Electronic stop board system based on mobile terminal

Abstract

The invention provides an electronic station board system based on a mobile terminal, and the system comprises the mobile terminal which is used for interacting with a server, achieving the positioning of a user through a positioning module, and obtaining and displaying the state information of a bus through a user interface; the intelligent bus module is used for monitoring the position information and the running state of the bus and the environment state in the bus in real time and transmitting the position information, the running state and the environment state to the server in real time; the bus stop board module is used for carrying out RFID identification on a bus which is about to arrive at the bus stop board and transmitting an RFID identification result to the server in real time; and the server is used for receiving the real-time data transmitted by the intelligent bus module, the bus stop board module and the mobile terminal, and providing bus arrival time prediction, arrival reminding and route optimization recommendation services for the user through big data analysis. According to the invention, through deep integration of the mobile terminal and the server side, real-time acquisition and dynamic display of the bus information are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of bus stop signs, and in particular to an electronic bus stop sign system based on a mobile terminal. Background Art

[0002] With the popularity of smart phones and the rapid development of smart cities, the demand for intelligent public transportation systems is increasing. Traditional bus electronic signboard systems mainly rely on fixed hardware devices. These systems often have problems such as delayed information updates, lack of personalized services, and high maintenance costs. They cannot meet the real-time information needs of modern users, resulting in a poor travel experience. The existing bus electronic signboard systems have the following major technical and functional problems: delayed information updates. Traditional electronic signboard systems rely on hardware devices in fixed locations, with low update frequency. It is difficult for users to obtain real-time location information and estimated arrival times of buses in a timely manner, resulting in long waiting times and inconvenience in travel. Lack of personalized services. The existing system mainly provides static bus information and cannot provide personalized arrival reminders, route recommendations and other services according to the individual needs of users, which limits the improvement of user experience. High maintenance costs. The maintenance and update of fixed electronic signboard equipment requires frequent manpower and capital investment, especially when the hardware needs to be replaced or upgraded, the cost is even higher.

[0003] Fixed electronic bus stops usually obtain bus location information through GPS and central control systems, and display the information on fixed bus stops. The main problem with this system is that the information is not updated in a timely manner, and the equipment is limited by the physical location and cannot provide mobile and personalized services. In addition, the maintenance and upgrade costs of the hardware are high, and the scalability of the system is poor. Existing mobile terminal applications only provide static bus route information and cannot update in real time or provide dynamic bus arrival information based on the user's location. Such applications have great limitations in user experience, especially when facing complex traffic conditions, and cannot provide timely and accurate travel guidance. Summary of the invention

[0004] In view of this, the object of the present invention is to provide an electronic bus stop sign system based on a mobile terminal, and to provide a mobile electronic bus stop sign system that can update public transportation information in real time, reduce maintenance costs and improve user experience.

[0005] In order to achieve the above-mentioned object of the invention, the present invention provides an electronic station sign system based on a mobile terminal, the system comprising:

[0006] The mobile terminal is used to interact with the server, locate the user using the positioning module, and obtain and display the bus status information through the user interface;

[0007] The intelligent bus module is used to monitor the location information, operating status and environmental status of the bus in real time, and transmit the location information, operating status and environmental status to the server in real time;

[0008] The bus stop module is used to perform RFID recognition on the bus that is about to arrive at the bus stop and transmit the RFID recognition results to the server in real time;

[0009] The server is used to receive real-time data transmitted from the smart bus module, bus stop module and mobile terminal, and provide users with bus predicted arrival time, arrival reminder and optimized route recommendation services through big data analysis.

[0010] Furthermore, the mobile terminal includes:

[0011] A data cache unit, used to cache user historical query information;

[0012] A first communication unit, used for communicating with a server;

[0013] User positioning unit, used to obtain the real-time location of the user;

[0014] The user interface unit is used to obtain the server-side data through the first communication unit and display it on the user information query interface.

