system (500), deployed using suite of services bundled on the RIPSAC platform.
Figure 6 is a working example illustrating road condition monitoring and alert application deployed by an Intelligent Transportation System using the RIPSAC services according to an exemplary embodiment of the invention.
Figure 7 is a flow diagram illustrating steps designed to enable the RIPSAC platform to perform the task of real-time analytics of any smart-space environment according to an exemplary embodiment.

Figure 8 is a flow diagram illustrating steps designed to enable the ITS platform with support of the RIPSAC services to perform the task of real-time analytics of a vehicular transportation according to an exemplary embodiment.
DETAILED DESCRIPTION:
The description has been presented with reference to an exemplary embodiment of the invention. Persons skilled in the art and technology to which this invention pertains will appreciate that alterations and changes in the described method and system of operation can be practiced without meaningfully departing from the principle, spirit and scope of this invention.
Referring to figure 1 is a system architecture diagram of a Real-Time Integrated Platform for Services and Analytics (RIPSAC) 100 comprising various hardware elements configured to perform real-time data analytics in a smart computing environment according to an exemplary embodiment of the invention.
As illustrated in figure 1, the system architecture (100) comprises a RIPSAC backend cloud (112) that includes a cloud server (101) connected to a database (102). The system further comprises various RIPSAC devices (114) implemented on different smart devices such as Smart phone (103), a telematics device (104) enabling real-time analytics of sensor data. The system further comprises various heterogeneous sensor devices (105), (106), (107) and (108) etc placed in the vicinity of smart computing environment connected with various telecommunication devices such as Smartphone (103), and the telematics device (104) etc. Thus, the sensors along with the telecommunication devices collectively form an intelligent smart environment according to this exemplary embodiment.

Further, as illustrated in figure 1, the system platform (100) supports various connectivity options such as Bluetooth®, USB, ZigBee and other cellular services collectively illustrated as smart computing network (109). In an exemplary embodiment, the system platform interfaces with sensors (105,106, 107, and 108)such as GPS, accelerometers, magnetic compass, audio sensors, camera sensors etc deployed in vicinity of the smart computing environment. The platform enables connection of telecommunication devices such as Smartphone with the server, and accordingly with the database using any communication link including Internet, WAN, MAN referred to as (110) in figure l.In an exemplary embodiment, the system platform (100) is implemented to work as a stand-alone device. In another embodiment, the system platform (100) may be implemented to work as a loosely coupled device to the smart computing environment.
In one embodiment, the Smartphone as illustrated in figure 1 may include in-built sensors such as accelerometer, compass, GPS, NFC reader, microphone and camera etc. In this embodiment, the system platform (100) may be installed on the Smartphone in the form of a mobile application (App). In such scenario, the inbuilt sensors in the Smartphone feed the data collected by them related to vehicle tracking, traffic measurements, and human driving characteristics etc to the RIPSAC platform (100) acting as mobile app on the Smartphone. In such scenario, the Smartphone is considered to be a ubiquitous telematics platform which may act as a car phone if the Smartphone is located inside the car. Further, based on the data collected from various sensors, the system platform (100) with the help of various hardware and software platforms collectively performs the task of scalable data analytics on the captured sensor data in any smart computing environment.
Referring to figure 2 is a block diagram (200) illustration various user-devices connected to RIPSAC platform for utilizing various RIPSAC services and

applications in accordance with an exemplary embodiment of the invention. As illustrated in figure 2, the RIPSAC platform (201) provides various RIPSAC services related to sensors, storage and analytics to different stakeholders connecting with the platform. A plurality of sensor providing devices (205) act as contributors or publishers that publishes sensor data observed in any smart space environment. The sensor providing devices (205) own the sensor observation data.
A plurality of application developer devices (203) as shown in figure 2 communicates with the platform (201) by means of communication network, preferably by means of an internet connection. The application developers are adapted to access the RIPSAC services on the platform to develop varied sensor-driven application and deploy these on the platform (201) in the form of RIPSAC applications. As illustrated, a plurality of end-user subscriber devices (207) are shown that connects with the platform (201) by internet communication means in order to subscribe with the RIPSAC applications deployed in the RIPSAC platform (201). In an embodiment, the sensor providing devices (205) and the application developer devices (203) can perform the tasks interchangeably. In this exemplary embodiment, platform/PaaS provider (209) is an entity that runs the RIPSAC platform (201) as a hosted service.
In this exemplary embodiment, the RIPSAC platform (201) provides different services for each of the application developer/tenant device (203), sensor provider device (205), end-user device (207) and a platform provider (209) connected to the platform through internet means. In this exemplary embodiment, the platform provider (209) is provided with the ability to deploy and run the core RIPSAC services such as sensor , Storage and Analytics Services, deploy and run Identity , Security, Privacy and end User License Mgmt services. The platform provider is provided with the ability to deliver targeted advertisements, create a multi-tenant

environment with control resource sharing, create separate environments of sandboxes for different tenants and enable operation support systems such as managing, monitoring, billing etc. In this exemplary embodiment, the sensor providing devices (205) are provided with the services needed to describe feature of interest and different types of phenomenon, sensor & sensor observation description, Feeds & sensor streams definition, services required to publish & share sensor streams to the platform and services needed to define access control and privacy preferences for published sensor streams.
In this exemplary embodiment, the application developer/tenant devices (203) are provided with environments required for development & testing of applications in the form of Sandboxes. Further, Software Development Kits and Application Programming Interfaces (APIs) in form of web services calls or language specific libraries are made available to these devices. Additionally, the platform provides test sensor data to tenants so that they can develop and test applications. The application developer/tenant devices (203) are adapted to register and deploy Apps to the RIPSAC platform (201). The application developer/tenant devices are enabled to define end user license Agreements for their applications and can Start, Stop, upgrade, redeploy and undeploy applications. In this exemplary embodiment, the end-user devices (205) as shown in figure 2 are adapted to download apps, subscribe or unsubscribe to RIPSAC applications and services. Further, these devices are adapted to control the privacy setting of sensor data which they are contributing/publishing with the platform and are enabled to track & view usage history, billing information etc.
In an embodiment, the services provided to various stakeholders in the platform including platform providers (209), application developers/tenants, sensor providers and end-user subscribers etc are facilitated through various hardware/software

components in the platform. Figure 3 and 4 refers to software architecture diagrams illustrating different suite of sensor-based services enabling real-time analytics of sensor data in accordance to an exemplary embodiment of the invention. The software architecture comprises three software platforms enabling the real-time including a sensing device software platform, a backend software platform and a Smartphone platform.
As illustrated in figure 3, the sensing device software platform (300)comprises a real-time operating system (OS), device drivers required for establishing interconnections and network adaptors and providing support for deployment and execution for multiple concurrent telematics services and applications, standard programming languages and development tools for software development, remote deployment, real-time monitoring and management of deployed software components, support for secure deployment of trusted applications and services and fine grained access controls. In an embodiment, considering these requirements for executing various applications and services, the programming language such as JAVA and OSGI as a service delivery platform is utilized.
Referring to figure 4 is a software platform architecture diagram (400) illustrating various backend components in the backend software platform. The backend software platform comprises a scalable sensor service module, a scalable storage service module, a scalable analytics services module, web-based portals facilitating connectivity with end-user mobile computing devices that collectively implements real-time analytics on data received from various sensor devices installed in a smart-space environment. RIPSAC acts as a Platform-as-a-Service (PaaS) cloud computing platform that allows quick and easy development, deployment and administration of sensor driven applications. RIPSAC provides sensor device management, data acquisition, data storage and analytics services. These services are made available to

