A mobile terminal-based electronic station board system

Abstract

The application provides a kind of electronic bus stop system based on mobile terminal, the system includes: mobile terminal, for interacting with server, the positioning of user is realized using positioning module, the state information of bus is obtained and demonstrated through user interface;Intelligent bus module, for real-time monitoring the position information, running state of bus and the environmental state in bus, and the position information, running state and environmental state are transmitted to server in real time;Bus stop module, for carrying out RFID identification to bus arriving at bus stop soon, and RFID identification result is transmitted to server in real time;Server, for receiving real-time data transmitted from intelligent bus module, bus stop module and mobile terminal, providing bus predicted arrival time, station arrival reminder and optimized route recommendation service for user through big data analysis.The application realizes real-time acquisition and dynamic display of bus information by deeply integrating mobile terminal and server.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bus stop boards, and in particular to an electronic bus stop board system based on a mobile terminal. BACKGROUND

[0002] With the popularity of smartphones and the rapid development of smart cities, the demand for intelligent public transportation systems is increasing. Traditional electronic bus stop board systems mainly rely on fixed hardware devices, which often have problems such as information update lag, lack of personalized services, high maintenance costs, and cannot meet the real-time information needs of modern users, affecting the travel experience. The existing electronic bus stop board system has the following main problems in technology and function: information update lag, traditional electronic bus stop board system relies on fixed position hardware devices, low update frequency, users are difficult to obtain real-time position information and estimated arrival time of buses, leading to long waiting time and travel inconvenience. Lack of personalized services, the existing system mainly provides static bus information, which cannot provide personalized arrival reminders, route recommendations and other services according to individual user needs, limiting the improvement of user experience. High maintenance cost, the maintenance and update of fixed electronic bus stop devices require frequent human and financial investment, especially when hardware needs to be replaced or upgraded, the cost is even higher.

[0003] Fixed electronic bus stop boards usually obtain bus position information through GPS and central control system, and display the information on fixed bus stop boards. The main problem of this system is that the information is not updated in time, and the device is limited by the physical location, which cannot provide mobile and personalized services. In addition, the maintenance and upgrade cost of hardware is high, and the expansibility of the system is poor. The existing mobile terminal application only provides static bus route information, which cannot be updated in real time or provide dynamic bus arrival information according to the user's location. Such application has great limitations in user experience, especially in the face of complex traffic conditions, it cannot provide timely and accurate travel guidance. SUMMARY

[0004] In view of this, the purpose of the present application is to provide an electronic bus stop board system based on a mobile terminal, which can update bus information in real time, reduce maintenance cost and improve user experience.

[0005] To achieve the above-mentioned purpose of the application, the present application provides an electronic bus stop board system based on a mobile terminal, which comprises:

[0006] a mobile terminal for interacting with a server, using a positioning module to realize the positioning of users, and obtaining and displaying the state information of buses through a user interface;

[0007] The intelligent bus module is used for monitoring position information, running state and environment state in the bus in real time, and transmitting the position information, running state and environment state to the server in real time.

[0008] The bus stop module is used for performing RFID identification on the bus arriving at the bus stop, and transmitting the RFID identification result to the server in real time.

[0009] The server is used for receiving real-time data transmitted from the intelligent bus module, the bus stop module and the mobile terminal, and providing bus predicted arrival time, arrival reminding and optimized route recommendation services for users through big data analysis.

[0010] Further, the mobile terminal comprises:

[0011] The data caching unit is used for caching user historical query information.

[0012] The first communication unit is used for communicating with the server.

[0013] The user positioning unit is used for acquiring real-time position of the user.

[0014] The user interface unit is used for acquiring server-side data through the first communication unit, and displaying the data on the user query information interface.

[0015] Further, the intelligent bus module comprises:

[0016] The first positioning unit is used for acquiring real-time position of the bus.

[0017] The inertial measurement unit is used for monitoring running state of the bus.

[0018] The environment monitoring unit is used for monitoring temperature, humidity, carbon dioxide concentration and passenger flow state in the bus.