[0015] Furthermore, the intelligent bus module includes:

[0016] The first positioning unit is used to obtain the real-time position of the bus;

[0017] Inertial measurement unit, used to monitor the operation status of the bus;

[0018] Environmental monitoring unit, used to monitor the temperature, humidity, carbon dioxide concentration and passenger flow status inside the bus;

[0019] A second communication unit is used to send the real-time processing data of the inertial measurement unit, the first positioning unit and the bus micro-processing unit to the server;

[0020] The bus microprocessor unit is used to read the data from the environmental monitoring unit, determine the current passenger load factor of the bus after passengers are picked up at each stop, and calculate the comfort level of the bus based on the passenger load factor.

[0021] Furthermore, after the passengers are picked up at each stop, the current passenger load factor of the bus is determined, and the comfort level of the bus is calculated based on the passenger load factor, specifically including:

[0022] S11, obtaining the number of people boarding at each bus stop and the real-time number of people on the bus;

[0023] S12, calculating the current passenger load factor of the bus, the calculation formula of the current passenger load factor is:

[0024]

[0025] Among them, S is the current passenger load of the bus, N is the number of people getting on the bus at each bus stop, M is the real-time number of people on the bus, and W is the maximum passenger capacity of the bus;

[0026] S13. The real-time temperature, humidity, carbon dioxide concentration and passenger load factor of the bus are introduced into the comfort evaluation model to obtain an evaluation of the comfort of the bus.

[0027] Furthermore, the bus stop module includes:

[0028] The second positioning unit is used to obtain the real-time location of the bus stop sign;

[0029] RFID reading and writing unit, used to identify the RFID tags of buses within a preset range;

[0030] The third communication unit is used to collect real-time data from the RFID reading and writing unit and the station sign monitoring unit, and send it to the server.

[0031] Furthermore, the server includes:

[0032] A load balancing unit for optimizing the request processing speed of the distributed database, the fourth communication unit and the data analysis unit;

[0033] A distributed database, used to store interaction data of the first communication unit, the second communication unit and the third communication unit;

[0034] The fourth communication unit is used to communicate with the first communication unit, the second communication unit and the third communication unit;

[0035] The data analysis unit is used to respond to user query requests, obtain data from the distributed database, and provide users with bus predicted arrival time, arrival reminders and optimized route recommendation services through big data analysis.

[0036] Furthermore, big data analysis is used to provide users with predicted bus arrival times, including:

[0037] S21, obtaining the real-time location of the user, the real-time location and running status of the bus, and the location of the bus stop and the RFID tag recognition status;

[0038] S22, matching the user's real-time location with the location of the nearest bus stop;

[0039] S23, determining whether the bus is recognized by the bus stop RFID reading and writing unit in step S22, if so, the bus is about to arrive at the station;

[0040] S24. If not, the real-time location, operation status and location of the bus stop are imported into the station prediction model to predict the arrival time of the bus.

[0041] Furthermore, the real-time location, running status and location of the bus stop are imported into the station prediction model to provide a prediction service for the arrival time of the bus, including:

[0042] S31, obtaining the location information of the bus and the corresponding bus route map;

[0043] S32, dividing the location information of the bus into shifts, and marking each location information with a shift;

[0044] S33, matching the location information collected during the operation of each bus with the bus route map in turn, and marking the accumulated travel distance of each location information in the current bus trip;

[0045] S34, extract the historical arrival time of the bus, and for each bus trip, obtain the timestamp and cumulative travel distance of the bus location information, as well as the cumulative distance and operation status along the route of each stop on the bus route map;

[0046] S35. Calculate the arrival time of the bus at each station by linear interpolation, and calculate the remaining time for each piece of location information to arrive at each subsequent station accordingly.

[0047] Furthermore, big data analysis is used to provide users with arrival reminder services, including:

[0048] S41, obtaining the target bus stop sign of the route corresponding to the target bus that the user takes;

[0049] S42, obtaining the real-time location of the user taking the target bus, and feeding back the remaining time from the real-time location of the target bus to the target bus stop to the mobile terminal;

[0050] S43. When the target bus enters the identifiable range of the RFID reading and writing unit of the target bus stop, the user is reminded through the mobile terminal that the bus has arrived at the stop.

