DESC:BACKGROUND OF THE INVENTION
Problem Statement:
[0001] Tourist safety is an important, but complex issue to manage because of many reasons such as capacity planning for a city, non-availability of data about number of tourists visiting the city at any instant of time, total accommodation capacity of the city, distribution of tourists in a city and other parameters. Furthermore, the local administration does not have information of tourist location and their volume to plan for optimum capacity utilization and distribution of tourists to safely accommodate all visiting tourists. Additionally, the number of tourists and the location keeps changing continuously over time, which makes it difficult to manage issues. For example, a major challenge is the sudden appearance of a large crowd in a shrine or pilgrimage. In addition, the tourists may be visiting the city for the very first time and are not acquainted with the place and culture. Tourist safety requires a tourist management system, which can proactively detect the problem early-on and can take preventive actions.
[0002] In addition, India has one of the largest rail and road networks in the world. Travel conditions in India are highly unpredictable due to multiple factors such as road traffic frequently getting disturbed and detoured for various reasons; extreme weather conditions; religious events; festivals; bad road conditions; rallies and agitations; peak holidays seasons etc. There is no specific way to connect and monitor traffic on the road that is caused by road blocks, traffic congestion, natural disasters such as landslides, accidents and other parameters. Furthermore, for local governance, road traffic, tourist movement, and even for broadening of roads, the traffic information such as congestion data, movement data, and other parameters must be known.
Solution:
[0003] In view of the above concerns, a need for tourist safety, tourist navigation and flow-management is required. The tourist safety and management system provides an optimized way of handling individual emergencies, for example, accidents, theft, loss of travel documents, sickness etc. Likewise, a different type of emergency may be a mass emergency, for example, flash floods, strikes, roadblocks due to agitations, floods, landslides, riots etc. In order to cater to these challenges, a Tourist Safety and Information System (TSIS) is proposed.
[0004] The tourist safety and information system is a unique and novel approach of handling different factors associated with tourism. In addition, the tourist safety and information system addresses most of the problems. The tourist safety and information system integrates the data from multiple sources and uses artificial intelligence algorithms to provide and forecast the likelihood of an undesired event and warn the tourists and other stakeholders to take accordingly precaution. The tourist safety and information system uses a combination of different technologies such as location determination, navigational path, data analytics, artificial intelligence and machine learning along with human behavioral science to predict problems and to timely notify the authorities and further to provide guidance for tourist safety. The tourist safety and information system bridges the communication gap between tourists, the state administration and the travel service providers. Based on the current location of the tourist, the tourist safety and information system can provide any type of help required for the safety of the tourists. Furthermore, the tourist safety and information system is integrated with different government and private agencies so that vital information can be received/sent for quick action and to formulate a quick disaster management strategy for the safety of the tourists.
SUMMARY OF THE INVENTION
[0005] A computer implemented method for a tourist safety, real time information, updates alerts and forewarnings of the navigation route, locating a tourist during an emergency, real time monitoring of navigational route and one or more destinations, a predictive crowd analysis, providing assistance and emergency services to a tourist is disclosed. The computer implement method comprises: receiving real time data from multiple sources including a client unit; tracking the real time navigation route of the tourist; aggregating the data collect from multiple sources at a central server in real time; characterized by applying deep learning algorithms at the central server to analyze the current situation based on at least one parameter; comparing the at least one parameter with threshold value set for that parameter; raising an alert to the at least one of the stakeholders, when at least one of the parameters is greater than the set threshold value; locating the current location of the tourist and assessing the current situation, and using artificial intelligence and machine learning algorithms to provide a corrective action to the tourist in shortest time, and informing the stakeholders and at least one client unit of the corrective action to cater to the emergencies.
[0006] In some embodiments, the central server maintains a blockchain related to the movement of the tourist.
[0007] In some embodiments, the tourist registers with the central server by providing identity credentials for validation of the profile of the tourist, which is utilized for validation of the tourist credentials at one or more points of interest for establishing the identity of the tourist and for tracking the location of the tourist.
[0008] In embodiments, the central server implementing deep learning algorithms is trained to provide prediction of an unforeseen emergency based on one or more parameters.
[0009] In embodiments, the central server provides a process and system for dividing the area of influence into logical cells, manages the movement of each client unit in the area of influence, and exchanges information among the different client units to share information related to nearby points of interest. Furthermore, the exchange of information among different client units is related to at least one of a query, point of interest, emergency or merchandise.
[00010] In embodiments, the central server includes a tourist safety module implementing deep learning algorithms to monitor the navigation route of the tourist to the destination and for providing timely information related to predicted events for the safety of the tourist. The deep learning algorithms are related to monitoring current carrying capacity, road blockade, weather, safe/unsafe conditions of the navigational route. The deep learning algorithms provide forecasting related to at least one of a predictive crowd analysis, an emergency service and an alternate route during traffic jams.
[00011] In embodiments, each client unit acts as a retransmitter of information when at least one of the client units is unable to connect directly to the central server.
[00012] A tourist safety and information system for providing real time information, updates alerts and forewarnings about the navigation route for tourist safety and for locating a tourist during an emergency, real time monitoring of navigational route for one or more destinations, a predictive crowd analysis, the tourist safety and information system includes a client unit having a unique client identification number and configured to aggregate real time data from multiple sources; a central server configured to receive the aggregated real time data from at least one client unit and other sources. The central server includes a machine learning module, which is characterized by implementing deep learning algorithms to analyze the current situation related to at least one parameter associated with the navigation route to the destination; comparing the at least one parameter with a set threshold value of that parameter stored in the central server; raising an alert to the at least one of the stakeholders and the client unit, when at least one of the parameters is greater than the set threshold value; applying predictive analysis using machine learning algorithms to predict an unforeseen situation or an emergency to provide a corrective action to the tourist in the shortest time for an unforeseen situation or an emergency and informing one or more stakeholders and one or more client unit of the corrective action to cater to the emergencies.
[00013] In embodiments, the unforeseen situation or an emergency may be related to overcrowding, accident, outbreak of a disease, electricity failure, dispute or medical emergency.
[00014] In embodiments, the at least one parameter may be related to number of people at destination, traffic condition on the route, weather conditions, landslides, rains, city capacity and government orders
[00015] In embodiments, the client unit may be a tablet, a navigation device or an application in a mobile phone.
[00016] In embodiments, the central server comprises a machine learning module implementing deep learning algorithms initiate steps of: dividing the geographical region into logical cells based on a predefined criteria; tracking each client unit in each of the logical cells; collecting information from each client unit in each of the logical cells, and analyzing the information collected from each client unit in each logical cell to alert one or more tourists about points of interests and unforeseen situations. In some embodiments, the predefined criteria associated with the division of logical cells is based on the geographical landscape.
[00017] In one embodiment, the points of interest suggested by the central server for the current and the nearby logical cells may be based on the profile of the tourist.
[00018] The machine learning module of the central server aggregates data related to the build up of crowds at different locations within the points of interest. In embodiments, the points of interest may include but are not limited to religious places, tourist spots, shrines, wildlife sanctuary, popular tourist places, a dham, a char dham yatra or a holiday destination for prediction of unforeseen emergencies. The data aggregation for prediction of unforeseen emergencies may include but is not limited to data collected from tourism service providers registered with the central server, historical tourist data visiting a particular point of interest or a religious place, data aggregated from visual and other devices such as not limited to cameras, visual surveillance devices, security devices, registration with local authorities and government departments for entering the a particular point of interest, and the number of tourists in each logical cell. In addition, the machine learning module, which is associated with the central server, maintains a list of the number of client units entering and/or leaving each logical cell. Furthermore, the client unit can change the navigation tour based on the unforeseen emergency and dynamically make booking due to unforeseen reasons during the travel.
[00019] Disclosed is the method and system for a tourist's safety for providing real time information to a tourist. A tourist safety and information system includes a central server, a client unit apart from other systems. The central server implements deep learning algorithms to guide and suggest at least one tourist or a group of tourists as per their requirements and further ensure safety, manage tourist flow, overcrowding and create intelligence for management of tourists in a city, region or geographical location. The client unit, which may be embedded in the tourist vehicle, connects wirelessly with the central server to provide real time updates on different aspects related to safety, security of the tourist. Alternatively, each mobile phone of the tourist may act as the client unit to provide assistance and guidance during a tour, for example providing navigation guidance during travel in real time.
[00020] In one embodiment, the client unit may be in the form of a hardware device. In another embodiment , the client unit may be a software application, which can be downloaded and installed on a mobile computing device such as but not limited to a tablet, a phone, a tablet or some other type of mobile computing device.