application developers in form of application program interfaces (APIs) and software development kits (SDKs). RIPSAC provides a highly scalable platform for sensor integration, sensor data storage, analytics (including real-time and Big Data processing), rich query capabilities (including geo-spatial queries and continuous queries) and visualization.
At the core of RIPSAC is a set of services related to sensor description, discovery, integration, sensor observation and measurement capture, storage and query. RIPSAC provides these services in form of APIs and libraries. App developers can develop, test, deploy and manage applications in RIPSAC. RIPSAC supports multi-tenancy and provides secure sandboxes for testing and deployment of applications by each tenant. End users computing devices are configured to download Apps, subscribe & unsubscribe to them, control their privacy settings, and view usage history and billing information.
Thus, the RIPSAC integrates various services, software, libraries, tools in the single infrastructure platform that can be utilized for development and deployment of various sensor-driven applications. In an embodiment of the invention, the RIPSAC enables such integration by utilizing standard information models and access mechanisms such as the Open GeoSpatial Consortium (OGC) standards known as Sensor Web Enablement (SWE) standards. In an embodiment, the RIPSAC sensor services provide access to sensor and sensor observation data using these standards. Further, the RIPSAC platform provides client libraries and web service Application Program Interfaces (APIs) that make it feasible and easy to use the information model and access mechanism. In an embodiment, the RIPSAC platform further enables exchanging sensor related events across different applications and services using a messaging infrastructure that consists of message publish-subscribe mechanisms implementing such exchange of sensor related events.

In an embodiment, integration of any software running on RIPSAC (i.e. applications and services) with Analytics engines is provided by means of analytics engine specific libraries included in the RIPSAC platform. In this embodiment, a networking protocol enabling data connection facilitates connection of these libraries to analytics engines running on analytics servers. The libraries hide all complexities and details of network connectivity between the end points. Moreover, these libraries also provide load balancing services across the various analytics servers. In an embodiment, the RIPSAC database services are accessed using a combination of web service calls, technologies such as SQL, JDBC and JPA, and specific database client libraries etc. The various services bundled through said scalable sensor service module, scalable storage service module, scalable analytics services module and web-based portals are now described by referring to figure 4.
In an embodiment, as illustrated in figure 4, the presentation services module (401) are catered through portals and user Interfaces. The portal component includes application developer's portal, administrator's portal and an end-user subscriber portal. The application developer's portal is utilized to enable application developer's computing devices to register with the RIPSAC, register the developed applications, create databases, upload and test analytics programs etc. The administrator's portal is used by the RIPSAC administrator computer to manage and monitor the underlying software and hardware infrastructure, monitor, manage and control usage of platform services by tenants.
In an embodiment, the device integration and management services component (413) includes data aggregation and device monitoring and management services for interfacing gateway devices, sensors, mobile devices and their network addresses in RIPSAC. These services provide support for various network protocols for data

communication between these devices and RIPSAC. This suite of service enables ability to monitor the health and status of the devices and the ability to deploy software on these devices from RIPSAC. In this embodiment, device specific software modules, known as Device Sensor Adapters are provided for each type of device that are able to access the sensors attached to these devices and process sensor specific commands. Further, device specific software modules, known as Device Management Adapters are developed for each type of device that facilitates a web service interface for the following type of activities such as device health monitoring, device starting, stopping and restarting and device data structure access, read and update. In this embodiment, the Device management Adapters typically runs on the device itself. Alternatively, for some devices, Device management Adapters may run as a separate cloud based web service. The RIPASAC device management services use Device Management Adapters for each device connected to RIPSAC to manage and monitor devices. Further, software modules called RIPSAC Sensor Integration adapters are used by software running on the devices to invoke the RJPSAC Sensor Services over an internet connection. In addition to use of RIPSAC Sensor Integration Adapters, application software running on devices can also call web service interfaces exposed by RIPSAC applications directly. In such scenario, the RIPSAC Integration Adapters are bypassed in the device, but invoked from the RIPSAC application instead. These devices facilitate sensor data acquisition and integration on the platform using either pull-mode or push-mode.
In one embodiment, in case of a pull-mode sensor data acquisition, the sensor data feed is captured by RIPSAC applications by invoking Device Management Adapters running for the devices whose sensor data is required. In another embodiment, if the sensor data is acquired using push-mode, the sensor data is posted to RIPSAC sensor services by the device software either by invoking RIPSAC Sensor Integration Adapters or by calling the web services exposed by RIPSAC applications. In an

embodiment, depending on the application logic and type of sensor, the sensor data acquisition may be continuous (i.e. periodic), or event driven, or on demand initiated by some user action. The RIPSAC platform can support time series sensor data in any granularity.
In an embodiment, the Messaging & Event Distribution Services (411) provides an infrastructure for passing of messages and events across RIPSAC services and applications. Further, the Data Storage & Query Services (409) enables large scale, distributed sensor data storage and query facility, including support for geo-spatial queries. These services enable the capability of continuous query processing.
In an embodiment, the analytics services component (407) consists of several libraries and servers comprising machine learning packages, statistical processing packages, rule engines, complex event and stream processing, knowledge driven processing that are configured to perform real-time analytics on the stored sensor data. The Application services component (403) incorporates application components, core sensor services, and user interface & visualization services. The core sensor services enable sensor and senor observations description services, sensor discovery, feature description and phenomena, inserting & querying observations etc. In this embodiment, in order to insert observations for a given Sensor Id, observation in terms of pairs, geo-location coordinates of the observation and the time of observation is specified and then the observation is inserted using RIPSAC services. Similarly, observations are queried using one or more parameters including Sensor Id, Phenomenon, Geo-location parameters (points, boundaries etc), and time parameters. The Observations are used as is or it is passed on to analytics programs and then the output of analytics programs is used for observations. The user interface & visualization services component incorporates libraries and tools for creating rich visualizations and reports from the sensor data.

In an embodiment, the application components include producer applications component, consumer applications component and producer cum consumer applications component. The producer applications component is configured to publish sensor data to the RIPSAC platform. The consumer applications component is adapted to query and use sensor data from the RIPSAC platform. The producer cum consumer applications component is configured to simultaneously act as both producer applications component and consumer applications components.
In an embodiment, the application support services component (405) includes integration & orchestration services, planners, platform APIs & SDKs that collectively provide support for various RIPSAC service integration and orchestration thereof. The Service Orchestration allows creation of composite applications or composite services. Service Orchestration is itself a platform service that is available to application developers for the purpose of creating composite applications. Access to service orchestration services, like any other RIPSAC services, is controlled using policy driven access controls. The Service Orchestration services in the RIPSAC are implemented using a standard web service orchestration engine. These Services will allow application developers to specify the orchestration logic using standard web service orchestration languages such as Business Process Execution Language (BPEL). RIPSAC Orchestration services make it simpler to use orchestration services by hiding the details of orchestration engines and engine specific complexities. The RIPSAC platform enables these SDKs and APIs to provide support for third party application developers and also provides them access to developer sandboxes and training data. The application developers can test and verify the various applications built on the software platform enabling real-time analytics by utilizing the test data, development sandboxes and device simulators provided by the backend software platform. APIs and SDKs are software

