Riding state monitoring method, system and device

Abstract

The invention belongs to the technical field of riding state monitoring, and discloses a riding state monitoring method, system and device. The method comprises the following steps that whether a rider wears a helmet or not is detected, if not, an alarm is triggered, and unlocking can be conducted until the rider wears the helmet; if the rider still does not correctly wear the helmet after the alarm is triggered, the rider is prompted to forcibly lock the bicycle after preset time. Physiological parameters and alcohol concentration data of a rider are obtained; acquiring a real-time position of the rider and a traffic rule of the position, and recommending an optimal path for the rider according to the position information of the rider; the riding speed of the rider in the riding process is obtained, and whether the rider is overspeed or not in the riding process is judged according to the riding speed of the rider and the traffic rule of the position where the rider is located; and the riding state of the rider is analyzed based on the physiological parameters of the rider, the alcohol concentration data, the riding speed, the violation condition and the helmet wearing condition. The problem that the state of a rider cannot be comprehensively monitored is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of riding state monitoring, and specifically relates to a riding state monitoring method, system and device. Background Art

[0002] The riding status of cyclists is related to their safety and health, so it is necessary to protect people's life safety while riding in a more humane, intelligent and precise way. At the same time, the riding status of cyclists also provides a basis for managers to formulate more reasonable and effective riding plans. With the continuous development of the urban sharing economy, shared electric vehicles have emerged, and their riding speed is higher, so it is necessary to monitor the physiological parameters of cyclists in real time, and at the same time, it is necessary to take more stringent identification measures to ensure the safety of cyclists.

[0003] After searching, the patent document with publication number CN110329405A discloses a cycling management system, which monitors the rider's heart rate, body temperature, sweat volume and other physiological data, and analyzes the cycling posture. However, it is still not comprehensive enough and cannot fully monitor the rider's status. Summary of the invention

[0004] The purpose of the present invention is to provide a riding status monitoring method, system and device, which solves the problem that the prior art cannot fully monitor the status of the rider.

[0005] The present invention is achieved through the following technical solutions:

[0006] A riding status monitoring method includes the following steps:

[0007] Detect whether the rider is wearing a helmet; specifically:

[0008] If the rider is not wearing a helmet before riding, an alarm will be triggered and the bike can only be unlocked after the rider puts on a helmet. If the rider still does not wear a helmet correctly after the alarm is triggered, the rider will be prompted to lock the bike after a preset time.

[0009] If the rider does not wear a helmet correctly during riding, the alarm will continue to sound;

[0010] Obtain the physiological parameters of the rider;

[0011] Detect alcohol concentration data through the rider's breath;

[0012] Obtain the real-time location of the cyclist and the traffic rules at the location, and recommend the best route for the cyclist based on the cyclist's location information;

[0013] Obtain the riding speed of the cyclist during riding, and determine whether the cyclist is speeding according to the riding speed of the cyclist and the traffic rules at the location;

[0014] The rider's riding status is analyzed based on the rider's physiological parameters, alcohol concentration data, riding speed, whether there is any violation and whether the rider is wearing a helmet.

[0015] Further, the physiological parameters include blood pressure data and heart rate data.

[0016] Furthermore, when the rider encounters an emergency, he or she can use the SOS button to alert the police.

[0017] Furthermore, the alcohol concentration data was detected using the LM393\ZYMQ-3 sensor;

[0018] The vehicle speed is collected using the MPU6050 six-axis gyroscope sensor.

[0019] Furthermore, the real-time location of the rider is obtained using a GPS module.

[0020] Furthermore, an infrared sensor is used to detect whether the rider wears the helmet correctly, and the infrared sensor adopts the HC-SR501 human infrared sensing module.

[0021] Furthermore, the riding status is divided into four levels: excellent, good, average and poor, providing status analysis and inquiry for riders.

[0022] The present invention also discloses a riding status monitoring system, comprising:

[0023] Helmet detection module, used to detect whether the rider is wearing a helmet;

[0024] If the rider is not wearing a helmet before riding, an alarm will be triggered and the bike can only be unlocked after the rider puts on a helmet. If the rider still does not wear a helmet correctly after the alarm is triggered, the rider will be prompted to lock the bike after a preset time.