[00021] The client unit may provide information to the tourist related to government rules and regulations, navigation path, medical help, traffic related information, personal emergency related information and mass emergency related information. Accordingly, the tourist safety and information system associated with the central server may provide structured information categorized into at least three levels, that is (a) normal operation mode, (b) pre-incidence preparedness mode, and (c) post-incidence mode.
[00022] In normal mode of operation, the tourist safety and information system may provide tourism related information on the client unit or the mobile device related to but not limited to weather reports, navigational updates, current capacity at different destinations based at least on navigational path, total capacity of the navigational path, crowd situation at different destinations, queue situations at different historical monuments.
[00023] The client unit or the mobile device may analyze information based on self-learning from the data aggregated from the different sources. However, in preferred embodiment, the client unit or the mobile device handshakes with the central server to exchange data and/or information collected by it and provides the shared data to the tourist data in an encrypted form for analysis. The analyzed data provides meaningful assistance or suggestion or guidance. In some embodiments, the client unit or the mobile device may analyze the aggregated data and process it and to create meaningful information as a background process.
[00024] In some embodiments, the central server may utilize self-learning, which may be implemented by the machine learning algorithms. In some other embodiments, the central server may implement artificial intelligence by implementing a rule based engine that analyzes the received information to provide meaningful suggestions and safety information to the tourists.
[00025] In some embodiments, the client unit is implemented on a mobile phone. The mobile phone has a display, which may provide real time updates and safety suggestions on a display of the mobile phone. Besides, the mobile phone may also provide audible information from time to time. By clicking a button on the application, the full screen mode may be enabled on the display of the mobile phone.
[00026] In some embodiments, under normal operation mode, the tourist safety and information system may provide information and tips for driving, that is, a real time assistance to the drivers, specifically in difficult terrain or during driving on mountains with sharp turns.
[00027] In embodiments, the central server may execute several processes to analyze and monitor situations using data obtained from different sources. In embodiments, the situation may be related to analyzing traffic data, tourist data, pandemic data, weather data, hotel availability data, traffic movement data, emergency data and health data or some other type of data.
[00028] In some embodiments, the identity credentials of the tourist may be converted into digital signature/digital token using encryption, which can be provided to the client unit or the mobile device for authentication at different points of interest. Furthermore, in some embodiments, the digital token/digital signature may be utilized to track the location of the tourist in case of emergency or atleast to determine the last location of the tourist, if the tourist goes missing.
[00029] In some embodiments, the digital signature/digital token can be used to establish the identity of the tourist in case of emergency. When the digital token/digital signature is stored in the mobile device, the mobile device carried by the tourist may scan nearby client units or mobile devices and connect with them or connect with the central server to send a distress signal. In some embodiments, if the mobile device is unable to connect directly to the central server then the mobile device can connect through other client units or the mobile devices in vicinity to make a connection with the central server and ask for help. The client unit or mobile device may establish connection with nearby client units or the mobile devices through bluetooth, Wifi or NFC or other technologies.
[00030] In embodiments, the tourist may be a person of any nationality, gender, race, caste or a pet accompanying a tourist.
[00031] In embodiments, the central server may provide emergency services at a click of a button on the display of the client unit.
[00032] A computer implemented method for tourist safety, providing real time information, updates alerts and forewarnings about the navigation route, locating a tourist during emergency, real time monitoring of navigational route and one or more destinations, predictive crowd analysis and providing quickest assistance and emergency services to a tourist, the computer implement method comprising: receiving real time data from multiple sources including a client unit having installed mobile application; tracking the real time navigation route of the tourist; aggregating the data collect from multiple sources at a central server in real time; applying deep learning algorithms at the central server to analyze the current situation related to at least one parameter; comparing the current situation of at least one parameter with a threshold value of that parameter; raising an alert to the at least one of the stakeholders and the tourist about the current situation, and using artificial intelligence and machine learning algorithms to provide a corrective action and accordingly informing the stakeholders of the corrective action to cater to at emergency.
[00033] The central server maintains a blockchain of the movement of the tourist. The tourist registers with the central server by providing identity credentials for validation and once the identity credentials are validated then the central server provides a digital token for validation of the tourist at different points of interest. The digital token is further utilized for tracking the location of the tourist, when the tourist validates the credentials at any point of interest.
[00034] In embodiments, the central server divides the area of influence into logical cells and manages the movement and exchange of information among the different client units. The exchange of information among different client units may be related to at least one of a query, point of interest, emergency or merchandise and the like.
[00035] In embodiments, the central server maintains a check to filter out any objectionable content exchanged among client units.
[00036] In embodiments, the client units may act as a retransmitter of information when at least one of the client units is unable to connect directly to the central server.
[00037] In embodiments, the central server implements at least one of the a predictive crowd analysis, an emergency help and alternate route planning during congestion of a planned route.
BRIEF DESCRIPTION OF FIGURES
[00038] Fig. 1 illustrates the operating environment of a tourist safety and information system in an embodiment of the present invention;
[00039] Fig. 2A illustrates different components of a central server in an embodiment of the present invention;
[00040] Fig. 2B illustrates different components of a tourist safety module of the central server in an embodiment of the present invention;
[00041] Fig. 3A illustrates the different components of a client unit in an embodiment of the present invention;
[00042] Fig. 3B illustrates the different modules of a tourist module of the client unit in an embodiment of the present invention;
[00043] Fig. 4 illustrates a process flow of the tourist safety and information system in an embodiment of the present invention;
[00044] Fig. 5 illustrates a process flow for converting identify of a tourist into digital signature/digital token in an embodiment of the present invention;
[00045] Fig. 6 illustrates a process of locating points of interest in current cell or neighboring cell in an embodiment of the present invention;
[00046] Fig. 7 illustrates a process for connecting with the central server using one or more client units in vicinity in an embodiment of the present invention.
[00047] Fig. 8 illustrates a process of dynamic interaction between a tourist and a tourist community through the central server using one or more client units in an embodiment of the present invention;
[00048] Fig. 9 illustrates a process to monitor a tourist region for tourist safety and overcrowding in an embodiment of the present invention;
[00049] Fig.10 illustrates a process of handling overcrowding by uncovering nearby tourist points of interest in the vicinity in an embodiment of the present invention.
DETAILED DESCRIPTION OF THE INVENTION
[00050] In the following description of the tourist safety and information system, reference is made to the accompanying drawings which form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. The specific embodiments are not limiting and merely for illustration purposes. The invention can be practiced in many other different ways using the novel concept disclosed in the following description. The present invention is drawn to, among other things, apparatus, systems and methods for a portable electronic device that incorporate different state of art technologies such as triangulation, EDGE, Wifi, Bluetooth for location determination and other route navigation related service.
[00051] FIG. 1 illustrates an operating environment of a tourist safety and information system in an embodiment of the present invention. The operating environment 100 includes the tourist safety and information system 102, one or more data aggregator, multiple stakeholders, a central server 104 and one or more vehicles 106 such a vehicle 106A, a vehicle 106B or a vehicle 106C. Each tourist vehicle 106A is fitted with or associated with at least one client unit 108 with individual client units such as a client unit 108A, a client unit 108B, and a client unit 108C as shown in Fig. 1.
[00052] It may be noted that individual vehicles are denoted by numeral 106A, 106B and 106 C and plurality of vehicles are denoted by the numeral 106. Likewise, individual client units are denoted by 108A, 108B, 108C and the plurality of client units are denoted by numeral 108. In current implementation only three vehicles are shown but in different embodiments, the tourist safety and information system 102 can include more than or less than three vehicles, for example from a single vehicle to over 100,000 vehicles.
[00053] . The central server 104 may connect with a satellite or mobile network for accessing GPS data 110. The GPS data 110 can also be obtained in different ways, for example using GPS tracking through GPS servers dispersed over a geographical area. In addition, the central server 104 may access Wi-Fi data 112 by connection to Wi-Fi server or other wireless devices. The central server 104 can access Geographical Information System (GIS) data and digital map 132 provided by both government and private companies and other navigational websites, for example google maps. Likewise, the central server 104 may access government data 118 through the Internet or through LAN/WAN or using the cloud services. The tourist(s) may also provide access to their personal data 120, which is kept confidential in an encrypted form and exchanged with other devices/point of interests for validation of the tourist(s). The central server 104 may also access location capacity 130 of the points of interest. The location capacity is the maximum holding capacity of any tourist attractions, religious places, shrines and/or historical cities. This location capacity 130 includes information related to the maximum number of tourists and vehicles that can be accommodated including private and public infrastructure. Similarly, the central server 104 may also access travel and tourism data 122 associated with a particular destination, navigation path, routes, alternative routes for the travel including any alert and warning or blockages in a specific navigational path. The central server 104 may also access weather data 134 associated with the tourist’s destination such as weather forecasts, including those that are within a specified radius. In addition, the central server 104 may store and access emergency data 124 associated with the tourist. In some embodiments, the emergency data 124 may be associated with accidents, blockages, and landslides etc in a navigational route. The central server 104 may also access road and traffic data 128 such as maps, terrain, road network etc.