development tools that acts as Web Services and language specific bindings to various RIPSAC services.
In an embodiment, the RIPSAC backend platform further facilitates Software infrastructure that comprise application servers, relational databases and document databases. The application servers act as Containers / Virtual Machines / hosts on which user applications are executed. The relational databases and document databases services enable storage of data and documents in the RIPSAC backend platform. Additionally, the RIPSAC facilitate data center infrastructure services that include Compute, Network & Disk Storage Services, File Services and Firewall Services. The Compute, Network & Disk Storage Service consists of servers, disks and network resources that act as a virtual hardware infrastructure on which RIPSAC components finally run. File storage services are provided to servers using File Services. The Firewall Services are adapted to create secure zones based on policies to separate different tenants from each other.
In one embodiment of the invention, in order to enable flexible, extensible and interoperable platform that can accommodate and interoperate with virtually any sensor type and to allow easy addition of new applications and services, the platform adopts suitable database schemas and message encodings. The database schemas are designed in such a way so that virtually any sensor measurements and observations made in smart-space environment and can be stored for both immediate and historical use. Similarly, suitable XML based encodings and schemas can be used in messages transferred from the sensing device to the backend platform. Apart from proprietary protocols, both the telematics device as well as backend platform will support standard web services and http for accessing sensor observations.

In one embodiment, the RIPSAC platform incorporates Privacy preservation important feature in the software stack of the backend platform. Various sensor-based applications and services require various levels of privacy preservation and the proposed invention enables tailored levels of privacy protection for each application or service. Privacy preservation is achieved via the following four sub-components:
• Policy driven and adaptive access control software layer is configured for allowing fine grained control over who can access various sensors, sensor observation values and sensor database records and fields.
• Robust privacy preserving algorithms configured for anonymizing, diversifying, perturbing and randomizing privacy sensitive data.
• Data transformation algorithms configured for transforming private data to forms suitable for publishing for public consumption and vice versa.
• Use of Trusted Computing concepts and Trusted Platform Modules for secure and trusted storage of keys and algorithms for privacy preservation and data transformations as described above.
In an embodiment, the Smartphone software platform includes a software development kit (SDK) compatible to the Smartphone and an app-store model. The platform (100), if implemented as a Smartphone app is configured to be made compatible with various Smartphone devices in the market built on several operating systems (OS) or simple Java phones supporting J2ME, CLDC,MIDP and Midlets. The hardware platform illustrated in figure 2 in combination with the software platforms such as the sensing device software platform, the backend software platform and the Smartphone platform by virtue of single integrated cloud-computing platform enable the subscribers and other authorized third parties to perform various tasks based on the data analytics results that may be implemented in the cloud or in the vicinity of monitored and analyzed smart-space environment.

Thus, the RIPSAC platform as shown in figures 1 & 2 is configured for enabling development and deployment of sensor-driven applications through suite of services bundled on the platform. However, when this platform is deployed in real-life scenario such as intelligent transportation systems, there exist challenges in utilizing the existing suite of services on the platform to facilitate sensor-driven applications related to transport domain. This is because the transportation domain may include sensor devices that are mobile in nature, the end-user vehicular application to be deployed may be variant in nature with fluctuating data. Hence, the back-end of the platform hosting the bundle of services need to modified in the existing RIPSAC platform. Therefore, the applicant of this invention propose another inventive aspect, wherein the suite of services bundled on the platform are modified such that intelligent transportation service suite is added to said platform, wherein the intelligent transportation service suite is utilized for create and deploy various vehicle telemetry applications in the smart vehicular environment. These intelligent transportation services on the RIPSAC platform can be utilized for real-time monitoring of various aspects related to vehicular transport including driving habits, traffic conditions, road conditions, passenger behaviors and location tracking etc. The intelligent transportation system is enabled by using few set of services suite bundled in the RIPSAC platform. RIPSAC acts as a unified platform which provides Intelligent Transportation based Services that allows the deployment of applications as well as reusable algorithms and components into the platform. Various embodiments of the inventive intelligent transportation system are now described by referring to figures 5, 6 and 8.
Referring to figure 5 is a block diagram illustrating an intelligent transportation system (500), hereinafter referred to as ITS deployed using suite of services bundled on the RIPSAC platform. As illustrated, the intelligent transportation system (500) is adapted to configure a sensing service module (501), an edge analytics service module (503), a backend storage service module (505), a backend analytics service

module (507) and a reporting service module (509) to intelligently manage and deploy various sensor-based applications for transportation systems.
In an embodiment, the sensing service module (501) is configured to provide sensor data feeds either from a Smartphone or an in-car telematics platform equipped with an array of sensors either on board or connected via some bus/wireless interface. The edge analytics service module (503) performs analytics on the received data feeds from the sensor that enables preprocessing and feature extraction which leads to data reduction and also allows for storage of only features rather than raw sensor data. The Backend storage service module (505) is a SWE implementation which allows storage and retrieval of sensor data using SOS (Sensor Observation Service). The Backend analytics service module (507) is adapted for running analytics on the back-end subsystem that include execution of algorithms such as classification, clustering etc. The reporting/ service module (509) is a user interface service module that provides audio/visual alerts or visualizations to the end-user subscribed devices (511) based on the analytics run on the sensor data. More particularly, the results of the analytics in the form of anomalies detected in the vehicular transport and prognosis thereof is transmitted on the end-user computing devices (511) subscribed to RIPSAC services and application developed therefrom. Thus, the present invention provides Intelligent Transportation as a Service bundle on top of a SWE (Sensor Web Enablement) based platform in the form of RIPSAC platform. The ITS (500) incorporates a suite of services focused on Safety and Security for the vehicle, driver, passengers and other road users. The ITS (500) allows application developers/tenants (513) to pick and choose from a set of algorithms best suited for the domain. The ITS (500) allows application developers to test their algorithms with some test data from the platform. The intelligent transportation system (ITS) built on RIPSAC is flexible to allow for development of new algorithms and adding them back on to the bundle and also allows application developers to test their algorithms with some test data from the platform.

In an embodiment, the sensing service module (501) supports various sensor services including location service, motion service, diagnostic service, and in-vehicle audiovisual sensing service that provides sensor data feeds from various on-board/off-board vehicle sensors. The Location service is configured to interpret the position of an entity or a device. In general, the location is defined by latitude, longitude and altitude information. In a local scenario, like in a building, the location might mean much more granular location like floors and zones etc. Location may be provided by GPS systems or may be derived from vicinity sensors like RFID tags, Bluetooth or Wi-Fi. The location may also be derived from a person's public information like twitter hash tags, facebook location service of text analysis of blogs. Geo-tagging of pictures uploaded in near real-time by a user may also be used as inference.
In an embodiment, the motion service is provided from the vehicle as a set of raw or processed sensor outputs that depicts the motion parameters (typically velocity or acceleration) of a vehicle along the X, Y and Z axis using a set of pre-defined coordinate system. Motion is typically detected and estimated using accelerometer and optionally a compass as sensor. However it can also be inferred indirectly using emissive and beaming techniques from the infrastructure like once used by the police to detect speeding. However, use of the second form is rare and hence may be ignored. Further, motion can also be predicted using proximity sensing to other vehicles or infrastructure points along a route. The Diagnostics service is provided by the analytics on a connected dashboard of a vehicle. It includes analysis of fuel level, batteries, oxygen sensors, MPFI readings, and accelerometer etc. Diagnostics forms an important service because a lot of vehicle safety and reliability depends on the vehicle condition which can be obtained from diagnostics information. This information is available from most of the vehicles using the On-Board Diagnostic (OBD).