[0025] If the rider does not wear a helmet correctly during riding, the alarm will continue to sound;

[0026] The vehicle locking module is used to trigger unlocking after the helmet detection module detects that the rider is wearing a helmet; or to forcefully trigger vehicle locking after a preset time has passed;

[0027] A physiological parameter detection module is used to obtain the physiological parameters of the rider;

[0028] Alcohol detection module, used to detect alcohol concentration data through the rider's breath;

[0029] GPS module, used to obtain the real-time location of the rider and the traffic rules at the location;

[0030] The vehicle speed sensor module is used to obtain the speed of the rider during riding;

[0031] A data processing module is used to recommend an optimal route for a cyclist based on the cyclist's location information;

[0032] Used to determine whether the rider is speeding according to the rider's speed and the traffic rules at the location;

[0033] Used to analyze the rider's riding status based on the rider's physiological parameters, alcohol concentration data, riding speed, whether there is any violation, and whether the rider is wearing a helmet;

[0034] The display module is respectively connected with the physiological parameter detection module, the GPS module, the vehicle speed sensor module, the cycling route planning module, the cycling violation analysis module, and the cycling status analysis module, and is used to display the output information of each module.

[0035] The present invention also discloses a riding status monitoring device, comprising a wearing terminal and a cloud platform; the wearing terminal is equipped with a helmet detection module, a vehicle locking module, a physiological parameter detection module, an alcohol detection module, a GPS module, a vehicle speed sensor module, a communication module and a main controller;

[0036] The helmet detection module is used to detect whether the rider is wearing a helmet. If the rider is not wearing a helmet before riding, an alarm is triggered and the bike cannot be unlocked until the rider wears a helmet. If the rider still does not wear a helmet correctly after the alarm is triggered, the rider is prompted to lock the bike after a preset time.

[0037] If the rider does not wear a helmet correctly during riding, the alarm will continue to sound;

[0038] The vehicle locking module is used to trigger unlocking after the helmet detection module detects that the rider is wearing a helmet; or to forcefully trigger vehicle locking after a preset time has passed;

[0039] A physiological parameter detection module is used to obtain the physiological parameters of the rider;

[0040] Alcohol detection module, used to detect alcohol concentration data through the rider's breath;

[0041] GPS module, used to obtain the real-time location of the rider and the traffic rules at the location;

[0042] The vehicle speed sensor module is used to obtain the speed of the rider during riding;

[0043] The main controller is connected to the helmet detection module, the physiological parameter detection module, the alcohol detection module, the GPS module, the vehicle speed sensor module and the communication module, and is used to gather information from the helmet detection module, the physiological parameter detection module, the alcohol detection module, the GPS module and the vehicle speed sensor module, and transmit the gathered information to the cloud platform;

[0044] The wearable terminal communicates with the cloud platform through the communication module;

[0045] The cloud platform is equipped with a cycling route planning module, a cycling violation analysis module, and a cycling status analysis module;

[0046] Cycling route planning module, used to recommend the best route for cyclists based on their location information;

[0047] The cycling violation analysis module is used to determine whether the rider has exceeded the speed limit during riding based on the rider’s speed and the traffic rules at the location;

[0048] The riding status analysis module is used to analyze the riding status of the rider based on the rider's physiological parameters, alcohol concentration data, riding speed, whether there is any violation and whether the rider is wearing a helmet.

[0049] Furthermore, the wearable terminal is also connected to the APP through the communication module, and the rider can view relevant data during riding on the cloud platform interface or using the software APP.

[0050] Compared with the prior art, the present invention has the following beneficial technical effects:

[0051] The purpose of the present invention is to provide a riding status monitoring method and system, which are mainly progressive in the following aspects:

[0052] Alcohol concentration detection for riders. The alcohol detection module is used to test the rider’s alcohol concentration and determine whether the rider is riding under the influence of alcohol. If the alcohol concentration exceeds the limit, an alarm message will be issued to restrict the user from riding, thereby ensuring the rider’s safety.

[0053] Whether the rider is wearing a helmet correctly. If the rider is not wearing a helmet, an alarm will be triggered until the rider wears a helmet; if the rider still does not wear a helmet correctly after the alarm is triggered, the rider will be prompted to lock the bike after a preset time; if the rider does not wear a helmet correctly during riding, the system will continue to issue a voice alarm;

[0054] Optimal route planning and recommendation for cyclists. According to the cyclist's starting address and destination address, three route planning modes are provided, namely the shortest route, the route with the least traffic lights, and the route with the most green shades;

[0055] Analysis and judgment of the rider's status during riding. Based on the rider's physiological parameters (blood pressure and heart rate), riding speed, whether there is a violation, alcohol concentration, and whether the helmet is worn correctly, the rider's riding status is given using the rider status analysis model, which corresponds to four levels: excellent, good, average, and poor, providing status analysis and query for riders;

[0056] Determine whether the cyclist has violated traffic regulations. Obtain the cyclist's location information through GPS positioning, determine whether the cyclist has violated traffic regulations based on the traffic regulations of the section of the road where the cyclist is located, and provide improvement suggestions for the cyclist's illegal behavior;

[0057] In summary, the present invention can comprehensively monitor the status of the rider and ensure the safety of the rider.