[0051] Furthermore, through big data analysis, we provide users with optimized route recommendation services, including:

[0052] S51, according to the current location information and destination information input by the user, matching the starting bus stop sign and the target bus stop sign based on the current location information and the destination information;

[0053] S52, obtaining the starting bus stop sign and the target bus stop sign to obtain all bus routes between them;

[0054] S53, importing the passenger load factor, comfort level and arrival time of all bus routes in step S52 into a route recommendation model to obtain a comprehensive evaluation index;

[0055] S54. Compare and analyze the comprehensive evaluation index with the preset comprehensive evaluation threshold. If the comprehensive evaluation coefficient is greater than or equal to the preset comprehensive evaluation threshold, the bus line is determined to be a pushable line. If the comprehensive evaluation coefficient is less than the preset comprehensive evaluation threshold, the bus line is determined to be a non-pushable line.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The present invention provides an electronic bus stop sign system based on a mobile terminal. The present invention realizes the real-time acquisition and dynamic display of bus information by deeply integrating the mobile terminal with the server. At the same time, the server uses a big data processing framework to analyze the data and provide users with bus predicted arrival time, arrival reminders and optimized route recommendation services; through the sensors and communication equipment of the intelligent bus module, the real-time monitoring and uploading of bus location information, operating status and user flow are realized; through the bus stop sign module, accurate bus station announcements are realized. This system uses the portability of mobile terminals to provide flexible real-time information services, which not only improves the frequency of information updates, but also reduces maintenance costs. At the same time, this system is also highly scalable and can adapt to different cities and user needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0059] Figure 1 A schematic structural diagram of an electronic bus stop system based on a mobile terminal provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0061] Reference Figure 1This embodiment provides an electronic station sign system based on a mobile terminal, the system comprising:

[0062] The mobile terminal is used to interact with the server, use the positioning module to locate the user, and obtain and display the status information of the bus through the user interface. The mobile terminal includes:

[0063] The data cache unit is used to cache user historical query information.

[0064] The first communication unit is used to communicate with the server.

[0065] The user positioning unit is used to obtain the user's real-time location.

[0066] The user interface unit is used to obtain the server-side data through the first communication unit and display it on the user information query interface.

[0067] Understandably, the mobile terminal module supports mainstream iOS and Android operating systems through native or cross-platform mobile application development. The application locates the user's position through GPS and communicates with the server in two directions to obtain and display the real-time location information of the bus. The module can also cache information on common routes to reduce data traffic consumption. In terms of technical implementation, for example: data interaction with the server is carried out by using an efficient RESTful API. The mobile terminal application uses high-precision GPS and the network function of the mobile phone to achieve real-time positioning, and ensures the security of data transmission through an encrypted channel (HTTPS). The interface adopts a responsive design to ensure a good user experience on devices of different sizes.

[0068] The intelligent bus module is used to monitor the location information, operating status and environmental status of the bus in real time, and transmit the location information, operating status and environmental status to the server in real time. The intelligent bus module includes:

[0069] The first positioning unit is used to obtain the real-time position of the bus.

[0070] Inertial measurement unit, used to monitor the operating status of the bus.

[0071] Environmental monitoring unit, used to monitor the temperature, humidity, carbon dioxide concentration and passenger flow status inside the bus.

[0072] The second communication unit is used to send the real-time processing data of the inertial measurement unit, the first positioning unit and the bus micro-processing unit to the server.

[0073] The bus microprocessor unit is used to read the data from the environmental monitoring unit, determine the current passenger load factor of the bus after passengers are picked up at each stop, and calculate the comfort level of the bus based on the passenger load factor.

[0074] It can be understood that the smart bus module includes a high-precision GPS, an inertial measurement unit, an environmental monitoring unit, a second communication unit and a bus micro-processing unit installed on the bus, which are used to monitor the location information and operating status of the bus in real time. The module can automatically send data to the server to ensure the timeliness of the information. The environmental monitoring unit contains multiple sensors, including environmental sensors (temperature, humidity, air quality) and passenger flow sensors. The sensor data is aggregated through the Internet of Things gateway and uploaded to the server for processing. The bus micro-processing unit processes the data transmitted by the environmental monitoring unit in real time through edge computing, reducing the burden of cloud processing, thereby reducing the demand for network bandwidth and energy consumption.