[0019] The second communication unit is used for sending 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 micro-processing unit is used for reading data of the environment monitoring unit, determining current passenger loading rate of the bus after passenger boarding at each station ends, and calculating comfort degree of the bus according to the passenger loading rate.

[0021] Further, the current passenger loading rate of the bus is determined after passenger boarding at each station ends, and the comfort degree of the bus is calculated according to the passenger loading rate, and the method specifically comprises:

[0022] S11, acquiring the number of passengers boarding at each bus station and real-time number of passengers on the bus.

[0023] S12, calculate the current passenger rate of the bus, the calculation formula of the current passenger rate is:

[0024]

[0025] Wherein, S is the current passenger rate of the bus, N is the number of passengers at each bus stop, M is the real-time number of passengers 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 rate of the bus are introduced into the comfort evaluation model to obtain the evaluation of the comfort of the bus.

[0027] Further, the bus stop board module comprises:

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

[0029] The RFID read-write unit is used to identify the RFID tags of the buses within the preset range;

[0030] The third communication unit is used to collect the real-time data of the RFID read-write unit and the stop board monitoring unit and send them to the server.

[0031] Further, the server comprises:

[0032] 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;

[0033] The distributed database is used to store the interactive data of the first communication unit, the second communication unit and the third communication unit;

[0034] The fourth communication unit is used for communication and exchange 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 in the distributed database, and provide bus predicted arrival time, station arrival reminder and optimized route recommendation services for users through big data analysis.

[0036] Further, the bus predicted arrival time is provided for users through big data analysis, which specifically comprises:

[0037] S21, obtaining the real-time position of the user, the real-time position and running state of the bus and the position and RFID tag identification state of the bus stop board;

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

[0039] S23, judging whether the bus is identified by the bus stop RFID read-write unit of step S22, if yes, the bus will arrive at the station;

[0040] S24, if not, the real-time position, running state of the bus and the position of the bus stop are introduced into the station prediction model to predict the arrival time of the bus.

[0041] Further, the real-time position, running state of the bus and the position of the bus stop are introduced into the station prediction model to predict the arrival time of the bus, specifically including:

[0042] S31, obtaining the position information of the bus and the corresponding bus line map;

[0043] S32, classifying the position information of the bus by shift, and marking each position information by shift;

[0044] S33, for each shift, the position information collected during the running of the bus is matched with the bus line map in turn, and the cumulative travel distance of each position information under the current shift is marked;

[0045] S34, extracting the historical arrival time of the bus, for each shift bus, obtaining the timestamp of the bus position information and the cumulative travel distance, and the cumulative distance along the line and the running state of each station on the bus line map;

[0046] S35, calculating the time of the bus to arrive at each station by linear interpolation, and calculating the remaining time of each position information to arrive at the subsequent stations.

[0047] Further, through big data analysis, the arrival reminding service is provided for the user, specifically including:

[0048] S41, obtaining the target bus stop corresponding to the target bus line of the user;

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

[0050] S43, when the target bus enters the RFID read-write unit recognizable range of the target bus stop, reminding the user through the mobile terminal that the bus has arrived at the station.

[0051] Further, through big data analysis, the optimized route recommendation service is provided for the user, specifically including:

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

[0053] S52, obtain all bus lines between the starting bus stop and the target bus stop;

[0054] S53, introduce the passenger carrying rate, the comfort degree and the time to reach the starting station of all bus lines in step S52 into a line recommendation model to obtain a comprehensive evaluation index;

[0055] S54, compare and analyze the comprehensive evaluation index with a preset comprehensive evaluation threshold value, if the comprehensive evaluation index is greater than or equal to the preset comprehensive evaluation threshold value, the bus line is determined as a pushable line, if the comprehensive evaluation index is less than the preset comprehensive evaluation threshold value, the bus line is determined as a non-pushable line.