[0058] Furthermore, when a rider encounters an emergency, he or she can use the SOS one-button alarm. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 The architecture diagram of the rider status monitoring system designed for the present invention;

[0060] Figure 2 It is a block diagram of the rider status monitoring system;

[0061] Figure 3 This is the cloud platform architecture diagram;

[0062] Figure 4 This is the block diagram of the cyclist state analysis model. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present invention more clear, the following is further described in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the embodiments described are only part of the embodiments of the present invention, not all embodiments.

[0064] The components described and shown in the drawings and embodiments of the present invention may be arranged and designed in various configurations. Therefore, the detailed description of the embodiments of the present invention provided in the following drawings is not intended to limit the scope of the claimed invention, but merely represents a selected embodiment of the present invention. Based on the drawings and embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0065] The features and performances of the present invention are further described in detail below in conjunction with the embodiments.

[0066] Example 1

[0067] The present invention discloses a method for monitoring a rider's state, comprising the following steps:

[0068] Check whether the rider is wearing a helmet correctly:

[0069] If the rider is not wearing a helmet before riding, an alarm will be triggered and the bike can only be unlocked after the rider puts on a helmet. If the rider still does not wear a helmet correctly after the alarm is triggered, the rider will be prompted to lock the bike after a preset time.

[0070] If the rider does not wear a helmet correctly during riding, the alarm will continue to sound;

[0071] Obtain the physiological parameters of the rider;

[0072] Obtain the alcohol concentration data of the cyclist;

[0073] Obtain the real-time location of the cyclist and the traffic rules at the location, and recommend the best route for the cyclist based on the cyclist's location information;

[0074] Obtain the speed of the cyclist during riding, and determine whether the cyclist is speeding according to the cyclist's speed and the traffic rules at the location;

[0075] The rider's riding status is analyzed using the rider's status analysis model based on the rider's physiological parameters (heart rate and blood pressure), riding speed, whether there is a violation, alcohol concentration, and whether the helmet is worn correctly.

[0076] The present invention specifically detects the rider's heart rate, blood pressure, alcohol concentration, location information, riding speed, and whether the rider wears a helmet correctly, comprehensively determines whether the rider is safe, and collects statistics on the riding status to issue early warnings and reminders for dangerous situations.

[0077] Specifically, physiological parameters include heart rate and blood pressure. Data fusion of heart rate and blood pressure parameters is performed, and abnormal results will trigger the cloud platform alarm function.

[0078] Specifically, the alcohol concentration of the rider is detected. When the alcohol concentration exceeds the threshold, the voice alarm function will be triggered and the cloud platform will send an alarm message to remind the rider.

[0079] Example 2

[0080] Correspondingly, the present invention also discloses a riding status monitoring system, comprising:

[0081] Helmet detection module, used to detect whether the rider is wearing a helmet;

[0082] If the rider is not wearing a helmet before riding, an alarm will be triggered and the bike can only be unlocked after the rider puts on a helmet. If the rider still does not wear a helmet correctly after the alarm is triggered, the rider will be prompted to lock the bike after a preset time.

[0083] If the rider does not wear a helmet correctly during riding, the alarm will continue to sound;

[0084] The vehicle locking module is used to trigger unlocking after the helmet detection module detects that the rider is wearing a helmet; or to forcefully trigger vehicle locking after a preset time has passed;

[0085] A physiological parameter detection module is used to obtain the physiological parameters of the rider;

[0086] Alcohol detection module, used to obtain the cyclist's alcohol concentration data;

[0087] GPS module, used to obtain the real-time location of the rider and the traffic rules at the location;

[0088] The vehicle speed sensor module is used to obtain the speed of the rider during riding;

[0089] A data processing module is used to recommend an optimal route for a cyclist based on the cyclist's location information;

[0090] Used to determine whether the rider is speeding according to the rider's speed and the traffic rules at the location;

[0091] Used to analyze the rider's riding status based on the rider's physiological parameters, alcohol concentration data, riding speed, whether there is any violation and whether the rider is wearing a helmet;

[0092] The display module is respectively connected with the physiological parameter detection module, the GPS module, the vehicle speed sensor module, the cycling route planning module, the cycling violation analysis module, and the cycling status analysis module, and is used to display the output information of each module.

[0093] Specifically, the GPS module is used to detect the real-time location of the rider and upload the data to the cloud platform to provide location support for optimal route planning. At the same time, the cloud platform determines whether the rider has any traffic violations based on the traffic rules at the rider's location.