In an embodiment, in-vehicle audio-visual sensing service provides audio signals and visuals (images/videos) from inside the car or around the car using Smartphone based camera or in-vehicle cameras connected to a gateway. Typical multimedia signal processing techniques can be used to extract useful information from this data like object identification or classification etc. In an exemplary embodiment, one way of real-time upload of images to be used for real-time processing and derive inferences thereof has been disclosed in the pending Indian Patent Application Number has been disclosed in patent application 2999/MUM/2011.
In an embodiment, the back-end analytics service module (507) supports various analytics services including accelerometer analytics service, location analytics service, multimedia signal processing service, and modeling/simulation service. In this embodiment, the accelerometer analytics service can be used for a variety of purposes such as bad trail detection, rouge driver identification and also diagnosing the condition of a vehicle. The accelerometer analytics service utilizes raw accelerometer data and executes algorithms such as Feature Extraction and Classification etc to perform the analytics. The location analytics service suite implements clustering or classification of location that leads in aggregation of location based data to provide a much better insights or inferences to the responding devices. The location analytics service bundle contains a set of such algorithms that process the location data produced by sensors like GPS, A-GPS etc. to provide analytics like "who is nearer to whom" and "was it the same place".
In this embodiment, the multimedia signal processing service is an analytics service based on audio and video processing to provide driver assistance and vehicle monitoring utilities. This allows monitoring the driver behavior (e.g. sleep detection, attention detection etc.), alerts the driver in presence of pedestrians on the way and alerts the driver on road signs. The video processing services detect the pedestrians and their distances from the car, detect the road signs and detect the face and closure

of eyes of the driver. In an exemplary embodiment, one way of localizing and tracking drowsiness state of the eyes of the driver by using images captured by near infrared (IR) camera disposed on the vehicle has been disclosed in the pending Indian Patent Application Number 2784/MUM/2009.Further, the Indian Patent Application Number 1264/MUM/2009 discloses one way of sleep detection in the vehicle transits. Another technique utilize for detecting a driver falling asleep while driving has been disclosed in the Indian Patent Application Number 2036/MUM/2009.The detected events and alerts are the output of this service
In an embodiment, the modeling/simulation service bundle is configured to receive inputs from location, motion and diagnostic based services to model terrain or vehicle or even the driver. This provides a way to simulate the situation and generate synthetic data from training of the algorithms and system for the real runtime. Also this data can be used for future classification. In this embodiment, the reporting/ service module (509) provides audio/visual alerts, reports for the transportation service requested by various subscribers. It may be navigation, diagnostic or road prognosis alert or a report on the car health or the driving patterns etc.
In an embodiment, the ITS uses a Planning Service suite on the RIPSAC that can provide users with a route plan using an existing transportation system and location information about the source, destination and a set of *POI (places of interests). Further, the safety service on the RIPSAC is configured to use various sensor analytics service and alerting/reporting service to provide safety related alerts and actuations to the user. This includes image processing, diagnostic, location and motion services combined with several types of analytics run on the same, for example object detection and identification, accelerometer analytics and also readings from RPM and suspension sensors via On-board devices (OBD) of the vehicle.

Referring to figure 6 is a working example illustrating road condition monitoring and alert application deployed by the ITS using the RIPSAC services according to an exemplary embodiment of the invention. The working example illustrates the capability of the ITS (500) to detect and avoid potholes on the road. Potholes are both annoying as well as can be damaging to vehicles. However, potholes can be avoided and taken care of if the driver is made aware of their locations well in advance. To enables this, vehicles collaborative communicates with the ITS sensing and alert system. As illustrated, whenever a vehicle accelerometer (611.1) experiences an anomaly (609) in the z-axis, it uploads its location and the anomalous data (617) to the backend (600). The backend (600) does an analysis of the data from a number of such vehicles (611.2, 611.3, 611.4, and 611.5) and derive an inference that the detected location does contain a pothole. Following this, the vehicles (613, 615) which are on the same route are notified of the location and hence the pothole is successfully avoided.
In this exemplary embodiment, the road condition monitoring application is enabled using the suite service bundled in the RIPSAC for ITS. In the first step, sensor service for motion (603) is used to capture accelerometer readings from user's Smartphone (611.1). Following this, the \analytics service (605) is used for preprocessing, feature extraction and classification of the data on user's Smartphone (611.1) to identify the current road condition. This is achieved as a score for each classifier. Then sensor service for location (603) is used to get the current location and the data posted to backend (600). Such data is posted from a number of in-vehicle phones (611.2, 611.3, 611.4, and 611.5). Finally, a fusion is run on the data which does a clustering on the location data associated with the scores to get an aggregated score which is then provided to the user using alerting/reporting service (619) as audible alerts and a pothole map of the city/region.

Similarly, the Intelligent Transportation System (ITS) (500) can be configured to develop many such sensor-based applications enabling real-time monitoring of anomalies in the vehicular transportation system using the suite of services bundled on the RIPSAC platform. For example, one or more sensors may help in monitoring end-user vehicular driving such as acceleration and deceleration habits, driver's alertness, etc that may be utilized by the insurance companies for deciding the insurance premium and risk cover. Further, data collected by sensors located within the vehicle can be used to determine dynamic risk factors and help in accident avoidance, thereby reducing claims and exposure for the insurance company while in turn lowering premiums for the end user. Data collected by the sensors enable dynamic traffic control at a city level by collecting data about road conditions, vehicular density, etc. that when used in conjunction with GPS navigation will enable dynamic scheduling that can reduce bottlenecks and optimize commute time for all drivers.
In an exemplary embodiment, the platform would enable real-time editing of Word and PowerPoint documents within a car by a passenger through a visual interface or audio-based interface. In yet another exemplary embodiment, the platform enables real-time tracking of customer behavior and habits. The tracked behaviors are then utilized for advertising by the advertisers to occupants of the car, taking into account the role of the subject of advertising in the car. For example, for the occupant driving the car, the advertisers would target the occupant with audio advertisements and for the occupants in the back-seats would be targeted with visual advertisements. For both of the cases, the advertisements would be related to products or services that are related to tracked behaviors of all the occupants.
In an exemplary embodiment, the integration of the hardware and software platform enable multiple passengers in the same vehicle to perform various tasks associated

with business, entertainment, and communication they currently perform in the home or office. For example, the integrated platform allows lawyers to work on legal documents in the car while they are sitting in the passenger seat, children to do homework or play video games while they are riding in the back seat, insurance companies to monitor driver behavior in real time, and law enforcement officials to monitor drunk driving rules while a driver is driving the car. The various services and applications supported by the platform are as follows:
In an exemplary embodiment, the ITS (500) is configured to enable tracking behavior of the occupants in the vehicle using the suite of sensor, storage, analytics services bundled in the RIPSAC platform. The application involves the use of sensor observations, both present as well as past observations to learn the behavior of the occupants of the vehicle. This would include the driving habits of the driver and the actions / activities of the driver as well as other passengers. In an exemplary embodiment, one way of monitoring the cardiac activity of a driver is disclosed in the PCT Application PCT/IN2010/000581 wherein electrocardiography of a driver is monitored. Another technique of cardiac monitoring is disclosed in the PCT Application PCT/IN2010/000811 which includes a wearable and self-contained cardiac activity monitoring device that operates in multiple modes. In one of the modes the device wirelessly transmits the recorded electrocardiogram readings to a remote communication device(s). Activities other than driving include use of in-car entertainment systems, connected computers, vehicle controls and consumption of content using in-car systems. Using learnt behavior, occupants and their actions can be detected and tracked in real-time. This provides rich contextual information that can be used for variety of application including delivery of customized content, information and advertisement to occupants.

