This product is an intelligent real-time monitoring system for bus overload. It uses sensor network to monitor passenger density and body state in real time. It uses cloud computing technology to dynamically monitor passenger volume from two dimensions of time and space, judge whether the vehicle is overloaded, and prompt vehicle management personnel to deal with it in time. Through the new generation of Internet of things technology to achieve wireless transmission, data will be transmitted to the cloud platform, bus operators can check the overload of a certain road vehicle for a period of time on the platform, reasonably arrange the number of trains, make full use of public resources, and improve bus ride comfort and sustainable development. The system also includes functions such as dynamic passenger number statistics, passenger density distribution trend, in-car environment monitoring, and body condition judgment, which effectively improves the safety of bus operation and passenger comfort, helps to relieve traffic pressure, and promotes urban intelligence Construction etc. The system is mainly divided into four modules, namely, power module, information acquisition module, information processing module and information feedback module. (1) Power supply module: Provide stable voltage for the system. (2) Information acquisition module: Build 5 sub-modules to collect information to determine the overload state. With pressure sensing The system is initially divided into three parts: idle, busy and overloaded. The statistical system of bus passenger density distribution is established with infrared sensor as the core, and the distribution trend of passenger flow is presented in time through data statistics and algorithm analysis and processing. Environmental sensors such as carbon dioxide, temperature and humidity are used to monitor the environment in the car from various aspects and provide passengers with current environmental conditions in the car in real time; the tire wear is monitored by pressure and deformation sensors, and a bus body condition discrimination system is established. The vehicle body tires are initially divided into four states: normal, slight wear, severe wear, and abnormal; the bus statistics database is established by recording the overload of public transport vehicles in real time. After the information collection module collects the live data of the vehicle body, one copy is immediately fed back to the bus driver and the other is summarized by the bus management center to provide more effective information for scheduling. (3) Information processing module: the data analysis module comprehensively analyzes the recorded passenger flow distribution information and the real-time detected passenger density information within a certain period of time, and analyzes and processes the data through statistical algorithms to give the discrimination of overload state; The information interaction module collects the car body information to the bus management center through wireless communication technology, at the same time, the current bus body condition, passenger distribution and overload warning information are displayed to the driver through the OLED screen, and different suggestions are taken according to different situations. (4) Information feedback module: When the vehicle body information acquisition module judges that a certain data is abnormal, the vehicle warning sub-module prompts the driver to repair in time to solve the problem; when the vehicle is overloaded and the tires are severely worn, the red light is lit, To signal the driver to stop urgently.