Description:Field of the Invention
This invention relates to Intelligent Passenger Counting System with Remote Data Storage using Edge-computing
Background of the Invention
Manual counting of passengers in public vehicles especially during peak hours are prone to errors and is time-consuming leading to inaccurate passenger count. The intelligent passenger counting system automates and facilitates the counting process, minimizing human error and providing more accurate information in an efficient manner. The count data can be accessed by the billing machine or any other connected device of ticket issuer for checking any error in issued tickets count. Additionally, the system enables the remote storage of passenger count data in a server or cloud-based system, providing transportation authorities and operators with valuable insights into passenger flow patterns and peak hours. This real-time information facilitates analysis for improved resource allocation, planning, and decision-making, such as deploying additional vehicles as deploying additional vehicles or adjusting routes to meet passenger demand to meet passenger demand.
CN111881843A The invention provides a taxi passenger carrying number counting method based on face detection, which comprises the steps of obtaining a picture in a taxi through a camera arranged in the taxi; judging the face through a trained low-level feature pyramid network, and then extracting frame marks from the judged face; filtering extraction frames outside the range according to the face distribution range in a service scene in a common taxi to obtain a preliminary passenger model condition; processing the picture through an HSV color model, calculating the size of a pixel area, assisting in judging the passenger distribution condition of a rear seat, and finally obtaining a prior passenger model; and introducing the prior passenger model into a Bayesian model, and finally obtaining the specific passenger number in the vehicle according to the corresponding actual passenger model. According to the method, the face detection technology, the HSV color model and the Bayesian model are combined, so that more accurate passenger carrying number of the taxi is obtained, and the defect that the face detection technology is not accurate enough is overcome.
Research Gap: The model presented in this patent can be used in variety public vehicle while the other one is specifically designed for taxis.
The model presented in this patent is suitable to monitor a large number of passengers accurately.
The model presented in this patent uses Edge computing and is able to send the information to a remote server for further analysis and storage.
US4009389A There is provided apparatus for determining the number of passengers entering and/or leaving a collective passenger vehicle. The apparatus comprises means for projecting a pair of light-beams of invisible light across the passageway of said passengers and means for receiving said light-beams. Detecting means which operate in conjunction with the light-beam receiving means are adapted to detect the energized or unenergized state of the receiving means and in response thereto to feed information to a data registering or recording means, said information being indicative of the number of passengers passing through the light-beams.
Research Gap: The method presented in this patent uses computer vision algorithms on camera footage placed at strategic positions to count number of passengers (the other one uses invisible light-beam of invisible light at the entry/exit doors).
The model presented in this patent uses Edge computing and is able to send the information to a remote server for further analysis and storage.
None of the prior art indicate above either alone or in combination with one another disclose what the present invention has disclosed. Present invention is Intelligent Passenger Counting System with Remote Data Storage using Edge-computing
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
In this, strategically positioned cameras are installed inside public vehicles to capture video footage, essential information about passenger presence and movements. This device is placed to ensure a wide field of view and clean line of sight and a stable power source is provided to run their processing components, communication modules, and other hardware components. These edge devices are equipped with processing capabilities and advanced computer vision algorithms like faster R-CNN or YOLO to analyze the data in real-time at the edge. By utilizing these algorithms, passengers entering and exiting the vehicle can be detected and tracked, enabling accurate real-time passenger counting. Conducting the counting at the edge provides immediate updates on passenger numbers without relying on a remote server or cloud-based processing. Once the passenger counting is performed, the edge device establishes a Wi-Fi connection within the public vehicle allowing personnel, such as the ticket issuer or conductor, to connect their devices such as smartphones, tablets, or portable billing machines to the network to then access information about the number of passengers on board in real-time. The edge device also initiates the transmission of the passenger count data to a remote server or cloud-based system over the internet connection. The remote server or cloud-based system serves as a central repository for the passenger count data from multiple vehicles and allows transportation authorities or operators to access and analyze the data from various vehicles remotely which can include examining passenger flow patterns, identifying peak hours, generating reports, or conducting predictive analytics to optimize resource allocation and improve operational efficiency. The frequency of data transmission can be tailored to meet system requirements, occurring periodically or continuously.