[0094] Specifically, a speed sensor is used to obtain the vehicle speed during riding, and whether the rider is speeding during riding is determined according to the rider's position, so as to ensure the rider's safety.

[0095] Specifically, an infrared sensor module is used to detect whether the rider is wearing a helmet. If it is detected that the rider is not wearing a helmet, a voice alarm function will be triggered until the rider wears a helmet.

[0096] The data processing module is used to process the alcohol concentration, the rider's physical parameters, and the GPS location information. The optimal route is recommended for the rider based on the rider's location information. The rider's speed and the traffic rules at the location are used to determine whether the rider is speeding during riding. The rider's riding status is analyzed based on the rider's physiological parameters, alcohol concentration data, riding speed, whether there is a violation, and whether the rider is wearing a helmet.

[0097] Heart rate and blood pressure sensors are used to detect the rider's physical condition, and the rider's current state is determined by heart rate and blood pressure. The MAX30102 heart rate and pulse sensor is used, which has a high anti-interference ability and can maintain normal operation under various interferences. The MSP20 blood pressure sensor uses MEMS technology to design and manufacture piezoresistive pressure sensing molds. It consists of a spring diaphragm and four piezoresistors integrated in the diaphragm to establish a Wheatstone bridge structure. When the elastic diaphragm is under pressure, the Wheatstone bridge will generate a linear voltage signal (mV) output, which is connected to the microcontroller ADC acquisition interface to obtain the rider's blood pressure information.

[0098] The alcohol detection uses LM393\ZYMQ-3 sensor, the TTL output valid signal is low level, the analog output voltage is 0~5V, and the higher the concentration, the higher the output voltage.

[0099] In order to monitor the riding speed of the cyclist, the MPU6050 six-axis gyroscope sensor is used to measure the speed. When the speed limit is exceeded, there will be a voice alarm until the vehicle stops.

[0100] The GPS module uses the U-BLOXNEO-6M module, and the module has an additional amplifier circuit to speed up the satellite search speed of the passive ceramic antenna. The various parameters of the module can be set through the serial port, which is more convenient and practical. It has a PPS light (indicator function) that allows users to clearly view the current status of the sensor.

[0101] The helmet detection module uses infrared sensors to detect whether the rider is wearing a helmet correctly, and remotely warns and prompts illegal operations. When someone enters the monitoring area of ​​the HC-SR501 human infrared sensing module, this port will generate a positive voltage, otherwise it will display a negative voltage. The human body has a constant body temperature, generally at 37°C, so it will emit infrared rays with a specific wavelength of about 10μm. When the human body is within the sensor detection range, the infrared pyroelectric (PIR) element of the human infrared sensor HC-SR501 is affected by this infrared ray, and a pyroelectric effect occurs, causing the sensitive element to lose charge balance, thereby converting the optical signal into an electrical signal.

[0102] When the output value of the alcohol detection module, blood pressure and heart rate detection module is greater than the threshold, a voice alarm is issued to remind the rider to ride safely. The SYN6288 speech synthesis module uses DSP technology to convert text information into natural and smooth speech output. This module has many advantages: the module supports multiple languages, including Chinese, English, Russian, etc.; the volume, speech speed, pitch and other parameters can be adjusted to meet different needs; the digital speech synthesis technology is used to output clear and natural speech; it supports serial communication and is easy to use; it is small in size and low in power consumption, suitable for various speech synthesis application scenarios.

[0103] Specifically, the Morse code is used to implement the SOS one-button alarm function, where S represents three short signals and O represents three long signals, and the long signal is three times the short signal. When using Morse code to call for help, a combination of long and short signals is required, that is, three short, three long, and three short signals are sent in groups.

[0104] Example 3

[0105] Of course, the main controller can also be used to upload alcohol concentration, rider's body parameters, and GPS location information to the cloud platform through the WIFI module or 4G. Riders can view relevant data during riding on the cloud platform interface or using the software APP. The cloud platform completes the fusion and cleaning of detection data, data storage, data processing, and analysis and decision-making. The cloud platform uses location information to recommend the best route for riders, analyzes rider status, and determines whether there are any violations based on location information and traffic rules at the location and records them. It provides data statistics and trend forecasts for cycling managers, while improving riders' riding experience and safety.

[0106] The main controller uses STM32F103, which is a 32-bit microcontroller based on the Cortex-M3 core. It has 37 GPIOs, 2 12-bit ADCs with a total of 12 channels, and a rich set of timer peripherals. The main controller in this system mainly completes the aggregation of data collected by the end-side device, completes the protocol conversion, and performs simple data processing and analysis, and uploads the results to the cloud via WIFI or 4G.

