In this use case, a solutions provider for the Internet of Vehicles (IoV) industry from Shanghai adopted the solution based on Application Real-Time Monitoring Service (ARMS) to collect statistics about online conditions of vehicles.

  • It is impossible to collect multidimensional statistics on raw data by using databases because a vast amount of data is involved (approximately 100,000 vehicle data records per second).

ARMS-based IoV monitoring solution

The following figure shows the overall architecture.
  • The automaker's platform uploads real-time data on new-energy vehicles to Alibaba Cloud by using Message Queue (MQ).
  • The ARMS real-time application monitoring function works with MQ to obtain the online data of all vehicles and to perform real-time statistics and storage. The following information is displayed:
    • 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 in columnar storage mode by custom aggregation.
    • Data delivery: ARMS delivers data to downstream services after they call the corresponding API operations.
  • Downstream Enterprise Distributed Application Service (EDAS) obtains data from ARMS by calling corresponding API operations, and presents and analyzes data externally by using applications of customers.

Business values of the IoV monitoring solution

  • It tracks the running status of vehicles in real time, collects statistics on fault data in real time, and gives feedback on statistic results based on different vehicle models, achieving dramatic quality enhancement.
  • It detects violation actions in the first place, for example, swindling for subsidies, by monitoring the running status of new-energy vehicles.