[00054] The central server 104 can access and exchange information with the vehicle 106A, which includes a client unit 108A. The client unit 108A connects with the central server 104 for accessing data related to traffic, emergency, government compliance, travel, and tourists places to be processed and displayed to the tourist on the client unit 108. The client unit 108A is associated with vehicle 106A or installed within the vehicle 106A. Likewise, the client unit 108B is associated with the vehicle 106B. The client unit 108A associated with vehicle 106A may access the central server 104 for sending/receiving data for tourist safety and other information. In addition, the client unit 108A can connect with one or more servers associated with either the client unit 108A directly or through the central server 104 to access travel and tourism data 122 comprising routing and navigation information, tourism attractions, accommodation information, local guide and other related information. Likewise, the client unit 108A can connect with one or more servers to access emergency data 124 comprising tourist information, warnings, alerts, accidents, landslides and other undesired events directly or through the central server 104. The central server 104 may also push all this data to the client units 108 after specific time intervals or on demand. Furthermore, the client unit 108A can connect with one or more servers to access the road and traffic data 122 comprising traffic information from traffic authority servers or through third party applications or through the central server 104.
[00055] In different embodiments, the client unit 108A may be embedded in the vehicle 106A, can be a hand held mobile device, or embedded in a watch worn on wrist by a tourist or can be downloaded as a mobile application in the mobile devices of a tourist.
[00056] In embodiments, the personal data 120 of the tourist includes information that relates to an identity of any individual, for example, name, address, passport details, nationality, phone number, mobile number and other personal details. All the personal data 120 is stored and exchanged in an encrypted form with different devices.
[00057] In embodiments, the government data 118 includes but is not limited to the data obtained from National Portal of India, Ministry Of Statistics And Programme Implementation Dataset, RBI Database Of Indian Economy, Gateway to Indian Earth Observation, India Weather Data, Aadhaar Metadata, Tourism Data, Police & Hospital Data, Digital Maps or some other type of data provided by Open Government Data (OGD) Platform.
[00058] In embodiments, the travel and tourism data 122 includes navigation routing information, number of tourists, mode of transport, tourism attractions, hotels, adventures, local fairs and events and other related data both from private & public domain.
[00059] In embodiments, the emergency data 124 includes medical history of the tourist, landslide data, weather information, accident data, nearby emergency services help access points or some other type of data.
[00060] In embodiments, the road and traffic data 128 includes information related to location wise road’s capacity, road’s current conditions, probable points for accidents and traffic jams, type of vehicle, national highways traffic information, location of railway crossings, locations of bridges, historical data of the bridges, diversions, constructions of roads, public demonstrations and public events on specific roads, military movement or para military force movement.
[00061] In different embodiments, the central server 104 and the vehicle 106A having the client unit 108A can send/receive data based on the requirements of the tourists. Likewise, the vehicle 106B having the client unit 108B and the vehicle 106C having the client unit 108C can send/receive data either directly or through the central server 104 from one or more data sources such as the GPS data 110, the GIS and digital map data 132, the Wi-Fi data 112, the government data 118, the personal data 120, the travel and tourism data 122, the emergency data 124, the weather data 134, the location capacity data 130, the traffic data 128 and some other type of data associated with the tourist. In addition, the client units 108 can also communicate and exchange data between them. For example, the client unit 108A can communicate data and information with the client unit 108B.
[00062] Fig. 2A illustrates different modules of a central server in an embodiment of the present invention. The central server 104 comprises a memory 202 having an operating system 204, one or more applications 208, a tourist safety module 210. The tourist safety module 210 further includes at least a navigation module 224, an emergency module 226, a neighborhood scanning module 228 apart from other modules such as weather module, travel and tourism module, which may be configured to external data sources as shown in Fig.1. In addition, the central server 104 includes at least one processor 212, an input/output module 214 and a communication interface 218. The processor 212, the input/output module 214, and the communication interface 218 are interfaced to a bus 222. The bus 222 is also connected to the memory 202 and provides exchange of data among different modules. Furthermore, the bus 222 can also provide electrical power to different modules.
[00063] In different embodiments, the central server 104 may be a multiprocessor server, multi-threaded server, a rack server, a cloud server or a distributed server having all components and modules including the tourist safety module 210.
[00064] Fig. 2B illustrates different modules of a tourist safety module in an exemplary embodiment of the present invention. The tourist safety module 210 may include additional or fewer modules in different implementations. The tourist safety module 210 include a communication module 230, an information collection and analysis module 232, a vehicle and tourists tracking and identification module 238, a client unit identification 240, a vehicle id and client id safety information 242, a machine learning module 248, a tourist cell information and analysis module 260, a client identification 258, a tourist cell interface 262 and a database 244. In addition, the tourist safety module 210 further includes the navigation module 224, the emergency module 226, the neighborhood scanning module 228.
[00065] The communication module 230 enables exchange of information from the tourist safety module 210 and the client unit 108A and/or the client unit 108B and/or the client unit 108C. The information is exchanged by using module data, Wi-Fi connection or using neighborhood client unit protocol, which is a unique protocol for exchanging information in absence of other means of information exchange. The information received from the client units 108 and other data sources such as but not limited to GPS data, government data, traffic data is analyzed in the information collection and analysis module 232. The analysis of information is based on the information/data requirements of the client units 108. The information collection and analysis module 232 may extract information related to tracking and identification of the vehicle 106A or other vehicles such as 106B. Likewise, the vehicles 106 such as the vehicle 106B or the vehicle 106C can be tracked and identified. After the vehicle client unit identification number has been identified, the tracking and identification of the client unit is processed in the client unit identification 240. The client unit identification 240 then passed the received data to the vehicle ID and Client ID safety information 242. The safety information is processed in the machine learning module 248, which also collected necessary data from the database 244, the vehicle tracking and identification 238, the client identification 240 and other information for different modules.
[00066] The machine learning module 248 includes an analytics database 250, a rule based engine 246, a decision tree module 252 and a recommendation engine 254. The rule based engine 246 includes rules that allow the machine learning module 248 to make decisions based on the information required by the client units 108. For example, in case of emergency, the rule based engine 246 may take a decision to inform the nearest emergency center regarding the emergency; identify the nearest vehicle and alert them for help; or even make a call to the family doctor to attend the emergency over a call if the communication can be established. Likewise, other rules may be coded in the rule based engine 246 for safety and security of the tourist. The rules related to tourist safety, navigation, tourism, overcrowding, emergency and other aspects related to tourism are stored in the analytics database 250. The analytics database 250 may also be accessed by the decision tree module 252 and the recommendation engine 254. The rules based engine 246 is connected to the recommendation engine 254, the decision tree module 252, and analytics database 250. The decision tree module 252 provides decisions to be taken by the tourist safety module 210 and finally passed over to the central server 104v for validation and further processing. The decision tree module 252 passes the decision made by the machine learning module 248 to the recommendation engine 254. The recommendation engine 254 provides recommendations related to safety, navigation, accommodation, crowd diversion, health and other aspects based on one or more variables. In some embodiments, the data related to conditions in vicinity are also collected from different client units 108. For example, the data gathered using crowdsourcing from different locations and stored in at least one database such as 244 or the analytics database 250. The gathered data is analyzed in the rule based engine 246 by applying artificial intelligence algorithms and/or internal rules defined in the the analytics database 250.
[00067] Fig. 3A illustrates a client unit in an exemplary embodiment of the present invention. The client unit 108A is exemplary and other client units such as the client unit 108B or the client unit 108C can have additional number of modules/components in other implementations. In some embodiments, the client units 108 may be similar in configuration and arrangement. In some other embodiments, the client units 108 may be different in configuration and arrangement. For example, the client unit 108A and be different from the client unit 108B in configuration having additional modules than that shown in Fig. 3A.
[00068] The exemplary client unit 108A includes a processor 312, an input/output module 314, a communication module 318, a memory 302, a bus 322, and interface 320 for communication with the central server 104 or other client units 108 such as the client unit 108B or the client unit 108C. The memory 302 may be a ROM or a RAM or any other type of volatile or nonvolatile memory. The memory 302 includes an operating system(s) 304, one or more applications 308, a tourist module 310. The tourist module 310 comprises a client navigation module 312, a client emergency module 314, a client neighbourhood scanning module 318 apart from other modules.
[00069] The client navigation module 312 that provides information related traffic conditions, roadblocks and other navigation issues related to tourist’s navigational route. In some embodiments, the client navigation module 312 collects data related traffic on the fly by connecting with different data sources and accordingly guides the tourist to avoid traffic and other conditions. In some embodiments, the client navigation module 312 collects data from nearby data sources and other client units 108 and passes the data to the central server 104. The central server 104 receives the data from the client unit 108A and calculates the navigation route based on the client requirements. The data can also be collected by one or more client units 108 that are in vicinity or the client units 108 that had passed through that route.