[0107] The management of the cycling status monitoring cloud platform mainly relies on advanced technologies such as artificial intelligence, the Internet of Things, big data, and cloud computing to achieve real-time collection, storage, analysis, and display of cycling data. The cyclist status monitoring system architecture involved in the present invention adopts a cloud + end cloud platform system architecture. Figure 1 As shown in Figure 1, it is mainly divided into three layers: data collection layer, data transmission layer and cloud platform application layer. The design of cloud server is mainly reflected in the different functions of cloud platform application layer.

[0108] The data collection layer mainly realizes the collection of rider status parameters and provides data support for data analysis and prediction. The collected data mainly include the rider's physiological parameters, including blood pressure, heart rate, etc., which are used as input for the rider's health status analysis. The speed sensor is used to obtain the speed of the vehicle during riding, determine whether there is speeding during riding, record the rider's riding parameters and riding habits, and give the rider reasonable suggestions. The GPS module is used to complete the rider's position positioning and provide location information for route planning. The helmet detection model is used to detect whether the rider wears the helmet in accordance with the regulations. If it does not meet the requirements, an alarm will be issued. The SOS one-key alarm module will press the SOS button to alarm when the rider encounters a dangerous situation, which will provide safety protection for the rider and send location information.

[0109] The data transmission layer is the middle layer of the system, and serves as a bridge between uploading and downloading. The data transmission layer converts the protocol of the data acquisition layer, packages it, and uploads it to the application layer. It can communicate with the cloud platform upward, making full use of the computing resources, storage resources, and communication resources of the cloud platform to provide technical support and management and safety assurance for the rider safety monitoring system; it needs to receive the status information collected by the on-site end side, perform calculations and analysis on the collected data to obtain the rider's status, etc.; finally, it sends control instructions to the end-side controller to implement rider status warning and other controls.

[0110] The cloud platform gathers monitoring information resources of various devices and intelligent sensor controllers, builds a rider's riding status database, and realizes centralized management of the riding comprehensive database; the riding status monitoring cloud platform is a central platform for system monitoring and operation and maintenance management, which can query, count and manage status information, including setting control and monitoring strategy adjustments, querying rider status and historical records. Through multi-data fusion, deep data mining and application analysis, it can form intelligent scheduling and control strategies, intelligent auxiliary decision support for asset maintenance and operation and maintenance management, and data-based early warning and forecasting functions, and generate various statistical reports, trend curves, and analysis reports, which constitute the core technical support for the riding status monitoring system.

[0111] In order to monitor the status of the rider, it is necessary to collect status parameters through various detection modules, such as blood pressure and heart rate modules, speed sensors, GPS modules, helmet detection modules, etc. If the rider has an abnormal situation or an emergency, early warning can be implemented, such as alarm module, bike lock module and SOS one-key alarm module. Use the communication module to communicate with the cloud platform. If the rider has his own wearable device, he can monitor physiological parameters and upload the data to the main controller using the Bluetooth module. The end-side block diagram is as follows: Figure 2 shown.

[0112] Therefore, the present invention can also be designed as a riding status monitoring device, including a wearable terminal and a cloud platform; the wearable terminal is equipped with a helmet detection module, a physiological parameter detection module, an alcohol detection module, a GPS module, a vehicle speed sensor module, a communication module and a main controller;

[0113] The helmet detection module is used to detect whether the rider is wearing a helmet. If the rider is not wearing a helmet before riding, an alarm is triggered and the bike cannot be unlocked until the rider wears a helmet. If the rider still does not wear a helmet correctly after the alarm is triggered, the rider is prompted to lock the bike after a preset time.

[0114] If the rider does not wear a helmet correctly during riding, the alarm will continue to sound;

[0115] A physiological parameter detection module is used to obtain the physiological parameters of the rider;

[0116] Alcohol detection module, used to obtain the cyclist's alcohol concentration data;

[0117] GPS module, used to obtain the real-time location of the rider and the traffic rules at the location;

[0118] The vehicle speed sensor module is used to obtain the speed of the rider during riding;

[0119] The main controller is connected to the helmet detection module, the physiological parameter detection module, the alcohol detection module, the GPS module, the vehicle speed sensor module and the communication module, and is used to gather information from the helmet detection module, the physiological parameter detection module, the alcohol detection module, the GPS module and the vehicle speed sensor module, and transmit the gathered information to the cloud platform;

[0120] The wearable terminal communicates with the cloud platform through the communication module;

[0121] The cloud platform is equipped with a cycling route planning module, a cycling violation analysis module, and a cycling status analysis module;

[0122] Cycling route planning module, used to recommend the best route for cyclists based on their location information;

[0123] The cycling violation analysis module is used to determine whether the rider has exceeded the speed limit during riding based on the rider’s speed and the traffic rules at the location;

[0124] The riding state analysis module is used to analyze the riding state of the rider using the rider state analysis model based on the rider's physiological parameters (heart rate and blood pressure), riding speed, whether there is a violation, alcohol concentration and whether the helmet is worn correctly.