[0075] In some optional implementations of this embodiment, as an example: precise positioning, the smart bus module uses high-precision GPS and IMU (inertial measurement unit) to obtain precise location information, and the data is uploaded to the server through the cellular network (4G / 5G). The microcontroller in the module is responsible for data preprocessing and ensuring the continuity of data in the case of unstable signals. Communication protocol selection, the sensor communicates with the gateway through low-power wide area network (LPWAN) protocols such as LoRa or Zigbee, and the data is preliminarily processed locally through edge computing devices to reduce bandwidth occupancy and data transmission delays. The deployment of sensors can be flexibly adjusted to meet the needs of different buses and routes. Security measures, in order to ensure the security of data transmission, the system uses SSL / TLS encryption technology to prevent data from being stolen or tampered with during transmission. The system also introduces two-factor authentication (2FA) and role-based access control (RBAC) to prevent unauthorized users from accessing sensitive data.

[0076] After the passengers are picked up at each stop, the current passenger load factor of the bus is determined, and the comfort of the bus is calculated based on the passenger load factor, including:

[0077] S11. Obtain the number of people getting on the bus at each bus stop and the real-time number of people on the bus.

[0078] S12, calculating the current passenger load factor of the bus, the calculation formula of the current passenger load factor is:

[0079]

[0080] Among them, S is the current passenger capacity of the bus, N is the number of people getting on the bus at each bus stop, M is the real-time number of people on the bus, and W is the maximum passenger capacity of the bus.

[0081] S13. The real-time temperature, humidity, carbon dioxide concentration and passenger load factor of the bus are introduced into the comfort evaluation model to obtain an evaluation of the comfort of the bus.

[0082] In this embodiment, by calculating the passenger load factor and comfort level, the bus can adjust the departure frequency according to the passenger load factor to avoid overcrowding during peak hours, and reduce unnecessary departures during non-peak hours to save resources. At the same time, the appropriate passenger load factor can ensure that the bus will not be overloaded and ensure the safety of users. The calculation of comfort level provides users with a more comfortable riding environment, which can reduce crowding and discomfort, attract more users to choose public transportation, help reduce the use of private cars, and alleviate traffic congestion and environmental pollution.

[0083] The bus stop module is used to perform RFID recognition on the bus that is about to arrive at the bus stop and transmit the RFID recognition result to the server in real time. The bus stop module includes:

[0084] The second positioning unit is used to obtain the real-time position of the bus stop sign.

[0085] The RFID reading and writing unit is used to identify the RFID tags of buses within a preset range.

[0086] The third communication unit is used to collect real-time data from the RFID reading and writing unit and the station sign monitoring unit, and send it to the server.

[0087] It can be understood that the bus stop module includes GPS positioning, RFID reading and writing units and a third communication unit installed on the bus stop, which are used to monitor the arrival status of the bus in real time. The module can automatically send the RFID tag data identified by the RFID reading and writing unit to the server to ensure the timeliness of the information. Most buses rely on a single GPS positioning, and there are problems such as signal loss and delay, as well as inaccurate bus stop forecasts. This module installs an RFID reading and writing unit on the bus stop to identify the RFID tags of buses within a preset range and report them to the cloud server, which is then pushed to the mobile terminal for bus stop forecasts. The design of this module effectively improves the accuracy and timeliness of bus station announcements, thereby making up for the shortcomings of a single GPS positioning, realizing the accurate announcement of smart bus electronic stops, improving the efficiency of passenger transfers, and improving the service quality of bus travel.

[0088] The server is used to receive real-time data transmitted from the intelligent bus module, bus stop module and mobile terminal, and provide users with bus predicted arrival time, arrival reminder and optimized route recommendation services through big data analysis. The server includes:

[0089] The load balancing unit is used to optimize the request processing speed of the distributed database, the fourth communication unit and the data analysis unit.

[0090] The distributed database is used to store the interaction data of the first communication unit, the second communication unit and the third communication unit.

[0091] The fourth communication unit is used to communicate with the first communication unit, the second communication unit and the third communication unit.

[0092] The data analysis unit is used to respond to user query requests, obtain data from the distributed database, and provide users with bus predicted arrival time, arrival reminders and optimized route recommendation services through big data analysis.