[00070] The client emergency module 314 of the tourist module 310 allows the client unit 108A to gather information related to emergencies in and around the navigation path. If the client unit 108A is in distress, the client emergency module 314 may initiate the emergency procedure to alert the central server 104 of the emergency. In addition, the client emergency module 314 may also alert nearby devices such as vehicles 106B or the vehicle 106C navigating through that road or the nearby road for help. In some embodiments, the client emergency module 314 may receive a distress message from the nearby device such as the client unit 108B and offer help based on the type of emergency. Furthermore, the client unit 108B may receive instructions from the central server 104 for the type of help required by the client unit 108A. Alternatively as directed by the central server 104, the client unit 108C may navigate to the client unit 108A in distress to offer help and support.
[00071] In some embodiments, the client emergency module 314 may utilize a secure connection to other devices such as the client unit 108B or the client unit 108C in vicinity accessible through one or more wireless protocols to send a distress indication to the central server 104 for help.
[00072] The tourist module 310 also includes a client neighbourhood scanning module 318. The novel approach of communicating with the central server 104 in absence of communication signal is solved in this novel method and system of neighborhood scanning.
[00073] In some embodiments, the tourist safety system 100 implements a geo-fence based logical division of a tourism region into logical cells or virtual cells. The process involves dividing a tourism region (for example a state or a tourist circuit consisting of multiple cities) into virtual cells, called tourism cells. Each tourism cell is designed based on many factors including density of points of interests, geography of the area, for example a hilly region or a plain region and some other factors, tourist density during peak and non-peak time, number of stakeholders in that virtual cell and other factors related to optimal tourist management. The adjoining cells are referred to as neighboring tourism cells. The client unit 108A or the client vehicle 106A or the application installed in the tourist mobile phone gets the information about the current tourism cell and the neighboring tourist cells. This allows the tourist to create intelligence about the various points of interest in or near its current location. In one embodiment, the current tourism cell and the neighboring tourism cells are shown on the display of the client units 108 with points of interest marked on each tourism cell.
[00074] As the vehicle of the tourist navigates from the current tourism cell to the neighboring cell, the neighboring cell will become the current tourism cell while the last current tourism cell will become the neighboring tourism cell. This way the tourist module 310 in communication with the central server 104 keeps on updating the client unit 108A or the application installed in the tourist mobile phone with the information and the points of interest associated with each neighboring cell. In embodiments, the tourists are dynamically updated about the various points of interest, tourism products and services, local products, art and craft without searching for it in addition to updating them for lesser known tourist spots in the vicinity of the famous tourist place. The tourist safety and information system 100 in this way keeps updating the tourist with information related to places, shopping, crowd status, points of interest, eating points, offer and discounts and even crowd information at a particular eating spot on the client unit 108A or the client vehicle 106A or the tourist mobile phone. In this way, the tourist may continue navigating the path to the destination and can get timely information in advance.
[00075] This process of scanning and dynamically updating the application in the client unit 108A or the client vehicle 106A or the tourist mobile phone is performed by the client neighbourhood scanning module 318. In another embodiment, the scanning and dynamically updating the application in the client unit 108A may be performed at the central server 104 and passed to the client units 108 at predefined time intervals or instantly.
[00076] The client unit 108A associated with the vehicle 106A accesses the central server 104 to inquire about the navigation route based on the pre-planned tourist destination. In some embodiments, the tourists get information about the place and nearby area using the tourism cell while navigating to the pre-planned tourist destination. The information is provided either on demand or may be pushed depending upon the security level and services subscribed by the tourist through the client unit 108A. In some embodiments, the tourist safety and information system 102 keeps on updating the tourist's mobile device or the client unit 108A with the information as well information related to points of interest of all the neighboring cells. By providing this information, the tourist can get to know various points of interest, tourism products, recreational and other services, local products, art and craft without searching for it.
[00077] In different embodiments, the tourist safety and information system 102 may push the information in the client unit 108A or the mobile device of the tourist based on certain attributes of the tourist. The pushed information may be associated with tourists' interest areas based on the profile of the tourist.
[00078] Fig. 3B illustrates different components of a tourist module in an embodiment of the present invention. In this embodiment, the tourist module 310 of the client unit 108A includes the client navigation module 312, the client emergency module 314 the client neighbourhood scanning module 318, a communication module 330, a vehicle tracking and identification 332, a tourism cell information and analysis module 334, a data collection module 348, a data processing and analysis module 340, a client unit identification module 342, a data processing analysis module 340, a server module 344, and a display module 342 apart from other modulus. A database 352 is provided inside the client unit 108A that holds all the information and data related to identification, neighbourhood data collection, navigation, and other data for analysis.
[00079] The communication module 330 accesses different devices such as the central server 104 and client unit 108A through a tourist cell interface 338 for exchanging information and data. The client navigation module 312 receives navigation data from the central server 104. The vehicle tracking and identification 332 and the client unit identification 342 keeps track of the other client unit 108B or the client unit 108C or other client units 108 during navigation so that each client unit 108 can be uniquely identified. The client emergency module 314 handles different emergencies in coordination with the central server 104. The tourism cell information and analysis module 334 communicates with the central server 104 to provide points of interest and other information while navigating from one tourism cell (current cell) to other tourism cells (neighbourhood cells). The data collection module 348 collects data from different access points including other client units 108 during navigation and passes this data to the central server 104. The data processing and analysis module 340 processes the collected data collected from different access points. In addition, the data processing and analysis module 340 processes the data received from the central server 104 for visual presentation on the display 342. The server module 344 manages data exchange between the client unit 108A and the central server 104.
[00080] The central server 104 provides a unique and novel method and system of storing the tourist identity in order to avoid exposure of the identity of one or more tourists traveling to one or more destinations. The central server 104 may hold the scanned documents, which confirms the real and authentic identity of the tourist. The documents may be encrypted and stored in a digital form as digital signature/digital token. The encrypted documents may be stored in the central server 104 and a digital footprint may be provided to the client unit 108A. The digital footprint may be used to authenticate the tourist’s identity on demand at points of interest such as hotels, monuments, state borders and other places that require physical authentication. In some embodiments, the encrypted documents along with the software application for authentication of the documents in digital form may be stored in the client unit 108A for quick authentication. In some other embodiments, the encrypted documents may be passed from the central server 104 to the local access point computer/server for quick authentication and validation of tourists identification.
[00081] The central server 104 maintains a blockchain of the movement of the tourist. The tourist registers with the central server 104 by providing identity credentials for validation and once the identity credentials are validated the central server 104 provides a digital token for validation of the tourist at a point of interest. The digital token is further utilized for tracking the location of the tourist, when the tourist validates the credentials at the point of interest. This information may be used for tracking the last location of the tourist in case of emergency.
[00082] Referring to Fig. 4, a process of tourist safety and information is illustrated in an embodiment of the present invention. The process 400 starts at 402 and immediately moves to step 404. At step 404, the process 400 collects data from different sources for safety and information of the tourist, which includes but is not limited to data gathered from GPS through satellite, nearby accessible WiFi devices, data received from different government and non-government institutions such as the forest department, the transport department, tourism department, traffic servers, and navigation and map servers and other data sources. The travel data may include navigation data, destination to be visited, accommodation reservations, reservation tickets for point of interests and other types of travel data. Likewise, the emergency details may include evacuation plan, medical history and details, chronic diseases and backup plan for alternate travel arrangement and other similar details. Furthermore, all traffic related data may be directly provided by the traffic police server(s) and diversion, road blocks, and demonstrations are aggregated at the central server 104.
[00083] At step 408, the data collected from different sources by the client units 108 such as the client unit 108A, the client unit108B, and the client client unit 108C is aggregated and provided to the central server 104 for analysis for providing safety and navigation directions to the tourist. In some embodiments, the personal data of tourists can be scanned by the client unit 108A and is encrypted and stored as a digital signature or a digital token. The digital signature or a digital token can be utilized to act as an e-pass for validation at different points requiring identity verification of the tourist.
[00084] At step 410, the central server 104 may analyze the collected data from different sources either directly or through client units 108 such as the client unit 108A, the client unit 108B, and the client unit 108C using artificial intelligence algorithms to provide safety, navigation and other instructions to the tourist(s).
