Data synchronization method and system for internet of vehicles device

By analyzing and optimizing the initial perception mode of the vehicle-mounted sensing unit, and combining perception supervision information and user decisions, the problem of low data synchronization efficiency of the vehicle-mounted sensing unit was solved, achieving more efficient and accurate environmental perception and improving the safety and intelligence of autonomous driving.

CN122248001APending Publication Date: 2026-06-19GUANGDONG CHUANCHANG INFORMATION TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
GUANGDONG CHUANCHANG INFORMATION TECH CO LTD
Filing Date
2026-04-07
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

In existing technologies, the data synchronization and processing efficiency of on-board sensing units is relatively low, resulting in inaccurate and untimely environmental perception, which affects the safety and intelligence of autonomous driving.

Method used

By acquiring IoT sensing tasks, analyzing the initial sensing patterns of the vehicle-mounted sensing units, collecting and summarizing data, and optimizing and adjusting based on sensing supervision information, the system can dynamically adapt to different driving scenarios by combining user decision-making tendencies.

Benefits of technology

It improves the accuracy and efficiency of vehicle environmental perception, reduces data synchronization errors and delays, enhances the performance and stability of vehicle networking devices, and ensures driving safety and intelligent decision-making.

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Abstract

This invention relates to the field of data processing, specifically to a data synchronization method and system for vehicle-to-everything (V2X) devices. The method involves acquiring the vehicle's IoT sensing task, analyzing the data sensing requirements of each on-board sensor unit based on the IoT sensing task, obtaining the initial sensing mode of each on-board sensor unit, driving each on-board sensor unit to collect and aggregate data based on the initial sensing mode, monitoring the data collection and aggregation process, generating sensing supervision information, optimizing the IoT sensing task and the initial sensing modes of each on-board sensor unit based on the sensing supervision information to obtain optimization tendency information, and making optimization decisions based on pre-deployed user decision tendencies to adjust the IoT sensing task and the initial sensing modes of each on-board sensor unit.
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