The Figure 1 represents the working of the proposed model which starts by installing an edge-based system on the vehicle at a strategic position to ensure good lighting and wide view for camera. The camera captures the video footage and applies pre-trained computer vision model to calculated the count of passengers present in the vehicle on real-time. After the passenger count is determined the edge-based system sends the data to the ticket issuer connected device so that the ticket issuer can check for any errors made. Also, the edge-based system sends the count data to a cloud server to store and analyse it to obtain useful information from it. The cloud server is able to send timely alert messages to the ticket issuer in case of errors.
The Fig.2 is a block diagram to presents the working of the edge-based node and its connected components. The edge device i.e., camera (22) is responsible for capturing real time video of passengers and providing with necessary details to the processing unit (20). The processing unit apply computer vision model (23) to the acquired video footage to compute the numbers of passengers in the vehicle at a given point and provide with real-time result. The extracted information then is sent to the ticket issuer to compare the number of persons with issued ticket for error prevention through Wi-Fi (24). The information of the passenger count data is transmitted to a remote server or cloud-based system over the internet connection for further analysis. All the components of the device are given the power supply to operate (21).
The Fig.3 is a block diagram to presents the overall working process of the model. The edge-based node (20) computes the number of passengers in the vehicle by processing the video footage captured by the camera by applying certain computer vision algorithms. The edge device sends the computed result to the authorized personnel (10) through Wi-Fi and also send it to the cloud server or remote server (30) through internet. The cloud server then stores the data into the database (40) and that data is used to analysis and informed decision making (50) for optimal resource allocation like deploying additional vehicles or adjusting routes to meet passenger demand. The cloud will timely check and send alert message to the ticket issuer in case of errors is found in the number of tickets issued or the number of passengers.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
Figure 1 System Architecture
Figure 2 System Architecture
Figure 3 System Architecture
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
These and other advantages of the present subject matter would be described in greater detail with reference to the following figures. It should be noted that the description merely illustrates the principles of the present subject matter. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described herein, embody the principles of the present subject matter and are included within its scope.
In this, strategically positioned cameras are installed inside public vehicles to capture video footage, essential information about passenger presence and movements. This device is placed to ensure a wide field of view and clean line of sight and a stable power source is provided to run their processing components, communication modules, and other hardware components. These edge devices are equipped with processing capabilities and advanced computer vision algorithms like faster R-CNN or YOLO to analyze the data in real-time at the edge. By utilizing these algorithms, passengers entering and exiting the vehicle can be detected and tracked, enabling accurate real-time passenger counting. Conducting the counting at the edge provides immediate updates on passenger numbers without relying on a remote server or cloud-based processing. Once the passenger counting is performed, the edge device establishes a Wi-Fi connection within the public vehicle allowing personnel, such as the ticket issuer or conductor, to connect their devices such as smartphones, tablets, or portable billing machines to the network to then access information about the number of passengers on board in real-time. The edge device also initiates the transmission of the passenger count data to a remote server or cloud-based system over the internet connection. The remote server or cloud-based system serves as a central repository for the passenger count data from multiple vehicles and allows transportation authorities or operators to access and analyze the data from various vehicles remotely which can include examining passenger flow patterns, identifying peak hours, generating reports, or conducting predictive analytics to optimize resource allocation and improve operational efficiency. The frequency of data transmission can be tailored to meet system requirements, occurring periodically or continuously.
The Figure 1 represents the working of the proposed model which starts by installing an edge-based system on the vehicle at a strategic position to ensure good lighting and wide view for camera. The camera captures the video footage and applies pre-trained computer vision model to calculated the count of passengers present in the vehicle on real-time. After the passenger count is determined the edge-based system sends the data to the ticket issuer connected device so that the ticket issuer can check for any errors made. Also, the edge-based system sends the count data to a cloud server to store and analyse it to obtain useful information from it. The cloud server is able to send timely alert messages to the ticket issuer in case of errors.