[00085] At step 412, the tourist is provided with safety information and navigation support related to the travel to their destination. The safety information and other relevant information includes reasons for deviation in plan, route changes, emergency instruction and other help related to tourist safety and navigation. The information provided is continuously monitored in real time and new updates are continuously provided to the tourist through client units 108 or directly to the tourist’s client unit 108A, where the tourist safety and information app is installed.
[00086] At step 414, the process 400 terminates after the tourist has reached an intermediate or the final destination. The process 400 continuously monitors the tourist safety through the navigation path until the final destination stored is reached by the tourist.
[00087] Referring to Fig. 5, the process of creation and validation of tourist identity in an embodiment of the present invention. The process 500 starts at 502 and immediately moves to step 504. At step 504, the tourist registers with the tourist safety and information system 100. Alternatively, the tourist can login into the tourist safety and information system 100 for registration. At step 508, the tourist uploads or provides the authentic scanned copies of the identity documents for verification and authentication to create an e-token or digital identity. The tourist safety and information system 100 may validate the identity of the document of the tourist and register the tourist. At step 510, the process 500 may encrypt the identity credentials to provide a digital token/digital signature for verification at different points of interest. After the digital token/digital signature of the identity credentials are created at step 510, the process 500, at step 512 allows the tourist to download the digital token/digital signature in digital valet, which can be any either mobile device or the client unit 108A. Alternatively, the tourist can obtain a smart card with digital signatures, which can be carried personally.
[00088] At step 514, the digital token/digital signature provided by the tourist safety and information system 100 may be validated by the tourist at the points of interest, if required. The digital token/digital signature provides a means to validate the identity of the tourist in a paperless and contactless manner. The digital signature/digital token of the tourist’s identity credential are required for statutory and non-statutory compliance at different points of interest. Such points of interest may include hotels, jungle safari, toll plaza, monuments and other places.
[00089] The process 500 also provides a unique way of tracking the tourist route using digital token/digital signatures. At step 518, when the tourist validates the digital token/digital signature for establishing identity, the process 500 also records the location of the tourist such as (date, time, location and other aspects) to establish the presence of the tourist at a specific point of interest. This is useful for tracking the last visited location of the tourist, if the tourist goes missing or a help is needed by the tourist in case of emergency. Furthermore, additional information such as emergency services, medical help can be provided and arranged to the tourist based on the locational information.The process 500 terminates at step 520.
[00090] Referring to Fig. 6, a process for identifying the points of interest for a tourist through distrubed logical cells is provided in an embodiment of the present invention. The process 600 starts at 602 and immediately moves to step 604. At step 604, the process 600 divides the geographical location of the tourist into multiple logical cells. Each logical cell covers a specific region or a geographical area. The logical cell occupied by the tourist is referred to as the current cell. The logical cells in the neighborhood of the current cell are referred to as adjoining cells.
[00091] At step 608, the process 600 assigns tourists a current cell based on the tourist’s location. At step 610, all the other logical cells adjacent to the current cell of the tourist are assigned as neighborhood cells. At step 610, the client unit 108A scans the current cell for other client units 108 or mobile devices implementing process 600. Furthermore, the process 600 also connects with the neighborhood cells to exchange data and information with them. All the client units 108 and the mobile devices on which the tourist safety and information system 100 has been installed connect with the central server 104 to exchange data and information.
[00092] At step 612, the process 600 scans all the active client units 108 and/or the mobile devices. At step 614, the client units 108 and/or the mobile devices are requested to share the data related to the points of interest in the neighborhood cells. It may be noted that the client units 108 connect to the central server 104 and provide the collected information to be shared with other client units 108. Alternatively, the client units 108 may communicate between each other to exchange information. The information received is analyzed and passed to the tourist’s client unit 108A or the mobile device and also to the central server 104. At step 618, the information received from different sources such as neighborhood client units 108 and/or the mobile devices, government institutions and map providers is analyzed at the central server 104 and passed to the tourist client units 108. Each client unit 108A displays the points of interest on the screen.
[00093] In some embodiments, at least one of the client units 108 may stop at a restaurant not rated or mapped by the central server 104 and provide a very good rating to it. In this scenario, the client unit 108A, which rates this restaurant, may directly provide such information to the tourist client units 108 for exploring the restaurant. This intercommunication among different client units 108 to share information related to points of interest, emergency services, and holding capacity of persons within the restaurant may optimize the journey of other tourists in real time. The process 600 may end at 620.
[00094] Referring to Fig. 7, a process for communication of a client unit with a central server in an embodiment of the present invention. The process starts at 702 and moves to step 704, where the client unit 108A or the tourist module 310 installed as an application in the mobile device of the tourist raises a distress call. In different embodiments, the distress call may be related to different types of emergencies such as but not limited to accidents, landslides, road blocks, festival or diversions or some other type of emergencies. At step 704, the tourist calls for help or raises a distress call. At step 708, the process 700 evaluates if a direct connection of the client unit 108A can be established with the central server 104 from the current location. If a direct connection can be established at step 712, the client unit 108A or mobile device having the tourist module 310 sends a distress call to the central server 104. The central server 104 initiates a process to help and address the distress call of the tourist by providing instruction to the one or more stakeholders to reach out to the tourist.
[00095] If the client unit 108A or the mobile device having the tourist module 310 can’t reach the central server 104 directly, the process 700 moves to step 710. At step 710, the process 700 broadcasts the emergency help data to all the (nearby) vehicles 106 that have the client units 108 or the mobile device having the tourist module 310. On successfully connecting to the other client units 108 or the mobile device having the tourist module 310, the process 700 at step 714 forwards the distress/emergency signal to the central server 104 for help and corrective action. In some embodiments, the central server 104 may alert the government authorities regarding the emergency. If the emergency is of highest order the central server 104 may send emergency signals to different stakeholders for addressing the emergency immediately or prepare for disaster management.
[00096] In some embodiments, depending upon the emergency the client units 108 in vicinity may be directed to help the tourist. In an alternative embodiment, the central server 104 may direct all the vehicles 106 in vicinity to help the tourist under distress and also activate the emergency operating procedure and direct the emergency worker to attend the emergency. The process 700 ends at step 718.
[00097] Referring to Fig. 8, a process for interaction and communication among tourists and tourism stakeholders without joining a group chat using logical cell division is illustrated. The process 800 uses a unique technology of a two way messaging protocol. In preferred embodiments, the group is dynamically modified with new client units 108 entering the neighboring logical cells (that are within the area of influence) while some of the client units 108 leaving the cells (that move out of the area of influence). The client unit 108A and the central server 104 interact based on limited broadcasting technology so that tourist(s) can communicate with each other. Alternatively, the client unit 108A and the central server 104 interact with each other based on the mobile data or GPS network or WiFi network. For example, the tourist can connect with other tourists in the vicinity and ask questions or take guidance from each other.
[00098] In some embodiments, the tourist can broadcast queries and seek guidance from other tourists or communities by broadcasting a message to other vehicles 106 or client units 108 that are within the reach of the current cell. Similarly, the tourist can share local merchandise and can query for a local artisan or can share details of artists/ manufacturers that are close to the current location of the tourist.
[00099] The process 800 starts at 802. At step 804, the process 800 divides the geographical location of the tourism zone or a tourist region into multiple logical cells. Each logical cell covers a specific region or a geographical area. The logical cell occupied by the tourist is referred to as the current cell. The logical cells in the neighborhood of the current cell are referred to as adjoining cells or neighborhood cells.
[000100] At step 808, the process 800 assigns the tourist a current cell based on the current location of the tourist. In addition, each tourist is assigned a unique identification code that is embedded in the client unit 108A in the client unit identification 342. This unique identification code is used to track each tourist based on the location. The unique identification code comprises a client unit identification, a cell identification and a location area code. The central server 104 dynamically updates the database 244 based on the information of the client unit 108A or the mobile device having the tourist module 310 as the tourist moves from one cell (current cell) to another cell (neighboring cell). When the vehicle 106A moves from the current logical cell to the neighboring cell, all parameters are updated accordingly at the client unit 108A and the central server 104.
[000101] At step 810, the central server 104 then prepares a list of other adjacent logical cells and updates all the client units 108 informing the current positions of the client units 108 or mobile devices having the tourist module 310. The process 800 is continuously and dynamically updated at a specified time interval, for example, 1 second or every 10 second.
[000102] At step 812, a client unit 108A or mobile device having the tourist module 310 sends a message to nearby client units 108 or mobile device having tourist module 310 by first connecting with the central server 104. The central server 104 checks the location of the client unit 108A and determines the list of adjacent neighboring cells and the current cell. Subsequently, the central server 104 compares the list of adjacent neighboring cells and the current cell of each of the client units 108 and then updates itself. The central server 104 then updates the client unit 108A from whom the message was received, scans the message for any objectionable content and forwards this message to all client units 108 or the mobile devices having the tourist module 310 in the current cell and the other neighboring logical cells depending upon the area of influence. In embodiments, the area of influence may be based on distance for example radius of 10 kms or to every reachable client units 108 or the mobile devices having the tourist safety and information application. In embodiments, the area of influence may be based on distance, which may vary from 0.5 kms in hilly region to 50 kms in plain region. It may be noted that all client units 108 and the mobile devices in the area of influence associated with the central server 104 are bound by privacy terms and other license agreements to ensure only registered users have access to the broadcasted message.