[0093] As can be understood, the server side is the data processing center of the entire system, which is deployed in a cloud computing environment and adopts a highly available and scalable architecture. The server side receives real-time data from the smart bus module, bus stop module and mobile terminal, and provides information such as the predicted arrival time and current operating status of the bus through big data analysis. Technical implementation: Big data analysis, the server side uses a distributed database (MongoDB, Cassandra) to store the historical and real-time data of the bus, and analyzes it through a data processing framework (Apache Spark). Load balancing and caching, the load balancer (Nginx) and the cache system (Redis) are used to optimize the processing speed of requests and ensure the stability of the system under high concurrency. Anomaly detection, the system integrates anomaly detection algorithms (Isolation Forest, LOF) in the data processing process to detect anomalies such as GPS signal loss and sensor failure. Once an anomaly is detected, the system triggers an alarm and automatically attempts to reacquire data or enable backup sensor data to ensure the continuity and reliability of the system.

[0094] Provide users with predicted bus arrival times through big data analysis, including:

[0095] S21. Obtain the real-time location of the user, the real-time location and running status of the bus, and the location of the bus stop and the RFID tag recognition status.

[0096] S22: Match the user's real-time location with the location of the nearest bus stop.

[0097] S23, determine whether the bus is recognized by the bus stop RFID reading and writing unit in step S22, if so, the bus is about to arrive at the station.

[0098] S24. If not, the real-time location, operation status and location of the bus stop are imported into the station prediction model to predict the arrival time of the bus.

[0099] In this embodiment, active RFID technology and GPS satellite positioning technology are used, RFID reading and writing units are set on bus stops, and high-precision GPS is set on buses. Vehicle positioning data is collected and reported to the cloud server, and more accurate positioning data is obtained comprehensively, and pushed to the smart bus electronic stop for bus station forecasting. This method can effectively improve the accuracy and timeliness of vehicle entry station announcements, thereby making up for the shortcomings of single GPS positioning, realizing accurate station announcements on bus electronic stop signs, improving the efficiency of passenger transfers, and improving the service quality of public transportation.

[0100] Import the real-time location, operation status and location of the bus stop into the station prediction model to predict the arrival time of the bus, including:

[0101] S31. Obtain the location information of the bus and the corresponding bus route map. A bus GPS record contains the following fields: vehicle number, route number, up and down direction, timestamp, longitude, latitude, instantaneous speed, instantaneous direction. The geographic information data of the bus route consists of a group of location nodes containing longitude and latitude information. These nodes sequentially identify the intersections, turning points and stations that the bus route passes through. The road section formed by adjacent location nodes can be regarded as a straight line section.

[0102] S32, divide the location information of the bus into shifts, and mark each location information as a shift. For example, the location information of the bus is divided into shifts: the distance and change trend between the GPS records of the bus with the same vehicle number and the first and last stops of the bus line are used to screen out the first and last GPS sampling points of each bus shift and their corresponding sampling times, and the first and last GPS sampling times of each bus shift are used to define the operating time range of the bus shift. According to the time range, the GPS records belonging to the shift are screened out from the GPS data of the same vehicle number and the shift number is marked.

[0103] S33. The location information collected during the operation of each bus is matched with the bus route map in turn, and the accumulated travel distance of each location information in the current shift is marked. The GPS data collected during the operation of each bus shift is matched with the route in turn to obtain more accurate location data, and the accumulated travel distance of each GPS record in the current shift is marked, and the data is used to visually identify the travel progress of the bus shift.

[0104] S34, extract the historical arrival time of the bus, and for each bus trip, obtain the timestamp and cumulative travel distance of the bus location information, as well as the cumulative distance and operating status along the route of each stop on the bus route map.

[0105] S35. Calculate the arrival time of the bus at each station by linear interpolation, and calculate the remaining time for each location information to arrive at each subsequent station. GPS records contain timestamps and cumulative travel distances. According to the cumulative distances of bus stations along the bus routes, the arrival time of each bus at each station is calculated by linear interpolation. For each GPS record, the arrival time of the bus station that has not arrived is subtracted from the timestamp of the GPS record to obtain the remaining time for the GPS record to arrive at the next several stations.

[0106] Providing users with arrival reminder services through big data analysis, including:

[0107] S41, obtaining the target bus stop sign of the route corresponding to the target bus that the user takes.

