Vehicle Sensor Data Indexing With Edge Offload Nodes
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Solution Overview
Problem
Modern vehicles generate vast amounts of sensor data that overwhelm existing communication and storage systems, leading to bottlenecks and excessive computing resource usage, particularly when offloading data to the cloud.
Innovation Solution
Utilizing edge-based devices, such as charging stations or static locations, to store and process sensor data, derive additional content, and index it based on attributes like time and location, providing an index to a cloud-based system that aggregates data from multiple sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If sensor data is offloaded to cloud-based systems, then data storage and processing capability is improved, but communication bottlenecks and storage costs increase significantly
Solution Approach 1:
The patent segments the centralized cloud storage system into distributed edge storage nodes located at charging stations. Instead of offloading all sensor data to a central cloud, the system divides storage responsibilities across multiple edge devices that are geographically distributed near the data sources (vehicles). This segmentation reduces communication bottlenecks by enabling local storage and processing at the edge, thereby lowering communication costs while maintaining adequate storage capacity.
Solution Approach 2:
The patent introduces edge-based charging stations as intermediary devices between vehicles and cloud systems. These charging stations serve as intermediate storage and processing nodes that receive sensor data from vehicles, perform local processing and indexing, and only upload summarized or queried data to the cloud when necessary. This intermediary layer reduces the volume of data transmitted over communication networks, thereby reducing communication costs while preserving data accessibility.
2Adaptability or versatility
If raw sensor data is stored and processed centrally, then data availability is improved, but computing resource consumption and processing load increase excessively
Solution Approach 1:
The patent segments centralized computing operations into distributed edge computing tasks performed at charging stations. Each edge device executes local processing, filtering, and indexing operations on sensor data received from vehicles. This segmentation distributes computing resource consumption across multiple edge nodes rather than concentrating all processing load in the cloud, thereby reducing overall computing resource usage while maintaining data accessibility through the distributed network.
Solution Approach 2:
The patent implements preliminary processing and indexing of sensor data at edge devices before potential cloud upload. Edge charging stations perform initial data filtering, aggregation, and index creation locally, so that when data needs to be accessed or uploaded to the cloud, the processing workload has already been reduced. This preliminary action at the edge reduces the computing resource burden on centralized cloud systems while preserving data accessibility.
3Loss of information
If comprehensive sensor data is transmitted to the cloud, then data completeness is improved, but communication bandwidth requirements and transmission time increase
Solution Approach 1:
The patent extracts only essential metadata and index information from complete sensor data at the edge, separating the full raw data from its representative characteristics. Edge charging stations create compact indexes that capture the essential information content of sensor data without transmitting the entire data sets. This extraction approach maintains data completeness in terms of information accessibility while dramatically reducing the volume of data transmitted, thereby reducing transmission time and communication bandwidth requirements.
Solution Approach 2:
The patent creates simplified copies (indexes) of sensor data at edge devices that represent the full data without being the complete data sets themselves. These index copies contain metadata and key information that enable data querying and retrieval without requiring transmission of the original large-volume sensor data. When cloud access is needed, the system transmits these compact index copies rather than complete data sets, maintaining information accessibility while minimizing transmission time and bandwidth usage.
4Productivity
If edge-based indexing is implemented, then communication efficiency is improved, but system complexity increases due to distributed architecture
Solution Approach 1:
The patent implements a universal indexing framework and standardized data protocols that work across all edge devices in the distributed network. By establishing common interfaces, standardized index formats, and unified communication protocols, the system enables multiple edge charging stations to operate with consistent behavior patterns. This universality reduces the operational complexity of managing distributed edge devices, making the system easier to deploy and maintain while preserving communication efficiency benefits.
Data Source
AI summary
Systems, methods, and other embodiments described herein relate to improving the use of sensor data in a mobile context by indexing the sensor data with derived content. In one embodiment, a method includes, responsive to an offload event, acquiring sensor data from a vehicle. The method includes generating an index of the sensor data according to attributes of how the sensor data was acquired. The method includes analyzing the sensor data to derive additional content using at least a model. The method includes updating the index using the additional content to further indicate characteristics of the sensor data relative to the attributes. The method includes providing the index to a remote device as a report about contents of the sensor data.