[000103] At step 814, the client units 108 or the mobile devices having the tourist module 310 may respond to the message. In embodiments, the client unit 108A can exchange messages in a similar way. The central server 104 ensures that the response reaches all the other client units 108 that raised the query even if it has traveled out of the region in order to provide a possible solution to a future query by other tourists.
[000104] At step 818, the tourist’s location may keep changing during travel, the client units 108 or the mobile devices having the tourist safety and information application keep sending its location to the central server 104. The central server 104 will keep on assigning the client units 108 to the new logical cell and keep sending an updated list of adjacent cells. The process 800 terminates at step 820.
[000105] Fig. 9 illustrates a process to monitor a tourist region for tourist safety and overcrowding in an embodiment of the present invention. The process 900 is initiated at step 902 and immediately moves to step 904. At step 904, the process 900 divides a tourist region into multiple logicals cells. In embodiments, the virtual logical cells may be defined of the same size and area. In another embodiment, the virtual logical cells may be of different size and region. The logical cells are virtual mapping of geographical area or geographical region based on the different parameters such as but not limited to population density, concentration of hotels, shopping area, number of important shrines in the vicinity or some other factors. Each logical cell/region may be connected with the central server 104 with a number of transmitting points/towers. The central server 104 may continuously monitor the one or more tourists in each logical cell by maintaining communication with the client units such as the client unit 108A, the client unit 108B, and the client unit 108C.
[000106] At step 908, the process 900 assigns each logical cell one or more parameters such as but not limited to total capacity, rainfall, temperature, snow, road conditions, traffic conditions, waiting time etc. In addition, the process 900 assigns a threshold value to each of the parameters like total capacity, rainfall, temperature, snow, road conditions, traffic conditions, waiting time, population density, tourist spot capacity, tourist accommodation capacity and maximum people density in each logical cell etc. For example, the threshold parameter may be related to the current capacity of a religious place. For a specific religious place the threshold value may be set to 1000 persons. Likewise, the total accommodation for a particular city may be set to a threshold value of 50000. In embodiments, in addition to parameters related to safety and security of the tourist there can be other parameters such as medical institutions, disaster management preparedness and the like. In different embodiments, for each logical cell, the assigned parameters including the ones which are related to safety and security of the tourist can either be the same or different based on their location, tourism conditions etc. In at least one implementation, the threshold value assigned for each parameter can change over time. For example, if the conditions change such as better infrastructure, climate change, these threshold values will also be changed. Alternatively, a sudden appearance of a large crowd in a particular logical cell may result in reorganization of the threshold parameters.
[000107] At step 910, the central server 104 collects data from various sources and is dynamically evaluated in time. The central server 104 then processes the implemented artificial intelligence algorithms and by comparing the current parameters with the corresponding threshold values of that parameter to evaluate if there is any deviation. The comparison of current parameters with the threshold values is performed repeatedly after a fixed time period. For example, the time period may vary from 1 minutes to 60 minutes.
[000108] At step 912, the process 900 determines if one or more parameters are equal to or greater than the parameter threshold value. If so, then the central server 104 sends messages to the stakeholders forewarning them of a specific condition arising out of one or more parameters exceeding the threshold value. In one embodiment, depending upon the severity, the process 900 first sends an information message, followed by a warning and then lastly an alert. Stakeholders can take actions accordingly as per standard operating procedures. The process 900 then analyzes the consequences of the specific threshold value on each of the stakeholder and alerts them depending upon the type of issue, responsibility matrix, affected stakeholders and severity of the problem. In some embodiments, the process 900 may ask the relevant authorities to take specific action for a sudden increase in the threshold value. The process 900 keeps monitoring the situation continuously even after sending the alert message. Furthermore, if the process 900 finds no improvement in the situation, it then sends further alerts as per escalation matrix. In some embodiments, the process 900 may also send information, warnings to stakeholders in adjacent logical cells forewarning them of the situation in order to prepare them in advance and prevent tourists from visiting the troubled logical cell(s).
[000109] At step 914, the process 900 continuously monitors the situation. Once the parameter falls below threshold value, the central server 104 marks in a troubled logical cell as safe and sends an information message of "Normal Condition" to the stakeholders. This helps stakeholders to resume the normal operations in that logical cell.
[000110] At step 918, the process 900 uses the above data, incident response time, infrastructure update, effectiveness of the system etc as data for self learning and feedback to retain itself for accurate prediction. As the learning data increases in volume, the artificial intelligence algorithm becomes highly effective in prediction of the abnormal condition in one or more logical cells. It then applies machine learning algorithms to update the list of parameters, and the threshold value. The process 900 terminates at 920.
[000111] Fig.10 illustrates a process of handling overcrowding by uncovering nearby tourist points of interest in the vicinity in an embodiment of the present invention. The process 1000 addresses the problem of handling the overcrowding especially at shrines or religious places, although the same can be implemented in other places such as historical sites, holy places and other famous destinations. In this embodiment, the overcrowded sites are divided into multiple logical cells with each logical cell defining a particular geographical region and then the process manages the crowds by diverting the tourists to alternative places to manage overcrowding.
[000112] The process 1000 starts at 1002 and immediately moves to step 1004. At step 1004, the process 1000 virtually divides the tourism region or a tourist circuit into multiple logical cells. Each logical cell covers a specific region or a geographical area. At step 1008, the process 1000 registers tourism service providers vendors with the central server 104. These tourism service providers are then categorized based on the logical cells near or around the point of interest, for example, a religious place etc. The geographical location of each tourism service provider and the point of service is recorded in the central server 104. In some embodiments, the tourism service providers may provide tourist services from multiple locations with one or more logical cells. In this case, each location along with its geographical location is stored and mapped with its coordinates in the geographical region and allocated a logical cell.
[000113] In embodiments, different types of tourism service providers such as local, small tourism service providers, big tourism service providers, public tourism service providers, private tourism service providers, individual tourist guides and tourist aggregators can register themselves with the central server 104. Based on the geographical location, the central server 104 may internally assign the logical cell based on the service location. The tourism service providers can also register a nearby tourism site/attraction/story/fact to increase the reach and uncover new places. In addition, these registered tourism sites/attractions/stories/facts help in attracting more tourists apart from helping in crowd management. In embodiment, the tourism service providers in each logical cell are registered with the central server 104. Each tourism service provider is registered for location and various services, products, artifacts offered to the tourists.
[000114] At step 1010, the process 1000 uses the tourism service providers data stored in the central server 104 to create a virtual network of tourism services and tourism service providers for each logical cell. A tourism ecosystem for the entire region consisting of tourism related information, services, products in different categories and location. The tourism ecosystem comprises each logical cell and a list of services and products available in that logical cell of the geographical region.
[000115] At step 1012, the process 1000 uses the virtual network created and stored in the central server 104 to provide information to the tourists of each logical cell within a specified area. At step 1010, the process 1000 combines the virtual network of tourism service providers along with services with the registered tourists visiting a specific logical cell. This information presents a complete knowledge about tourism in that geographical region along with dynamic conditions on the ground. The process 1000 then provides this information to the visiting tourist with different options by using different permutations of the activities/services based tourist profile and preferences. In embodiments, different permutations of services/activities can be categorized based on the region, tourist's choice, traveling preference, on-ground situations etc. In some embodiments, the process 1000 also provides tourists with the option to customize their travel plans using the information.
[000116] In some embodiments, a map of logical cells combining to form a geographical region in the vicinity of the current location of the tourist is provided. In this implementation, the tourist can visualize the current crowding in a particular region and accordingly change or delay their plan to visit the tourist site by first selecting other tourist spots in adjoining logical cells to avoid crowds.
[000117] At step 1014, the process 1000 allows the tourist(s) to book/alter their travel to nearby tourist spots available through the client unit 108A or a mobile device such as mobile phone. Furthermore, the tourist can make bookings using a client unit 108A, which is passed to the tourism service providers on their respective client units 108 or mobile devices such as mobile phones or their computers. The process 1000 provides different options to tourist(s) and reduces overcrowding at famous destinations by diverting the tourists to nearby tourist spots and providing real time crowd information on their client units 108A. Furthemore, the process 1000 also enables locals such as individuals, guides and the other tourism service providers to be a part of mainstream tourism to increase their income. Finally, the process 1000 terminates at step 1020.

