Vehicle Data Interception for Situational Awareness
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Solution Overview
Problem
Vehicles generate vast amounts of data from sensors, which are often temporarily used and then overwritten or deleted, not being utilized or stored for other purposes such as public safety or operational optimization.
Innovation Solution
A vehicle-generated data management system that intercepts and processes sensor data, GPS data, and time data to generate situational data, which is then transmitted to a hybrid cloud system for further processing and utilization by various users or systems, leveraging machine learning and artificial intelligence techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If vehicle sensors continuously generate and temporarily use data, then the vehicle can perform its primary functions, but the data is overwritten or deleted without being stored or utilized for other purposes
Solution Approach 1:
The system extracts valuable information from vehicle-generated data by intercepting sensor data, GPS data, and time data from the vehicle's computing system. This extracted data is then processed to generate situational data that can be stored and utilized for various purposes such as public safety and operational optimization, preventing the loss of valuable information while maintaining the vehicle's primary functions
Solution Approach 2:
An intermediary computing system acts as a mediator between the vehicle's sensor data and potential users or applications. This intermediary intercepts data from the vehicle, processes it to extract meaningful information, generates situational data, and transmits it to a hybrid cloud system or directly to users, thereby preserving data value without interfering with the vehicle's operation
2Loss of information
If the system processes and stores all vehicle-generated data, then data utilization and value are improved, but system complexity and data management burden increase
Solution Approach 1:
Instead of storing all raw sensor data, the system extracts only the essential elements (sensor data, GPS data, time data) from the vehicle-generated data stream. This extraction approach captures the valuable information needed for situational awareness while significantly reducing the data volume that requires storage and management, thereby lowering system complexity
Solution Approach 2:
The data processing system is segmented into distinct functional modules: data interception, data processing and extraction, situational data generation, and data transmission. This modular segmentation allows each component to handle specific tasks efficiently, reducing the overall management burden while maintaining comprehensive data utilization
Data Source
AI summary
Computer-implemented methods for a vehicle-generated data management system. Aspects include receiving vehicle-generated data from a vehicle associated with a vehicle-generated data management system. Aspects further include processing the vehicle-generated data to extract sensor data, GPS data, and time data. Aspects further include generating situational data using the sensor data, the GPS data and the time data. Aspects further include transmitting the situational data and the processed vehicle-generated to a hybrid cloud system.