In an exemplary embodiment, the ITS (500) is configured to enable the In-vehicle anomaly detection using the suite of sensor, storage, analytics services bundled in the RIPSAC platform. In this exemplary embodiment, the In-vehicle anomaly detection involves monitoring and surveillance of the vehicle. The anomaly includes combined analytic output of a class of sensors. For example, an anomaly may include detection of any unexpected movement, unexpected sounds or even a sudden change in cabin temperature or light conditions of the vehicle. The major application of the anomaly tracking is to generate an alert based on the results of monitoring rather than a constant and continuous manual monitoring. The pattern matching, exception detection, movement detection and sound matching algorithms receives inputs from devices in vehicle such as cabin camera, cabin microphone, cabin-climate detection and notification devices to detect any unexpected conditions inside the vehicle. The In-vehicle anomaly further includes tracking in-cabin environment conditions by analyzing the parameters such as temperature, humidity, and thermostat etc. This can be considered to be a measure of climate control being used within the vehicles. The data is valuable since it allows the vehicle to auto adjust to the conditions based on the driver's preferences.
In an exemplary embodiment, the ITS (500) is configured to enable diagnosis of the vehicular components using the suite of sensor, storage, analytics services bundled in the RIPSAC platform. Diagnostics involves analysis of fuels levels, battery-capacity, Oxygen level, and accelerometer readings on the dashboard in order to ensure the vehicle safety and reliability in various different environmental conditions. These reading are sensed by different sensors such as dashboard sensor, accelerometer sensor and other sensors monitoring engine, transmission and other sub-systems. The values obtained from the sensors are analyzed using estimation and efficiency calculation algorithms. The output of the diagnostics tracking is to track or monitor the health of the vehicle and the possible problem areas in functioning of different

engine parts of the vehicle in order to avoid possible accidents. Further, a logging and tracing report can be generated at backend while the diagnostics tracking is in progress at vehicle premises providing detail activity report of the diagnostics data. In an exemplary embodiment, one way of capturing of sensing data from vehicle sensors for diagnosis and prognosis thereof has been disclosed in the pending Indian Patent Application Number 773/MUM/2011.
In an exemplary embodiment, the ITS (500) is configured to enable E-CALL Service from the remote vehicle using the suite of sensor, storage, analytics services bundled in the RIPSAC platform. The E-call is a service that allows a driver or a passenger to make an emergency call from the vehicle. The use of Telematics can be important in scenarios where cellular coverage may be hampered. Further, it may be vital in case the user does not have a cell phone which may have also got damaged during an accident. E-Call utilizes distress lines to make calls to emergency services and also automatically ask for help in case the passengers fail to respond. The purpose of the E-CALL is the detection of a disaster and making a call and to route the call using any available connectivity.
In an exemplary embodiment, the ITS (500) is configured to enable Region-based Tracking Service from the remote vehicle using the suite of sensor, storage, analytics services bundled in the RIPSAC platform. The region-based tracking involves tracking of vehicular information related to number of vehicles located in one specific region. This can be referred to an aggregated location-based service wherein the region based motion detection of multiple vehicles along with the traffic density is tracked for that particular region being monitored.
In an exemplary embodiment, the ITS (500) is configured to enable the post to ITS (Intelligent Transport System) Telematics service that allows posting of vehicle

sensor data to the transportation system for better traffic management. This service shall allow one time and periodic posting of vehicle data to the ITS. All the telematics analytics data sensed by different sensors in the vehicle is posted to the ITS for traffic management.
In an exemplary embodiment, the ITS (500) is configured to enable Citizen Sensor / Participatory Sensing service that involve active participation of citizens acting as citizen sensors those observe hazardous situations in a particular area such as crimes, natural calamities etc and report these observations in the form of audio or text data to the concerned authorities using their handheld devices. Since there may be wide variety of events that can be reported with varied skill levels of people, a standardized format for reporting is difficult. Therefore, a semantic analysis of citizen report data is implemented using NLP based algorithm for extract relevant information. Further the ITS platform also support mechanisms for rewarding contributors based on relevance and trustworthiness of the data.
In an exemplary embodiment, the various services as disclosed above are used for implementation of various real-time vehicular applications that are associated with the vehicle tracking and traffic management. Few of the applications are as follows:
In an exemplary embodiment, the ITS (500) with the support of RIPSAC platform enables development of Car Black-box application. Analogues to aeroplane's black-box, this application is responsible for sensing different parameters of the vehicle using in-built sensors. This application is utilized to remotely monitor the health status and thereby diagnostics of the vehicle. Further, this application is utilized to monitor the driver's driving habits in order to help physician and the insurance companies to perform post-accident tasks based on the monitored results.

In an exemplary embodiment, the present invention enables the ITS platform (500) to locate different users driving their vehicles in a real-time. For example, the ITS platform (500) monitors the driving details such as route map and time of day etc by sensing the location data of the vehicles of the participating users. Based on this analysis, a social graph is generated in real-time containing possible users driving their vehicles in a particular area.
In an exemplary embodiment, the ITS platform (500) using the suite of bundled sensor, analytics and storage services plays a vital role in helping the insurance companies decide risk cover and premium amount for different individuals based on their driving habits. For example, real-time capturing of driving characteristics such as traffic level, time of driving, type of roads frequently travelled, travelling distance may be analyzed to determine the risk associated with accident. Further, based on observed traffic characteristics for each of the individuals, the premium amount and risk cover can be decided so that both the insurance provider and the insured individual are benefited. In an exemplary embodiment, the edge platform in the vehicle comprising different sensors can quickly and efficiently assists with managing the insurance claims process. For example, from the accelerometer sensor data, the driving pattern of the driver and a crash can be detected. From the timestamps, the driving time and the time when actually the incident occurred can be detected. Faster the insurance company comes to know of the accident, claim amount will be less. In an exemplary embodiment, the traffic characteristics are monitored in real-time based on analysis of inputs from motion, location, time and diagnostic sensors. The analytics of the traffic details enable insurance provider to detect accidents quickly in order to receive less amount of claims. On the other hand, if the driver is a safe driver with good driving habits, he or she is eligible to pay fewer premiums for the insurance amount covered. These analytics enable reduction in