CLAIMS:WE CLAIM:
1. A computer implemented method for a tourist safety and providing real time information, updates alerts and forewarnings about the navigation route, locating a tourist during an emergency, real time monitoring of navigational route for one or more destinations, a predictive crowd analysis and for providing assistance and emergency services to a tourist, the computer implement method comprises:
receiving real time data from multiple sources including a client unit;
tracking the real time navigation route of the tourist;
aggregating the data collect from multiple sources at a central server in real time;
characterized by
applying deep learning algorithms at the central server to analyze the current situation based on at least one parameter;
comparing the at least one parameter with threshold value set of that parameter;
raising an alert to the at least one of the stakeholders, when at least one of the parameters is greater than the set threshold value;
locating the current location of the tourist and assessing the current situation, and
using artificial intelligence and machine learning algorithms to provide a corrective action to the tourist in shortest time, and
informing the stakeholders and at least one client unit of the corrective action to cater to the emergencies.

2. The computer implemented method of claim 1, wherein the central server maintains a blockchain related to the movement of the tourist.

3. The computer implemented method of claim 1, wherein the tourist registers with the central server by providing identity credentials for validation of the profile of the tourist, which is utilized for validation of the tourist credentials at one or more point of interest for establishing the identity of the tourist and for tracking the location of the tourist.