[0108] S42: Obtain the real-time location of the user taking the target bus, and feed back the remaining time from the real-time location of the target bus to the target bus stop to the mobile terminal.

[0109] S43. When the target bus enters the identifiable range of the RFID reading and writing unit of the target bus stop, the user is reminded through the mobile terminal that the bus has arrived at the stop.

[0110] In this embodiment, the arrival reminder service can reduce the problem of passengers missing their stops due to drowsiness or noise in the car, and can also avoid physical injuries to passengers due to crowded getting off. Users can obtain the arrival time of the bus in a timely manner, ensuring that they will not miss their stops while riding the bus, which improves the convenience and reliability of travel.

[0111] Provide users with optimized route recommendation services through big data analysis, including:

[0112] S51, according to the current location information and destination information input by the user, matching the starting bus stop and the target bus stop based on the current location information and the destination information. Receive the current location information and the destination information input by the user, and obtain the starting bus stop closest to the current location and the target bus stop closest to the destination based on the current location information and the destination information input by the user.

[0113] S52, obtaining the starting bus stop and the target bus stop to obtain all the bus routes between them. All bus routes between the starting bus stop and the target bus stop are obtained to obtain all bus routes between the user's current location and the destination, thereby providing the user with the best travel route recommendation based on the selected bus routes.

[0114] S53, importing the passenger load factor, comfort level and arrival time of all bus routes in step S52 into the route recommendation model to obtain a comprehensive evaluation index. In this embodiment, in order to ensure the maximum satisfaction of different users in taking the bus, the selected bus routes are comprehensively evaluated to obtain a comprehensive evaluation index, so as to accurately grasp the degree of matching between supply and demand of the bus system.

[0115] S54, compare and analyze the comprehensive evaluation index with the preset comprehensive evaluation threshold. If the comprehensive evaluation coefficient is greater than or equal to the preset comprehensive evaluation threshold, the bus line is determined to be a pushable line. If the comprehensive evaluation coefficient is less than the preset comprehensive evaluation threshold, the bus line is determined to be a non-pushable line. By setting the threshold, the operation status of the bus line can be quickly classified, reducing the time and cost of manual analysis.

[0116] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An electronic bus stop sign system based on a mobile terminal, characterized in that: The system comprises: The mobile terminal is used to interact with the server, locate the user using the positioning module, and obtain and display the bus status information through the user interface; The intelligent bus module is used to monitor the location information, operating status and environmental status of the bus in real time, and transmit the location information, operating status and environmental status to the server in real time; The bus stop module is used to perform RFID recognition on the bus that is about to arrive at the bus stop and transmit the RFID recognition results to the server in real time; The server is used to receive real-time data transmitted from the smart bus module, bus stop module and mobile terminal, and provide users with bus predicted arrival time, arrival reminder and optimized route recommendation services through big data analysis.

2. The electronic bus stop sign system based on a mobile terminal according to claim 1 is characterized in that: The mobile terminal comprises: A data cache unit, used to cache user historical query information; A first communication unit, used for communicating with a server; User positioning unit, used to obtain the real-time location of the user; The user interface unit is used to obtain the server-side data through the first communication unit and display it on the user information query interface.

3. The electronic bus stop sign system based on a mobile terminal according to claim 1 is characterized in that: The intelligent public transportation module comprises: The first positioning unit is used to obtain the real-time position of the bus; Inertial measurement unit, used to monitor the operation status of the bus; Environmental monitoring unit, used to monitor the temperature, humidity, carbon dioxide concentration and passenger flow status inside the bus; A second communication unit is used to send the real-time processing data of the inertial measurement unit, the first positioning unit and the bus micro-processing unit to the server; The bus microprocessor unit is used to read the data from the environmental monitoring unit, determine the current passenger load factor of the bus after passengers are picked up at each stop, and calculate the comfort level of the bus based on the passenger load factor.