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

[0057] The electronic bus stop system based on a mobile terminal provided by the present application realizes real-time acquisition and dynamic display of bus information by deeply integrating the mobile terminal with the server end, meanwhile, the server analyzes data by using a big data processing framework to provide bus prediction arrival time, arrival reminding and optimized line recommendation services for users; the bus position information, running state and user flow are monitored and uploaded in real time through the sensors and communication equipment of the intelligent bus module; the accurate bus stop is realized through the bus stop module. The system provides flexible real-time information services by using the portability of the mobile terminal, not only improves the information update frequency, but also reduces the maintenance cost, meanwhile, the system has high expansibility and can adapt to different cities and user demands. BRIEF DESCRIPTION OF DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows, obviously, the drawings in the following description are only embodiments of the present application, and those skilled in the art can obtain other drawings according to the provided drawings without any creative labor.

[0059] Figure 1 The structure schematic diagram of the electronic bus stop system based on a mobile terminal provided by the present application is shown. DETAILED DESCRIPTION

[0060] The present application will be further described in detail below in combination with the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application. In addition, it should be noted that, in order to facilitate the description, only the parts related to the present application are shown in the drawings, but not all the structures.

[0061] REFERENCE Figure 1The embodiment provides a mobile terminal-based electronic bus stop system, which comprises:

[0062] A mobile terminal is used for interacting with a server, positioning a user by using a positioning module, and acquiring and displaying state information of a bus by using a user interface.

[0063] A data caching unit is used for caching historical query information of the user.

[0064] A first communication unit is used for communicating with the server.

[0065] A user positioning unit is used for acquiring a real-time position of the user.

[0066] A user interface unit is used for acquiring server-side data by using the first communication unit and displaying the data on a user query information interface.

[0067] It can be understood that the mobile terminal module supports mainstream iOS and Android operating systems by native or cross-platform mobile application development, the application positions the position of the user by using GPS and communicates with the server side in a bidirectional mode to acquire and display real-time position information of the bus, the module can also cache information of a commonly used route to reduce consumption of data flow. In terms of technical implementation, for example, efficient RESTful API is used to interact with the server side. The mobile terminal application realizes real-time positioning by using high-precision GPS and network functions of the mobile phone, and ensures the safety of data transmission by using an encrypted channel (HTTPS). The interface adopts responsive design to ensure good user experience on devices of different sizes.

[0068] An intelligent bus module is used for monitoring real-time position information, a running state and an environmental state in a bus of the bus, and transmitting the real-time position information, the running state and the environmental state to the server. The intelligent bus module comprises:

[0069] A first positioning unit is used for acquiring a real-time position of the bus.

[0070] An inertial measurement unit is used for monitoring the running state of the bus.

[0071] An environmental monitoring unit is used for monitoring temperature, humidity, carbon dioxide concentration and a people flow state in the bus.

[0072] A second communication unit is used for sending 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 micro-processing unit is used for reading the data of the environment monitoring unit, determining the current passenger carrying rate of the bus after the passengers get off at each station, and calculating the comfort degree of the bus according to the passenger carrying rate.

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

[0075] In some optional implementations of the embodiment, as an example: precise positioning, the intelligent bus module uses high-precision GPS and IMU (inertial measurement unit) to obtain accurate position information, and data is uploaded to the server through a cellular network (4G / 5G). The microcontroller in the module is responsible for data preprocessing and ensures data continuity in unstable signal conditions. Communication protocol selection, sensors communicate with gateways through low-power wide-area network (LPWAN) protocols such as LoRa or Zigbee, and data is preliminarily processed locally through edge computing devices to reduce bandwidth occupancy and data transmission delay. The deployment of sensors can be flexibly adjusted to adapt to different bus and line requirements. Security measures, in order to ensure the security of data transmission, the system adopts 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 get off at each station, the current passenger carrying rate of the bus is determined, and the comfort degree of the bus is calculated according to the passenger carrying rate, which specifically includes:

[0077] S11, the number of passengers getting on each bus station and the real-time number of passengers on the bus are obtained.

[0078] S12, the current passenger carrying rate of the bus is calculated, and the calculation formula of the current passenger carrying rate is:

[0079]

[0080] Wherein, S is the current passenger carrying rate of the bus, N is the number of passengers getting on each bus station, M is the real-time number of passengers on the bus, and W is the maximum passenger carrying capacity of the bus.