4. The computer implemented method of claim 1, wherein the central server is trained to provide prediction of an unforeseen emergency based on one or more parameters.

5. The computer implemented method of claim 1, wherein the central server divides the area of influence into logical cells and manages the movement and exchange of information among the different client units to share information related to nearby points of interest.

6. The exchange of information among different client units of claim 1 is related to at least one of a query, point of interest, emergency or merchandise.

7. The computer implemented method of claim 1, wherein at least one of the deep learning algorithms is related to monitoring the navigation route to the destination and for providing timely information related to predicted events for the safety and of the tourist.

8. The computer implemented method of claim 1, wherein the deep learning algorithms are related to monitoring current carrying capacity, road blockade, weather, safe/unsafe conditions of path & destination.

9. The computer implemented method of claim 1, wherein each client unit acts as a retransmitter of information when at least one of the client units is unable to connect directly to the central server.

10. The computer implemented method of claim 1, wherein the central server implements at least one of the predictive crowd analysis, the emergency services and an alternate route during traffic jams.

11. A tourist safety and information system for providing real time information, updates alerts and forewarnings about the navigation route for tourist safety and for locating a tourist during an emergency, real time monitoring of navigational route for one or more destinations, a predictive crowd analysis, the tourist safety and information system comprises:
a client unit having a unique client identification number and configured to aggregate real time data from multiple sources;
a central server configured to receive the aggregated real time data from at least one client unit and other sources,
wherein the central server is characterized by:
implementing deep learning algorithms to analyze the current situation related to at least one parameter associated with the navigation route to the destination;
comparing the at least one parameter with a set threshold value of that parameter stored in the central server;
raising an alert to the at least one of the stakeholders and the client unit, when at least one of the parameters greater than the set threshold value;
applying predictive analysis using machine learning algorithms to provide a corrective action to the tourist in shortest time for an unforeseen emergency situation, and
informing the stakeholders and one or more client unit of the corrective action to cater to the emergencies.

12. The tourist safety and information system of claim 11, wherein the client unit is a tablet, a navigation device or an application in a mobile phone.

13. The tourist safety and information system of claim 11, wherein at least one parameter comprises number of people at destination, traffic condition on route to the destination, weather conditions, landslides, rains, city capacity and government orders.

14. The tourist safety and information system of claim 11, wherein the destination is a religious place, a holiday destination, a shrine or a dham.

15. The tourist safety and information system of claim 11, wherein the central server comprises aa machine learning module implementing deep learning algorithms initiate steps of:
dividing the geographical region into logical cells based on a predefined criteria;
tracking each client unit in each of the logical cells;
collecting information from each client unit in each of the logical cells, and
analyzing the information collected from each client unit in each logical cell to alert one or more tourists about points of interests and unforeseen situations.

16. The machine learning module of claim 15, wherein the client unit can change the navigation tour based on the unforeseen emergency and make dynamically booking during the travel.

17. The machine learning module of claim 15, wherein the predefined criteria associated with the division of logical cells is based on the geographical landscape.

18. The machine learning module of claim 15, wherein the suggested points of interest are based on the profile of the tourist.

19. The machine learning module of claim 15, wherein the aggregation of data for prediction of unforeseen emergency is based at least one of a information provided by the tourism service providers registered with central server, historical tourist data, data aggregated from visual devices, and registration with local authorities, number of tourists in each logical cell.

20. The machine learning module of claim 15, wherein the central server maintains a list of the number of client units entering and leaving each logical cell.