fraud claims and the insurance provider is able to monitor various characteristics of the vehicle, the vehicle driver in real-time.
In an exemplary embodiment, the ITS (500) can be implemented as a remote vehicle surveillance system. There is a high possibility of unauthorized intrusion or thefts of the vehicle. In order to avoid such mishaps, the remote surveillance system enables real-time monitoring of the activities in the vehicle from remote location by way of displaying the in-cabin panoramic view of the vehicle on the Smartphone of the owner of the vehicle.
In an exemplary embodiment, the ITS (500) can be implemented to develop an automated safety alert application using the suite of RIPSAC services. Often, the reason of accidents and mishaps is that the drivers seem to overlook or neglect the safety signs and or traffic signs. Also sometimes proximity to other vehicles around a corner or a sharp bend is not accounted for by drivers. In these scenarios, an audible or visual alert to the driver regarding the ignorance of safety norms can be life-saving. In an exemplary embodiment, the present invention enables such alerts by providing proximity sensors and notification actuators into the traffic signals and road-signs. Further, execution of aggregated localized analytics on vehicle motion provides details regarding proximity and extrapolation predicting collisions on the road. These details are then analyzed in real-time which is then can be used to generate alerts. Further, the current bad road conditions related information without any indications in the form of sign-board can be gathered from different mobile users using crowd sourcing and this information is disseminated to the drivers by way of real time generated notification alert.
In an exemplary embodiment, the ITS (500) with the support of RIPSAC service suite is configured to develop and deploy traffic guidance application. Rush hour

traffic management is a major concern for any city administrative body. Also in case of break-down and blockage especially in hilly terrain, the risk free traffic diversion becomes a major concern due to the limited availability of roads and their limited capacity. Further, in case of a disaster, one major concern of post-disaster management is evacuation. Here, due to the large volume of traffic from a particular source leads to the problem of congestion and panic. Therefore, a proper traffic management and thereby traffic shaping is required. According to an exemplary embodiment, the traffic shaping depends on major criterion such as identification of congestion or blockage or breakdown, an appropriate sizing and causal analysis of the problem, routing of emergency services and routing of normal traffic. In an embodiment, identification of a possible bottleneck is performed through analysis of the region based vehicle density to generate emergency notifications. The possible reasons for traffic congestion may be due to social event or procession, natural calamities or disaster, and accidents such as bride/tunnel outage etc. After identification of the problem, there are two major action items, to route the emergency services through the fastest path possible and then lead the people to their destination quickly and safely. These two are conflicting and dependent requirements which require intelligent traffic shaping. As a result of traffic shaping, traffic congestion can be avoided, emergency services can be provided on time and smooth evacuations can be efficiently managed by the concerned authorities.
In an exemplary embodiment, the ITS (500) with the support of RIPSAC service suite is configured to develop and deploy Rogue Driver Detection. In an exemplary embodiment, the present invention enables real-time detection of rouge driver based on the driving habits of the drivers. In an exemplary embodiment, one way of detecting rough driving and accordingly rough vehicle thereof is disclosed in the pending Indian Patent Application 2750/MUM/2011. If the telematics device installed in the vehicle is tampered or de-activated by a driver in order to escape its

driving habits being tracked, the reports are generated based on text or audio received from the individuals driving in the same region.
In an exemplary embodiment, the ITS (500) with the support of RIPSAC service suite is configured to develop and deploy a method and system of transmitting information from source device to destination by means of audio commands embedded in the vehicular horn. One way of such implementation is being disclosed in 314/MUM/2012 wherein audio information is broadcasted via a smart horn embedded in the vehicle which is interpreted by the application installed at the receiving station in order to take further steps. Further, the ITS (500) with the support of RIPSAC service suite is configured for managing unmanned Railway check posts. One way of managing unmanned railway check posts has been disclosed in 2335/MUM/2011 wherein, when the train is in proximity of an unmanned level crossing the system notifies all the mobiles in the vicinity of said level crossing.
In an exemplary embodiment, the ITS (500) with the support of RIPSAC service suite is configured to develop and deploy a method and system for damage assessment of object. One way of such assessment is disclosed in 2751/MUM/2011, wherein damage assessment of an object is done by converting the visual data of the object into Multi-Dimensional (MD) representation and by identifying a set of characteristic points and a set of contour maps from the said MD representation of the object.
In an exemplary embodiment, the ITS (500) with the support of RIPSAC service suite is configured to develop and deploy an application of tourist guidance and navigation thereof, One way of facilitating such tourist guidance and navigation has been disclosed in 3367/MUM/2011, wherein a tourist information is embedded in an

encoded metadata at the source station which is retrieved by accessing a web link received along with encoded metadata at the destination station. Further, in another exemplary embodiment, the ITS (500) is configured for determining fatigue time of an activity in the vehicle. One way of determining fatigue time of an activity is disclosed in 3550/MUM/2011 wherein actual fatigue time (AFT) for an activity is determined based upon received standard fatigue time (SFT) and a fatigue index corresponding to one or more external parameters.
In an exemplary embodiment, the present invention supports real-time context based advertising based on data collected by various sensors deployed in the vehicle premises. For example, in this embodiment, real-time monitoring of customer behaviors and habits is implemented utilizing various sensor devices. These monitored behaviors and habits of the customer are used for context-based advertising by advertisers to occupants of a car, taking into account the role of the subject of advertising in the car. For example, if the customer in the car is a driver, he or she will be targeted with audio advertisements in the front seat relevant to his or her profile. If the customer is a backseat passenger, then he or she will be targeted with video advertisements in the back-seat. Thus, the context-based advertising in accordance to this exemplary embodiment supports regulatory requirements (e.g. audio advertisements in the front seat and video advertisements in the backseat).In yet another exemplary embodiment, the context-based advertising includes real-time generation of user-specific profiles based on tracked telematics data inside the vehicle. Based on the generated profiles, each individual user will be targeted with advertisements from different advertisers in context to the user-specific profile. More specifically, multiple users will be targeted.

Referring to figure 7 is a flow diagram illustrating steps designed to enable the R1PSAC platform to perform the task of real-time analytics of any smart-space environment according to an exemplary embodiment.
At step 701, sensor-based data in assorted formats is captured from one or more sensors deployed in the smart-space environment.
At step 703, the sensor-based data is pre-processed the captured data to extract relevant sensor-based information and enable storage thereof in a database.
At step 705, real-time analytics on the stored sensor-based information is performed to derive insights, inferences and visualized data therefrom.
At step 707, a set-of bundled services and algorithms in the RIPSAC is utilized to develop, test and deploy one or more sensor-based applications based on the results of real-time analytics.
Referring to figure 8 is a flow diagram illustrating steps designed to enable the ITS platform with support of the RIPSAC services to perform the task of real-time analytics of a vehicular transportation according to an exemplary embodiment
At step 801, sensor data-feeds in assorted formats from one or more sensors deployed at the proximity of vehicles is acquired.
At step 803, the acquired sensor-based data is pre-processed to exclude raw data and extract featured sensor data therefrom essential for anomaly detection.