4. The electronic bus stop sign system based on a mobile terminal according to claim 3 is characterized in that: After the passengers are picked up at each stop, the current passenger load factor of the bus is determined, and the comfort of the bus is calculated based on the passenger load factor, including: S11, obtaining the number of people boarding at each bus stop and the real-time number of people on the bus; S12, calculating the current passenger load factor of the bus, the calculation formula of the current passenger load factor is: Among them, S is the current passenger load of the bus, N is the number of people getting on the bus at each bus stop, M is the real-time number of people on the bus, and W is the maximum passenger capacity of the bus; S13. The real-time temperature, humidity, carbon dioxide concentration and passenger load factor of the bus are introduced into the comfort evaluation model to obtain an evaluation of the comfort of the bus.

5. The electronic bus stop sign system based on a mobile terminal according to claim 1 is characterized in that: The bus stop module includes: The second positioning unit is used to obtain the real-time location of the bus stop sign; RFID reading and writing unit, used to identify the RFID tags of buses within a preset range; The third communication unit is used to collect real-time data from the RFID reading and writing unit and the station sign monitoring unit, and send it to the server.

6. The electronic bus stop sign system based on a mobile terminal according to claim 1 is characterized in that: The server comprises: A load balancing unit for optimizing the request processing speed of the distributed database, the fourth communication unit and the data analysis unit; A distributed database, used to store interaction data of the first communication unit, the second communication unit and the third communication unit; The fourth communication unit is used to communicate with the first communication unit, the second communication unit and the third communication unit; The data analysis unit is used to respond to user query requests, obtain data from the distributed database, and provide users with bus predicted arrival time, arrival reminders and optimized route recommendation services through big data analysis.

7. The electronic bus stop sign system based on a mobile terminal according to claim 6 is characterized in that: Provide users with predicted bus arrival times through big data analysis, including: S21, obtaining the real-time location of the user, the real-time location and running status of the bus, and the location of the bus stop and the RFID tag recognition status; S22, matching the user's real-time location with the location of the nearest bus stop; S23, determining whether the bus is recognized by the bus stop RFID reading and writing unit in step S22, if so, the bus is about to arrive at the station; S24. If not, the real-time location, operation status and location of the bus stop are imported into the station prediction model to predict the arrival time of the bus.

8. The electronic bus stop sign system based on a mobile terminal according to claim 7 is characterized in that: Import the real-time location, operation status and location of the bus stop into the station prediction model to predict the arrival time of the bus, including: S31, obtaining the location information of the bus and the corresponding bus route map; S32, dividing the location information of the bus into shifts, and marking each location information with a shift; S33, matching the location information collected during the operation of each bus with the bus route map in turn, and marking the accumulated travel distance of each location information in the current bus trip; S34, extract the historical arrival time of the bus, and for each bus trip, obtain the timestamp and cumulative travel distance of the bus location information, as well as the cumulative distance and operation status along the route of each stop on the bus route map; S35. Calculate the arrival time of the bus at each station by linear interpolation, and calculate the remaining time for each piece of location information to arrive at each subsequent station accordingly.

9. The electronic bus stop sign system based on a mobile terminal according to claim 8 is characterized in that: Providing users with arrival reminder services through big data analysis, including: S41, obtaining the target bus stop sign of the route corresponding to the target bus that the user takes; S42, obtaining the real-time location of the user taking the target bus, and feeding back the remaining time from the real-time location of the target bus to the target bus stop to the mobile terminal; S43. When the target bus enters the identifiable range of the RFID reading and writing unit of the target bus stop, the user is reminded through the mobile terminal that the bus has arrived at the stop.

10. The electronic bus stop sign system based on a mobile terminal according to claim 8, characterized in that: Provide users with optimized route recommendation services through big data analysis, including: S51, according to the current location information and destination information input by the user, matching the starting bus stop sign and the target bus stop sign based on the current location information and the destination information; S52, obtaining the starting bus stop sign and the target bus stop sign to obtain all bus routes between them; S53, importing the passenger load factor, comfort level and arrival time of all bus routes in step S52 into a route recommendation model to obtain a comprehensive evaluation index; S54. Compare and analyze the comprehensive evaluation index with the preset comprehensive evaluation threshold. If the comprehensive evaluation coefficient is greater than or equal to the preset comprehensive evaluation threshold, the bus line is determined to be a pushable line. If the comprehensive evaluation coefficient is less than the preset comprehensive evaluation threshold, the bus line is determined to be a non-pushable line.

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