[0125] The communication module can adopt a 4G module, a Bluetooth module or a WIFI module.

[0126] The 4G module uses SIM7600 to upload the data received, analyzed and processed by the main controller to the cloud.

[0127] If there is a WIFI signal, a WIFI module can be used to upload the data received and analyzed by the main controller to the cloud. ESP8266 is a WIFI microcontroller based on NXP's QNXvisor. It has multiple functions, including WIFI connection and management, Bluetooth connection, ZigBee support, etc.

[0128] The Bluetooth module is HC-06, which uses the Bluetooth protocol to transmit the sensor data to the main controller to collect data. If the rider wears wearable devices such as bracelets and watches, the data of the wearable devices can be directly transmitted to the main controller.

[0129] The main functions of the rider status monitoring and management cloud platform are:

[0130] 1) User registration and login, mainly to complete user login and registration.

[0131] 2) Cycling route planning module: Optimal cycling route planning and recommendation. Based on the cyclist's starting address and destination address, the module uses the optimal cycling route planning to give three route recommendations, namely the shortest route, the route with the fewest traffic lights, and the route with the most shade;

[0132] 3) Cycling violation analysis module: Determine whether the cyclist has violated the traffic regulations based on the traffic rules of the road section where the cyclist is located, and provide improvement suggestions for the cyclist's violations.

[0133] 4) Cycling status analysis module: Based on the input of the rider's physiological parameters (heart rate and blood pressure), riding speed, whether there is a violation, alcohol concentration, and whether the helmet is worn correctly, the rider's riding status is given using the rider status analysis model, corresponding to four levels: excellent, good, average, and poor, providing status analysis and query for the rider. Figure 4 shown.

[0134] More preferably, a monitoring strategy optimization model is provided. Different cyclists have their own monitoring preferences, and the monitoring strategy can be continuously optimized to adapt to different cyclists.

[0135] The system's cloud platform uses Alibaba Cloud, which is divided into two parts: business cloud and AI training platform. The business cloud meets managers' needs for remote control of rider status parameters, system data storage, data processing, analysis and decision-making, and intelligence, providing managers with complete integrated services; Alibaba Cloud AI training platform provides one-stop AI skill development services for deep learning, helping managers quickly develop, create and deploy algorithm models, and manage full-cycle AI workflows. The business cloud and AI training platform complement each other and work together to provide reliable, stable, efficient and convenient cloud services for the rider management system.

[0136] The business cloud platform is divided into four major parts according to the functional differences of cloud-based business logic: communication gateway area, application business area, data storage area and data analysis area. Through organic combination, it realizes centralized control, real-time monitoring and data analysis and mining of mid-end devices in the rider monitoring system.

[0137] The communication gateway area ensures efficient and real-time data interaction between the rider monitoring systems distributed in different geographical locations and the cloud. By deploying a distributed cluster of highly reliable and highly concurrent MQTT communication servers on the cloud, real-time and stable communication services can be quickly established between devices and between users and devices, ensuring smooth messaging of the entire lighting system.

[0138] The application business area executes application services, processes user or device requests in a timely and efficient manner, and combines the data storage area with the data analysis area to complete the business logic implementation of conventional services and personalized value-added services in the rider monitoring system. Conventional services include: user registration, login, password retrieval, product equipment creation, deletion, status query, equipment abnormality diagnosis, remote control, data point service, and data alarm service. Personalized value-added services include data statistical analysis, expert system, system optimization suggestions, and push of customer personalized needs.

[0139] The data storage area collects system equipment data and user behavior data from the communication gateway area and the application business area, stores them into big data, provides real-time and efficient query services for the application services in the application business area, and provides data support for big data analysis in the data analysis area.

[0140] The data analysis area has efficient and powerful computing performance, providing two functions: data mining service and high-performance computing service. The data mining service is based on the big data of rider detection and perception, and customizes rules according to system requirements to perform information mining of big data.

[0141] The research and development of business cloud service platform includes two parts: cloud platform design and application software design.