At step 805, a software-web enablement (SWE) service is enabled for storage and retrieval of said featured sensor data.
At step 807, a set-of bundled analytics services and algorithms in the RIPSAC is utilized to develop, test and deploy one or more sensor-based applications facilitating vehicle anomaly detection and prognosis.
At step 809, real-time alerts or visualizations are sent to the subscribed device regarding the detected anomaly in the vehicular transportation.
The preceding description has been presented with reference to various embodiments of the invention. Persons skilled in the art and technology to which this invention pertains will appreciate that alterations and changes in the described structures and methods of operation can be practiced without meaningfully departing from the principle, spirit and scope of this invention.
ADVANTAGES OF THE INVENTION
The present invention has following advantages:
• The present invention enables a platform-as-a-service cloud computing platform that allows quick and easy development, deployment and administration of sensor driven applications.
• The present invention provides an integrated platform for sensor data capture, storage, analytics, and visualization etc.
• The present invention enables easy development and deployment of applications developed by many different third party developers using a set of services are made available in form of Application Programming Interfaces

(APIs) and Software Development Kits (SDKs).
• The present invention enables multiple sensor data providers, multiple application developers and application end users to connect with the platform in a secure and mutually isolated way for accessing various services and application facilitated by the platform.
• The present invention enables sensor data to be shared across applications and users by facilitating policy driven data privacy and policy driven data on the platform.
• The present invention enables the platform to interface with any kind of sensor and is independent of type of the sensor and sensor data observation.
• The platform of the present invention provides scalable sensor data storage for a wide variety of sensors and sensor observations and provides scalable analytics services.
• The present invention enables Intelligent Transportation Service (ITS) platform that incorporates a suite of services focused on Safety and Security for the vehicle, driver, passengers and other road users.
• The proposed ITS allow application developers to select a service and an appropriate algorithm thereof from a set of algorithms best suited for the domain.
• The ITS allows application developers to test their algorithms with some test data from the platform.
• The ITS on the RIPSAC is flexible to allow for development of new algorithms and plug-in these in the platform for future developments in same domain.
• The present invention enables advertisers to target potential customers based on real-time analytics data that analyzes the user habits or behaviors.

Claims:
1. A system for providing infrastructure platform in a smart-space environment that
facilitates quick and easy development, deployment and management of sensor
driven applications, said system comprising:
a) a suite of infrastructure services integrated to the platform configured to acquire, store and analyze sensor data received from a plurality of sensor device;
b) a plurality of application program interface (APIs), programming language specific libraries and software development kit (SDKs) provided to application developers to utilize said infrastructure services in order to develop, test, deploy and manage a plurality of sensor-based application;
c) a presentation module comprising a plurality of web-based portals adapted to monitor, manage and control said infrastructure services, developed applications and software & hardware infrastructure; and
d) a suite of infrastructure applications configured to transmit/receive sensor data to/from the platform.

2. The system of claim 1, wherein the suite of services comprise one or more of: device integration and management, analytics, messaging & event distribution, data storage and query, sensor management, application support services, user interface & visualization and security, access control &privacy policy services.
3. The system of claim 2, wherein device integration and management is enabled using a set of devices consisting of but not limited to device sensor adapters, device management adapters, sensor integration adapters, web-service interface or combinations thereof.

4. The system of claim 2, wherein said device integration and management services are configured to interface varied sensor devices, facilitate support for networking protocols enabling data communication, monitor the health and status of said sensor devices, deploy software on the sensor devices from the infrastructure platform or combinations thereof.
5. The system of claim 2, wherein said messaging & event distribution services are adapted for passing of messages and events across the infrastructure platform services and applications built therefrom.
6. The system of claim 2, wherein said data storage & query services are configured to enable distributed sensor data storage and querying said sensor data storage.
7. The system of claim 2, wherein said sensor management services are configured to enable sensor discovery, description of sensor and sensor data observations, feature description, inserting observations, querying observations or combinations thereof
8. The system of claim 2, wherein said application support services are configured to provide support for service integration and orchestration thereof
9. The system of claim 2, wherein said application support services are configured to enable identity management, policy driven access control, data privacy controls& data masking and authentication of various category of users accessing the platform.
10. The system of claim 1, wherein said presentation module comprises an
application developer portal adapted to enable various application developers to

register with the platform, register their applications, create databases, a administrator developer portal adapted to enable various administrators to monitor, manage & control the usage of underlying software & hardware infrastructure and platform services by the tenants and a subscriber portal adapted to enable various subscribers to download apps, subscribe & unsubscribe to them, control privacy settings, and view usage history and billing information.
11. The system of claim 1, wherein said infrastructure application includes a software infrastructure comprising a plurality of application server configured to host the end-user executing applications, analytics servers, relational and document databases to store the data and documents related to said applications.
12. The system of claim 1, wherein said infrastructure application includes a data center infrastructure comprising a computer, network & disk storage resources as a underlying hardware/virtual hardware infrastructure, file servers providing file storage services and firewalls configured to create secure zones based on policies to separate different platform users or applications from each other.
13. A smart-space infrastructure platform delivered as a service over a network of devices connected in a network, said platform comprising: a standardized web-based interface facilitating sensor data management, sensor applications development using suite of infrastructure services and deployment of sensor applications on the end-user subscriber device, the web-based interface further facilitating management and control of tenants, subscribers and application developers usage history and billing information against utilization of platform services and underlying hardware & software resources.

14. The platform of claim 13, wherein an application developer is enabled to develop
a sensor based application by using APIs and SDKs binding the infrastructure
services.
15. The platform of claim 13, wherein such platform includes sensor data
acquisition, sensor data storage and sensor data analytics, alerting end-user
subscribing devices results of analytics and consequences thereof
16. The platform if claim 13, wherein application developers are able to plug-in the developed apps with such platform that can be used by end-user subscribers for data retrieval and analysis.
17. The platform of claim 13, wherein such platform integrates plurality of software components, libraries, software developments tools enabled to pre-process and store data captured from a plurality of sensor and disseminate analyzed data to plurality of end-user subscribers.
18. A method for providing infrastructure platform in a smart-space environment
characterized in facilitating quick and easy development, deployment and
management of sensor driven applications, the method comprising steps of:
a) configuring a platform for execution of computational activities for facilitating dynamic development, deployment and administration of a plurality of sensor driven application;
b) integrating a plurality of software component, libraries, infrastructure services, software developments tools to said platform to pre-process and store data captured from a plurality of sensor and disseminate analyzed data to a plurality of subscriber;

c) providing a plurality of application program interface (APIs) and software
development kit (SDKs) for a plurality of application developers to develop,
test, deploy and manage one or more sensor driven applications in said platform;
d) configuring service orchestration to each of the registered subscriber and
application developer with said platform using a user specific access and
permissions and implementing orchestration logic using a standard web service
orchestration engine; and
e) configuring the infrastructure platform to monitor, manage and control the
utilization of service infrastructure, hardware & software infrastructure and
sensor applications by different categories of users.
19. The method of claim 18, wherein the infrastructure services comprise of device integration, analytics, messaging, sensor management, application support services, user interface and visualization , and security, access control and privacy policy services.
20. The method of claim 18, wherein device integration and management service comprises services for interfacing gateway devices, sensors, mobile devices and corresponding network addresses thereof by means of device specific software modules including device sensor adapters, device management adapters and sensor integration management adapters or combinations thereof.
21. The method of claim 18, wherein said sensors are dynamically coupled with the infrastructure platform and are seamlessly integrated for ad-hoc data gathering.
22.The method of claim 21, wherein a plurality of category of sensors are integrated with the platform comprising of soft sensors, physical sensors, and

virtual sensors, each being scalable at an instance by means of dynamic addition of servers capable of processing sensor data depending on the load on the present servers handling sensor data.
23.The method of claim 18, wherein the infrastructure platform is configured to continuously/intermittently/upon request receive data from each of the integrated sensors that are pre-registered and authenticated with the platform such that an extent of data usage and dissemination is dynamically governed by owner thereof.
24. The method of claim 23, wherein the observation data from the said sensors can
be accessed through synchronous polling based mode or asynchronous
notification based mode and filtered by temporal, spatial, spatio-temporal, or
value based filtering criteria.
25. The method of claim 18, wherein said development and management of
applications includes one or more of creating, testing, initiating, stopping,
restarting, upgrading, modifying, deleting, deploying, and un-deploying plurality
of sensor driven applications.
26.The method of claim 18, wherein said infrastructure platform can be used for creating smart space applications and services in diverse sectors consisting of but not limited to energy, government, transportation, healthcare, education or combinations thereof.
27.The method of claim 18, wherein the monitoring, management and control of service infrastructure, hardware & software infrastructure and sensor driven applications is implemented by means of standard web-based portals in the platform.

