Connected Vehicle Intelligent Cloud Control Platform
- ZedIoT
- September 8, 2023
- 2:45 pm
- 0 comments
Real-time monitoring of intelligent terminal equipment installed on existing vehicles, collecting data from vehicle equipment, road, and other vehicle-mounted sensors.
Project Background
The customer provides products and solutions to multiple automotive manufacturers. They have also established partnerships with well-known domestic and international insurance/reinsurance companies and logistics enterprises to provide targeted solutions, helping the industry reduce costs and increase efficiency.
Project Requirements
Real-time monitoring of intelligent terminal devices installed in existing vehicles, collecting vehicle equipment, road, environmental information, and data from other onboard sensors. The collected information from multiple sources is processed, computed, and shared on an information network platform. This enables big data analysis, algorithm training, data modeling, data sharing, and secure publishing. The system should provide effective guidance and supervision of vehicles based on different functional requirements, as well as offer professional multimedia and mobile Internet application services.
Main Functions
· Data Visualization:
Visualize statistical results or big data analysis results, including displaying key data through numbers, charts, video images, radar scenes, and other forms.
· Real-time Monitoring of Vehicle Condition:
Clicking on a vehicle icon allows users to view detailed information about the vehicle, including license plate number, owner information, vehicle type, location name, fatigue status of the vehicle, real-time tracking of the vehicle's trip trajectory, and the ability to view trajectory playback.
· Electronic Geofencing:
When logistics vehicles enter or exit geofenced areas, the platform determines if the vehicle is parked or traveling outside of working hours and the geofenced area. It issues different alerts based on the situation.
· Data Statistics:
Includes driving statistics, nighttime driving statistics, overspeeding statistics, fatigue driving statistics, risk warning statistics, and AEB/FCW event statistics.
· Device Energy Consumption Monitoring:
Real-time monitoring of changes in vehicle fuel consumption and generating reports or fuel consumption curves for historical periods. This provides a visual representation of normal and abnormal fuel consumption patterns and insufficient refueling to achieve effective fuel consumption management.
Project Highlights
· Real-time monitoring of vehicles to obtain vehicle location, posture, and status information, and provide high-risk scene reminders;
· Vehicle operation analysis to analyze the operation of vehicles, combined with trip road conditions and fuel consumption calculation to identify high-risk/major accident-prone areas;
· Alarm management to display accident alarm information during vehicle driving through images, videos, sounds, etc.;
· Customized location check-in function: when drivers start work, they need to check in within 50 meters of the logistics vehicle using a WeChat mini program. The distance between the driver and the vehicle location is calculated to determine whether the check-in is successful, ensuring that the driver arrives on time.
· Big data security management relies on multi-dimensional data analysis to ensure the safe operation of enterprise vehicles;
· Supports process-oriented, scenario-oriented, and intelligent customization, providing visual development tools and supporting integrated development and operation, shortening product iteration cycles.
Project outcome
The platform has been successfully launched in the market, providing effective management of logistics vehicles. It can collect vehicle information in real time, accurately, and efficiently. This includes real-time radar scenes, video images, location information, vehicle operational data, and driver behavior information during the driving process. Through the platform's real-time, quarterly, and annual behavior analysis reports, it can evaluate driver behavior, risk trigger probability, and accident avoidance data, providing robust safety information assessment. The ultimate goal is to achieve risk control, strengthen management
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