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

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

[0083] The bus stop module is used for RFID identification of the bus arriving at the bus stop and real-time transmission of the RFID identification result to the server. The bus stop module comprises:

[0084] The second positioning unit is used for acquiring the real-time position of the bus stop.

[0085] The RFID read-write unit is used for identifying the RFID tags of the buses within the preset range.

[0086] The third communication unit is used for collecting real-time data of the RFID read-write unit and the stop monitoring unit and sending the real-time data to the server.

[0087] It can be understood that the bus stop module comprises a GPS positioning device, an RFID read-write unit and a third communication unit installed on the bus stop, which are used for real-time monitoring of the arrival state of the bus. The module can automatically send the RFID read-write unit to identify the RFID tag data to the server to ensure the timeliness of the information. Most buses rely on single GPS positioning, which has problems such as signal loss, delay and inaccurate bus prediction station. The module identifies the RFID tags of the buses within the preset range through the RFID read-write unit installed on the bus stop and reports to the cloud server, and then pushes to the mobile terminal for bus prediction station. The design of the module effectively improves the accuracy and timeliness of the bus station reporting, thereby making up for the shortcomings of single GPS positioning, realizing precise station reporting of intelligent bus electronic station board, improving passenger transfer efficiency and improving the service quality of public transportation.

[0088] The server is used for receiving real-time data transmitted from the intelligent bus module, the bus stop module and the mobile terminal, and providing bus prediction arrival time, station arrival reminder and optimized route recommendation services for users through big data analysis. The server comprises:

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

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

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

[0092] A data analysis unit is used to obtain data in the distributed database in response to a user query request, and provide a bus predicted arrival time, a station arrival reminder and an optimized route recommendation service for the user through big data analysis.

[0093] It can be understood that the server side is the data processing center of the entire system, deployed in a cloud computing environment, and adopts a high-availability and high-extensibility architecture. The server side receives real-time data from the intelligent bus module, the bus stop module and the mobile terminal, and provides the predicted arrival time of the bus, the current running state and other information through big data analysis. In terms of 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 uses a data processing framework (Apache Spark) for analysis. Load balancing and caching, a load balancer (Nginx) and a caching system (Redis) are used to optimize the processing speed of requests and ensure the stability of the system under high concurrency. Abnormality detection, the system integrates an abnormality detection algorithm (Isolation Forest, LOF) during data processing, which is used to detect abnormal situations such as GPS signal loss and sensor failure. Once an abnormality is detected, the system will trigger an alarm and automatically attempt to reacquire data or enable backup sensor data to ensure the continuity and reliability of the system.

[0094] The predicted arrival time of the bus is provided for the user through big data analysis, which specifically includes:

[0095] S21, obtaining the real-time position of the user, the real-time position and running state of the bus and the position and RFID tag identification state of the bus stop.

[0096] S22, matching the real-time position of the user with the position of the nearest bus stop.

[0097] S23, judging whether the bus is identified by the bus stop RFID read-write unit of step S22, if yes, the bus is about to arrive at the station.

[0098] S24, if not, importing the real-time position, running state of the bus and the position of the bus stop into a 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, an RFID read-write unit is arranged at a bus stop, a high-precision GPS is arranged on a bus, vehicle positioning data is collected and reported to a cloud server, more accurate positioning data is obtained comprehensively, and the bus prediction station is pushed to an intelligent bus electronic station board. The method can effectively improve the accuracy and timeliness of the vehicle station reporting, thereby making up for the deficiency of single GPS positioning, realizing accurate station reporting of the bus electronic station board, improving the passenger transfer connection efficiency, and improving the service quality of bus travel.

[0100] The real-time position of the bus, the running state and the position of the bus stop are introduced into the station prediction model to predict the arrival time of the bus, and the service specifically includes:

[0101] S31, obtain the position information of the bus and the corresponding bus line map. A bus GPS record contains the following fields: vehicle number, line number, up-down direction, timestamp, longitude, latitude, instantaneous speed, and instantaneous direction. The geographic information data of the bus line is composed of a group of position nodes containing longitude and latitude information. These nodes sequentially identify the intersections, turning points and stations passed by the bus line. The road section formed between adjacent position nodes can be regarded as a straight line section.