28. An intelligent transportation system comprising:
a) an infrastructure platform comprising plurality of hardware & software
components, infrastructure services, Application Program Interfaces (APIs),
Software Development Kits (SDKs);
b) a plurality of sensor device intermittently connecting with the infrastructure
platform by means of communication networks;
c) a vehicle telemetry application development means electronically coupled with
the infrastructure platform and the plurality of sensor device; and
d) said vehicle telemetry application development being facilitated using a
service-oriented architecture (SOA) which allows application development
and deployment thereof by means of data and infrastructure reusability.
29. The system of claim 28, wherein the hardware components comprises computer
machines, virtual machines, servers, disks, network resources or combination
thereof.
30. The system of claim 29, wherein the hardware components are configured by
plurality of software components embedded in the platform.
31. The system of claim 28, wherein the infrastructure services comprises an edge
analytics service, a backend storage service, a backend analytics service, a
reporting service or combinations thereof.
32. The system of claim 31, wherein said edge analytics service is adapted to
perform analytics on sensor data feeds by means of preprocessing and feature
extraction that leads to data reduction and allowing for storage of only features
rather than raw sensor data.

33. The system of claim 31, wherein said backend storage service is configured to enable storage and retrieval of sensor data by means of a Sensor Observation Service.
34. The system of claim 31, wherein said backend analytics service is configured for performing analytics on the back-end subsystem enabling classification, clustering of stored sensor data.

35. The system of claim 31, wherein said reporting service is adapted to provide audio/visual alerts to plurality of end-user subscribers based on the results of analytics run on the sensor data.
36. The system of claim 28, wherein the sensor devices are adapted to sense varied physical quantities in the smart vehicle environment including but not limited to temperature, pressure, location, motion, gyroscope, acceleration, deceleration, cardiac data or combinations thereof.
37. The system of claim 28, wherein the vehicle telemetry application development means enables application developers to invoke the plurality of services and computing algorithms therefrom by means of APIs and SDKs to develop diverse vehicle telemetry applications in the platform.
38. The system of claim 28, wherein said vehicle telemetry applications comprises from a group consisting of but not limited to pot-hole detection, rough-vehicle detection, cardiac-activity monitoring, in-car diagnostic and prognosis thereof, remote-photography, remote tourist guidance, driver-drowsiness identification, remote sleep-detection, remote damage assessment, managing unmanned railway-check posts, remote vehicle communication or combinations thereof.

39. The system of claim 28, wherein the vehicle telemetry application development means enables plug-in of additional customized vehicle telemetry applications developed by the application developers using desired services and algorithms in the platform.
40. The system of claim 28, wherein a plurality of category of sensor devices are integrated with the platform comprising of soft sensors, physical sensors, and virtual sensors or combinations thereof.
41. An intelligent transportation infrastructure platform delivered over a network configured to provide sensor data management and deployment of vehicle telemetry applications, said platform comprising: a plurality of infrastructure services enabling application developers to develop a plurality of sensor driven applications using APIs and SDKs, a plurality of end-user subscribers being connected with the platform for downloading and using the applications developed, and a plurality of web-based portal tracking infrastructure services and sensor driven applications by application developers and end-user subscribers respectively.
42. The platform of claim 41, wherein an application developer is enabled to easily, quickly , and in a user friendly manner develop, test and deploy vehicle telemetry applications using the infrastructure services and algorithms therefrom.
43. The platform of claim 41, wherein such platform includes services for sensor data acquisition, storage and analytics thereof along with services for device integration, data visualization capabilities, reporting capabilities enabled through audio/visual alerts, privacy support or combinations thereof.

44. The platform of claim 41, wherein such platform being used to develop and deploy vehicle telemetry applications including but not limited to pot-hole detection, rough-vehicle detection, cardiac-activity monitoring, in-car diagnostic and prognosis thereof, remote-photography, remote tourist guidance, driver-drowsiness identification, remote sleep-detection, remote damage assessment, managing unmanned railway-check posts, remote vehicle communication or combinations thereof.
45. The platform of claim 41, further comprising an administrator portal allowing various administrators to monitor, manage & control the usage of the underlying software and hardware infrastructure and platform services for development of vehicle telemetry apps by the tenants/application developers, an application developer portal allowing various application developers to register with such platform, register their vehicle telemetry applications, create databases, upload and test software programs and an end-user subscriber portal allowing various subscribers to download vehicle telemetry apps, subscribe & unsubscribe to them, control privacy settings, and view usage history and billing information.
46. A method for providing an intelligent transportation platform, the method
comprising steps of:
a) integrating a suite of bundled services on the said platform capable of executing algorithms, functions and calls to develop a suite of sensor driven applications for sensor data feeds received from sensor devices;
b) providing a plurality of application developers flexibility to select services and algorithms relevance in context with the domain of the sensor driven application to be developed thereof; and

c) configuring the platform to enable application developers to develop new sensor driven applications and algorithms thereof using selected services from the suite of bundled services.
47. The method of claim 46, wherein the sensor devices are adapted to sense varied
physical quantities in the smart vehicle environment including but not limited to
temperature, pressure, location, motion, gyroscope, acceleration, deceleration,
cardiac data or combinations thereof
48. The method of claim 46, wherein a suite of services includes an edge analytics service that is adapted to perform analytics on sensor data feeds by means of preprocessing and feature extraction that leads to data reduction and allowing for storage of only features rather than raw sensor data.
49. The method of claim 46, wherein a suite of services includes a backend storage service that is configured to enable storage and retrieval of sensor data by means of a Sensor Observation Service.
50. The method of claim 46, wherein a suite of services includes a backend analytics service that is configured for performing analytics on the back-end subsystem enabling classification, clustering of stored sensor data.
51. The method of claim 46, wherein a suite of services includes a reporting service
that is adapted to provide audio/visual alerts to plurality of end-user subscribers
based on the results of analytics run on the sensor data.

52. The method of claim 46, wherein said sensor data feeds are captured through onboard/off-board vehicular sensors, Smarthphones, proximity sensor gateway devices and other intelligent sensing devices or combinations thereof.
53. The method of claim 46, wherein said sensor devices includes diverse category of sensors such as physical sensors, virtual sensors, soft sensors or combinations thereof.
54. The method of claim 46, wherein said sensor driven applications facilitates vehicle anomaly detection and prognosis thereof and is focused to enable safety and security for the vehicle, driver, passengers and other road users.
55. The method of claim 46, wherein said algorithms, functions and calls are executed depending on the nature of service and the context of application to be developed, test and deployed.
56. The method of claim 46, wherein said platform providing test data to the application developers for testing the newly developed sensor driven applications and algorithms thereof.

57. The method of claim 46, wherein said platform facilitates plugging-in the newly developed sensor driven applications and algorithms thereof on the bundle of services for facilitating further application development and thereby data reusability