[0142] First, business cloud platform design

[0143] The cloud platform design adopts the resource positioning method and combines with the database to realize the resource storage and management of users and terminal sensor devices. The main contents of the cloud platform design are as follows:

[0144] ① User and device registration. The cloud platform provides users with a user information registration interface to complete the creation of user information in the cloud platform database. When registering, users access the cloud platform interface through the HTTP protocol, send the user name and password of the monitoring center to the cloud database to complete the registration. When registering a device, in order to prevent illegal device access, the cloud platform needs to verify the Secret provided when the device accesses. The Secret is submitted by the device using HTTP. After the verification is completed, the cloud platform allows the device to register successfully.

[0145] ②MQTT communication service design. After the user and device are successfully registered, they can access the cloud platform interface through the HTTP protocol, obtain the MQTT proxy server access password, and connect to the MQTT proxy server after verification. By deploying a distributed cluster of highly reliable and highly concurrent MQTT communication servers on the cloud platform, the reception, parsing, storage, and distribution of messages can be realized, and real-time and stable communication services can be quickly established between devices and between users and devices to ensure smooth system messaging. In order to support WEB-side MQTT communication, the cloud platform also needs to support WebSocket services.

[0146] ③ Application service function design. According to the actual needs of the lighting system, the cloud platform needs to support edge device management, data storage, crowd flow big data analysis, historical data query, fault feedback and other functions. When storing data, it is necessary to ensure that the cloud platform can efficiently handle the analysis and storage of high-concurrency data; when querying historical data, it can be presented to users through statistical charts, curve charts, data tables, etc.

[0147] The cloud platform provides unified REST-style WEB services to encapsulate interfaces for services such as device management, data storage, data query, and fault feedback. It describes terminals through URLs and implements CURD (add, delete, modify, and query) of database resources using common HTTP operations such as POST, GET, DELETE, and PUT.

[0148] Second, user application software design

[0149] The rider status monitoring system expanded with cloud technology requires management and configuration of the registration, binding, and cloud access control of edge-side sensor devices.

[0150] In order to facilitate the remote management and control of the rider status monitoring system by managers and users at all levels, it is necessary to provide application software with more comprehensive and complete functions. The application software provides functions such as remote control and status information feedback to meet the different needs of the rider status monitoring system in different time periods and different areas. The application software is intended to support multiple mobile platforms such as Hongmeng, Android, and IOS, and can be installed on mobile devices such as mobile phones and tablets to meet the needs of different managers.

[0151] The system management and monitoring center provides status monitoring operations with different permissions for system managers at all levels, and realizes configuration, remote control, historical data query and statistics of the rider status monitoring system, and the acquisition of personalized services through custom rules. The control center is planned to be provided to system managers in the form of a web page. Managers can enter the control center after identity authentication using a web browser. The B / S architecture of the control center is designed to facilitate cross-platform promotion and reduce the cost of system maintenance and upgrades.

[0152] The database of the rider status monitoring system consists of a real-time database for storing real-time data and a historical database for storing historical data.

[0153] 1) Real-time database storage format design

[0154] The real-time database is the core of the configuration and operation system to achieve real-time data update. It is mainly used to store the status data of users and devices during operation. The collected data reported by the processor will be processed by the data receiving and processing module and then saved in the real-time database. In order to improve data processing efficiency and meet the system's requirements for real-time performance, the system uses the memory database Redis as the system's real-time database, and uses the advantage of fast reading of the memory database to store real-time data of users and devices.

[0155] 2) Historical database storage design

[0156] Compared with the frequently updated device data stored in the real-time database, the historical database is mainly used to store the basic system information that changes less frequently, and save the historical data of the device data to provide a historical basis for the subsequent data analysis and statistics of the device. There are many different types of data in the rider status monitoring system. In order to store many heterogeneous data in the system, the system uses the loosely structured, scalable and more flexible non-relational data (NoSQL) MongoDB as the system's historical database. MongoDB is a document-based database in NoSQL, and multiple documents constitute a collection in the database.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A riding status monitoring method, characterized in that: The process includes: Detect whether the rider is wearing a helmet; specifically: If the rider is not wearing a helmet before riding, an alarm will be triggered and the bike can only be unlocked after the rider puts on a helmet. If the rider still does not wear a helmet correctly after the alarm is triggered, the rider will be prompted to lock the bike after a preset time. If the rider does not wear a helmet correctly during riding, the alarm will continue to sound; Obtain the physiological parameters of the rider; Detect alcohol concentration data through the rider's breath; Obtain the real-time location of the cyclist and the traffic rules at the location, and recommend the best route for the cyclist based on the cyclist's location information; Obtain the riding speed of the cyclist during riding, and determine whether the cyclist is speeding according to the riding speed of the cyclist and the traffic rules at the location; The rider's riding status is analyzed based on the rider's physiological parameters, alcohol concentration data, riding speed, whether there is any violation and whether the rider is wearing a helmet.