[0102] S32, divide the position information of the bus into shifts, and mark each position information with a shift. As an example, the first and last GPS sampling points of each shift bus and the corresponding sampling time are screened out by using the distance between the bus GPS record with the same vehicle number and the bus line first and last station and the change trend, the operation time range of each shift bus is determined by using the first and last GPS sampling time of each shift bus, and the GPS record belonging to the shift is screened out from the GPS data with the same vehicle number according to the time range and marked with a shift number.

[0103] S33, for the position information collected in the operation of each shift bus, sequentially match with the bus line map, and mark the cumulative driving distance of each position information under the current shift. The GPS data collected in the operation of each shift bus is sequentially matched with the line to obtain more accurate position data, and the cumulative driving distance of each GPS record under the current shift is marked, and the driving process of the bus shift is intuitively identified by using the data.

[0104] S34, extract the historical arrival time of the bus, for each shift bus, obtain the timestamp and cumulative driving distance of the bus position information, and the cumulative distance and running state of each station on the bus line map.

[0105] S35, the time of the bus to reach each station is calculated by linear interpolation, and the corresponding calculation of the remaining time of each piece of location information to reach the subsequent stations. The GPS record contains a timestamp and a cumulative travel distance. According to the cumulative distance of the bus stop along the bus line, the arrival time of each bus at each station is calculated by linear interpolation. For each GPS record, the arrival time of the bus stop that has not arrived is subtracted from the timestamp of the GPS record to obtain the remaining time of the GPS record to reach the subsequent stations.

[0106] The to-station reminding service is provided for the user through big data analysis, specifically including:

[0107] S41, the target bus stop corresponding to the line of the target bus taken by the user is obtained.

[0108] S42, the real-time position of the target bus taken by the user is obtained, and the remaining time from the real-time position of the target bus to the target bus stop is fed back to the mobile terminal.

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

[0110] In this embodiment, the to-station reminding service can reduce the problem of passengers over-station caused by drowsiness and noise in the carriage for users who are not familiar with the route or are easily distracted, and can also avoid physical injury to passengers caused by crowded off. The user can obtain the arrival time of the bus in time, ensure that the user will not over-station during the process of taking the bus, and improve the convenience and reliability of travel.

[0111] The optimized route recommendation service is provided for the user through big data analysis, specifically including:

[0112] S51, according to the current position information and destination information input by the user, the starting bus stop and the target bus stop are matched based on the current position information and destination information. The current position information and destination information input by the user are received, and the nearest starting bus stop to the current position and the nearest target bus stop to the destination are obtained according to the current position information and destination information input by the user.

[0113] S52, all bus lines between the starting bus stop and the target bus stop are obtained. All bus lines between the starting bus stop and the target bus stop are obtained to obtain all bus lines between the current position of the user and the destination, so as to provide the best travel route recommendation for the user based on the filtered bus lines.

[0114] S53, import the passenger rate, comfort and time to reach the starting station of all bus lines in step S52 into the line 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 lines are comprehensively evaluated to obtain the comprehensive evaluation index, so as to accurately grasp the supply-demand matching degree of the bus system.

