Fleet Vehicle Event Reporting With Cloud Deduplication
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Solution Overview
Problem
Existing vehicle event detection systems often rely on single-sensor data and local storage, lacking the ability to efficiently analyze and share relevant vehicle event information across a fleet of vehicles, leading to potential duplication and inefficiencies in data utilization.
Innovation Solution
A system comprising a fleet of vehicles equipped with sensors, processors, and transceivers that communicate with a remote computing server to process, analyze, and share vehicle event data, utilizing computer vision techniques to extract relevant information and generate timely event reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicle event data is stored locally in each vehicle, then data availability for individual vehicle analysis is maintained, but data duplication occurs across the fleet and overall data utilization efficiency deteriorates
Solution Approach 1:
The patent merges data storage and processing functions from individual vehicles to a centralized cloud server. Multiple vehicles' event data is consolidated in one location, eliminating duplication while maintaining availability through centralized access. The system combines distributed data collection with centralized processing to resolve the contradiction between local data availability and fleet-wide data efficiency.
Solution Approach 2:
The cloud server acts as an intermediary between individual vehicles and the fleet management system. Instead of each vehicle storing and processing data independently (causing duplication), the intermediary server receives, stores, and processes data from multiple vehicles, providing efficient access without duplication while maintaining data availability for all users.
2Device complexity
If single-sensor data is used for vehicle event detection, then system complexity is reduced, but detection accuracy and event identification reliability deteriorates
Solution Approach 1:
The system merges data from multiple sensor types (accelerometers, gyroscopes, GPS, cameras) into a unified event detection process. By combining these diverse data sources at the cloud server, the system achieves high detection accuracy without requiring each individual vehicle to process complex multi-sensor data locally, thus resolving the contradiction between simplicity and accuracy.
3Speed
If all vehicle event data is processed and transmitted in real-time, then event response time is improved, but data transmission volume and processing load increases
Solution Approach 1:
The system extracts only relevant event data from the continuous stream of vehicle sensor data, rather than transmitting all data. Event detection algorithms identify significant events (collisions, hard braking, unusual routes) and extract only these events for transmission and processing. This extraction approach maintains fast response times for actual events while dramatically reducing overall data transmission volume.
Solution Approach 2:
Instead of processing and transmitting all vehicle data continuously (excessive action), the system processes and transmits only the necessary event data (partial action). This selective processing approach achieves timely response to actual events without the burden of handling complete continuous data streams, resolving the contradiction between speed and data volume.
Data Source
AI summary
This disclosure relates to a system configured to generate and provide timely vehicle event information for a fleet of vehicles including at least a first vehicle. Individual vehicles detect vehicle events and transmit related information to a remote computing server. The remote computing server determines whether the detected vehicles events are relevant to add to a set of vehicle events scenarios. For example, if a particular vehicle event is duplicative of a previous vehicle event, if may not need to be added. The newest vehicles events may be reported at certain intervals, in particular if they are indicative of a trend.