In this use case, a solution provider from Shanghai for the Internet of Vehicles (IoV) industry adopted the ARMS-based solution to take statistics of online conditions of vehicles.
- As a vast amount of data is involved (approximately one hundred thousand vehicle data records per second), multi-dimensional statistics of raw data using databases is not available.
The following figure shows the overall architecture.
- The automaker’s platform uploads real-time data on new-energy vehicles to Alibaba Cloud using Message Queue.
- ARMS monitors Message Queue interconnected with the monitored service in real time to obtain the online data of all vehicles and perform real-time statistics and storage.It provides the following functions:
- Computing orchestration and storage: ARMS statistically analyzes the online rate and failure rate based on the reported vehicle information in multiple dimensions, such as the region, vehicle type, and enterprise, and stores the statistical analysis results by column based on the custom aggregation dimension.
- Data delivery: ARMS delivers downstream data by means of data API.
- Downstream EDAS calls data using APIs, and presents and analyzes data externally using applications of customers.
- It tracks running status of vehicles in real time, takes statistics of fault data in real time and gives feedback on statistics results based on different vehicle models, and achieves dramatic quality enhancement.
- It detects violation actions in the first instance, for example, swindling for subsidies, by monitoring the running status of new-energy vehicles.