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

[0116] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An electronic bus stop sign system based on a mobile terminal, characterized in that, The system includes: The mobile terminal is used to interact with the server, uses the positioning module to locate the user, and obtains and displays the bus's status information through the user interface. The intelligent bus module is used to monitor the location information, operating status and environmental conditions inside the bus in real time, and transmit the location information, operating status and environmental conditions to the server in real time. The bus stop module is used to perform RFID identification on buses that are about to arrive at the bus stop and transmit the RFID identification results to the server in real time. The server is used to receive real-time data transmitted from the intelligent bus module, bus stop module and mobile terminal, and to provide users with bus arrival time prediction, arrival reminder and optimized route recommendation services through big data analysis; We use big data analytics to provide users with predicted bus arrival times, specifically including: S21. Obtain the user's real-time location, the bus's real-time location and operating status, as well as the location of the bus stop sign and the RFID tag identification status; S22. Match the user's real-time location with the location of the nearest bus stop; S23. Determine whether the bus has been identified by the RFID reader / writer unit of the bus stop sign in step S22. If so, the bus is about to arrive at the station. S24. Otherwise, import the real-time location, operating status, and bus stop location of the bus into the arrival prediction model to predict the arrival time of the bus. The real-time location, operational status, and bus stop location of buses are imported into the arrival prediction model to provide arrival time prediction services for buses. Specifically, this includes: S31. Obtain the location information of the bus and the corresponding bus route map; S32. Divide the location information of buses into shifts and mark each location information with a shift. S33. The location information collected during each bus trip is matched with the bus route map in sequence, and the cumulative travel distance of each location information in the current trip is marked. S34. Extract the historical arrival time of the bus. For each bus trip, obtain the timestamp of the bus location information and the cumulative travel distance, as well as the cumulative distance along the route and the operating status 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 location information to reach the subsequent stations accordingly. We provide arrival reminder services to users through big data analysis, specifically including: S41. Obtain the target bus stop sign for the bus route corresponding to the user's target bus; S42. Obtain the user's real-time location when boarding the target bus, and send the remaining time from the real-time location of the target bus to the target bus stop to the mobile device. S43. When the target bus enters the RFID reader / writer range of the target bus stop sign, the user is notified via mobile device that the bus has arrived at the stop. We provide users with optimized route recommendations through big data analysis, specifically including: S51. Based on the current location information and destination information input by the user, match the starting bus stop and the target bus stop. S52. Obtain all bus routes between the starting bus stop and the target bus stop; S53. Import the passenger load factor, comfort level and arrival time at the starting station of all bus routes in step S52 into the 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 route is determined to be a route that can be promoted. If the comprehensive evaluation coefficient is less than the preset comprehensive evaluation threshold, the bus route is determined to be a route that cannot be promoted.

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

3. The electronic bus stop system based on a mobile terminal according to claim 1, characterized in that, The intelligent bus module includes: The first positioning unit is used to obtain the real-time location of the bus; An inertial measurement unit is used to monitor the operating status of the bus. The environmental monitoring unit is used to monitor the temperature, humidity, carbon dioxide concentration, and passenger flow inside the bus. The second communication unit is used to send the real-time processed data of the inertial measurement unit, the first positioning unit, and the bus microprocessor unit to the server; The bus microprocessor unit is used to read data from the environmental monitoring unit, determine the current passenger load factor of the bus after passengers have boarded at each stop, and calculate the comfort level of the bus based on the passenger load factor.

4. The electronic bus stop system based on a mobile terminal according to claim 3, characterized in that, After passengers have finished boarding at each stop, the current passenger load factor of the bus is determined. Based on the passenger load factor, the comfort level of the bus is calculated, specifically including: S11. Obtain the number of passengers boarding at each bus stop and the real-time number of passengers on the bus; S12. Calculate the current passenger load factor of the bus. The formula for calculating the current passenger load factor is: Where S is the current passenger load factor of the bus, N is the number of passengers boarding at each bus stop, M is the real-time number of passengers on the bus, and W is the maximum passenger capacity of the bus. S13. Import the real-time temperature, humidity, carbon dioxide concentration and passenger load of the bus into the comfort evaluation model to obtain an evaluation of the bus's comfort level.

5. The electronic bus stop system based on a mobile terminal according to claim 1, characterized in that, The bus stop sign module includes: The second positioning unit is used to obtain the real-time location of the bus stop sign; The RFID reader / writer unit is used to identify RFID tags on 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 bus stop monitoring unit, and send it to the server.

6. The electronic bus stop system based on a mobile terminal according to claim 1, characterized in that, The server includes: 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. A distributed database is used to store the interaction data between the first communication unit, the second communication unit, and the third communication unit. The fourth communication unit is used to communicate with the first, second, and third communication units. The data analysis unit is used to respond to user query requests, retrieve data from the distributed database, and provide users with bus arrival time predictions, arrival reminders, and optimized route recommendations through big data analysis.

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