2. A riding status monitoring method according to claim 1, characterized in that: Physiological parameters include blood pressure data and heart rate data.

3. A riding status monitoring method according to claim 1, characterized in that: When a rider encounters an emergency, use the SOS button to alert the police.

4. A riding status monitoring method according to claim 1, characterized in that: Alcohol concentration data is detected using LM393\ZYMQ-3 sensor; The vehicle speed is collected using the MPU6050 six-axis gyroscope sensor.

5. A riding status monitoring method according to claim 1, characterized in that: The real-time location of the rider is obtained using the GPS module.

6. A riding status monitoring method according to claim 1, characterized in that: An infrared sensor is used to detect whether the rider wears the helmet correctly. The infrared sensor uses the HC-SR501 human infrared sensing module.

7. A riding status monitoring method according to claim 1, characterized in that: The riding status is divided into four levels: excellent, good, average and poor, providing status analysis and inquiry for riders.

8. A riding status monitoring system, characterized in that: include: Helmet detection module, used to detect whether the rider is wearing a helmet; If the rider is not wearing a helmet before riding, an alarm will be triggered and the lock cannot be unlocked until the rider wears a helmet; If the rider still does not wear a helmet correctly after the alarm is triggered, the rider will be prompted to lock the bike after a preset time. If the rider does not wear a helmet correctly during riding, the alarm will continue to sound; The vehicle locking module is used to trigger unlocking after the helmet detection module detects that the rider is wearing a helmet; or to forcefully trigger vehicle locking after a preset time has passed; A physiological parameter detection module is used to obtain the physiological parameters of the rider; Alcohol detection module, used to detect alcohol concentration data through the rider's breath; GPS module, used to obtain the real-time location of the rider and the traffic rules at the location; The vehicle speed sensor module is used to obtain the speed of the rider during riding; A data processing module is used to recommend an optimal route for a cyclist based on the cyclist's location information; Used to determine whether the rider is speeding according to the rider's speed and the traffic rules at the location; Used to analyze the rider's riding status based on the rider's physiological parameters, alcohol concentration data, riding speed, whether there is any violation, and whether the rider is wearing a helmet; The display module is respectively connected with the physiological parameter detection module, the GPS module, the vehicle speed sensor module, the cycling route planning module, the cycling violation analysis module, and the cycling status analysis module, and is used to display the output information of each module.

9. A riding status monitoring device, characterized in that: It includes a wearable terminal and a cloud platform; the wearable terminal is equipped with a helmet detection module, a vehicle locking module, a physiological parameter detection module, an alcohol detection module, a GPS module, a vehicle speed sensor module, a communication module and a main controller; The helmet detection module is used to detect whether the rider is wearing a helmet. If the rider is not wearing a helmet before riding, an alarm is triggered and the bike cannot be unlocked until the rider wears a helmet. If the rider still does not wear a helmet correctly after the alarm is triggered, the rider is prompted to lock the bike after a preset time. If the rider does not wear a helmet correctly during riding, the alarm will continue to sound; The vehicle locking module is used to trigger unlocking after the helmet detection module detects that the rider is wearing a helmet; or to forcefully trigger vehicle locking after a preset time has passed; A physiological parameter detection module is used to obtain the physiological parameters of the rider; Alcohol detection module, used to detect alcohol concentration data through the rider's breath; GPS module, used to obtain the real-time location of the rider and the traffic rules at the location; The vehicle speed sensor module is used to obtain the speed of the rider during riding; The main controller is connected to the helmet detection module, the physiological parameter detection module, the alcohol detection module, the GPS module, the vehicle speed sensor module and the communication module, and is used to gather information from the helmet detection module, the physiological parameter detection module, the alcohol detection module, the GPS module and the vehicle speed sensor module, and transmit the gathered information to the cloud platform; The wearable terminal communicates with the cloud platform through the communication module; The cloud platform is equipped with a cycling route planning module, a cycling violation analysis module, and a cycling status analysis module; Cycling route planning module, used to recommend the best route for cyclists based on their location information; The cycling violation analysis module is used to determine whether the rider has exceeded the speed limit during riding based on the rider’s speed and the traffic rules at the location; The riding status analysis module is used to analyze the riding status of the rider based on the rider's physiological parameters, alcohol concentration data, riding speed, whether there is any violation and whether the rider is wearing a helmet.

10. A riding status monitoring device according to claim 9, characterized in that: The wearable terminal is also connected to the APP through the communication module, and the rider can view relevant data during riding on the cloud platform interface or using the software APP.

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