The Fig.2 is a block diagram to presents the working of the edge-based node and its connected components. The edge device i.e., camera (22) is responsible for capturing real time video of passengers and providing with necessary details to the processing unit (20). The processing unit apply computer vision model (23) to the acquired video footage to compute the numbers of passengers in the vehicle at a given point and provide with real-time result. The extracted information then is sent to the ticket issuer to compare the number of persons with issued ticket for error prevention through Wi-Fi (24). The information of the passenger count data is transmitted to a remote server or cloud-based system over the internet connection for further analysis. All the components of the device are given the power supply to operate (21).
The Fig.3 is a block diagram to presents the overall working process of the model. The edge-based node (20) computes the number of passengers in the vehicle by processing the video footage captured by the camera by applying certain computer vision algorithms. The edge device sends the computed result to the authorized personnel (10) through Wi-Fi and also send it to the cloud server or remote server (30) through internet. The cloud server then stores the data into the database (40) and that data is used to analysis and informed decision making (50) for optimal resource allocation like deploying additional vehicles or adjusting routes to meet passenger demand. The cloud will timely check and send alert message to the ticket issuer in case of errors is found in the number of tickets issued or the number of passengers.
ADVANTAGES OF THE INVENTION:
1. This model maintains the integrity of ticket issuing process by monitoring it.
2. The model uses real-time data for optimal resource allocation and decision-making.
3. This model allows efficient data processing at the edge for faster computation.
4. This model improves passenger experience by better planning of seating arrangements.
, Claims:We Claim:
1. An Intelligent Passenger Counting System with Remote Data Storage using Edge-computing comprises Processing Unit (20), Power Supply (21), Camera (22), Wi-Fi (24), Couper Vision Model (43), Edge based node (10), Authorized Personnel (Ticket Issuer) (20), Cloud Server (30), Analysis and Informed Decision Making (30); and Database (40).
2. The system as claimed in claim 1, wherein the camera captures the video footage and applies pre-trained computer vision model to calculated the count of passengers present in the vehicle on real-time.
3. The system as claimed in claim 1, wherein aafter the passenger count is determined the edge-based system sends the data to the ticket issuer connected device so that the ticket issuer checks for any errors made; and the edge-based system sends the count data to a cloud server to store and analyse it to obtain useful information from it; wherein the cloud server is able to send timely alert messages to the ticket issuer in case of errors.
4. The system as claimed in claim 1, wherein camera (22) is responsible for capturing real time video of passengers and providing with necessary details to the processing unit (20).
5. The system as claimed in claim 1, wherein the processing unit apply computer vision model (23) to the acquired video footage to compute the numbers of passengers in the vehicle at a given point and provide with real-time result.
6. The system as claimed in claim 1, wherein the extracted information then is sent to the ticket issuer to compare the number of persons with issued ticket for error prevention through Wi-Fi (24); and the information of the passenger count data is transmitted to a remote server or cloud-based system over the internet connection for further analysis; and all the components of the device are given the power supply to operate (21).
7. The system as claimed in claim 1, wherein the edge-based node (20) computes the number of passengers in the vehicle by processing the video footage captured by the camera by applying certain computer vision algorithms.
8. The system as claimed in claim 1, wherein the edge device sends the computed result to the authorized personnel (10) through Wi-Fi and also send it to the cloud server or remote server (30) through internet.
9. The system as claimed in claim 1, wherein the cloud server then stores the data into the database (40) and that data is used to analysis and informed decision making (50) for optimal resource allocation like deploying additional vehicles or adjusting routes to meet passenger demand; and the cloud timely checks and sends alert message to the ticket issuer in case of errors is found in the number of tickets issued or the number of passengers.