Swarm Vehicle Data Header Extraction for Backend Processing
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Solution Overview
Problem
Existing systems for collecting and processing transportation vehicle-based environmental data face high data costs and low flexibility when requirements change, with slow implementation of new functions, and lack intelligent processing capabilities.
Innovation Solution
A method and device for optimizing the collection and transfer of data from a swarm of vehicles, where parameterized orders define route sections, swarm size, and time intervals, allowing for intelligent processing and storage of headers, enabling efficient retrieval and processing of relevant data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is collected from all transportation vehicles continuously, then data completeness is improved, but data costs and processing complexity increase
Solution Approach 1:
The patent extracts and transmits only the header data (containing route section, time interval, and data class information) from vehicles to the backend, rather than transmitting all complete data sets. This extraction approach reduces data volume and transmission costs while maintaining the ability to retrieve complete data sets later based on header information, thus resolving the contradiction between data completeness and data quantity.
Solution Approach 2:
The patent segments data transmission into two stages: first transmitting only the header information (segment 1) which contains metadata about the data sets, and then transmitting only the required complete data sets (segment 2) based on header analysis. This segmentation allows the system to initially work with minimal data while maintaining access to complete data when needed, reducing overall data volume while preserving data completeness.
2Loss of information
If all data sets are transmitted immediately, then data availability is improved, but data processing efficiency decreases
Solution Approach 1:
The patent performs preliminary action by first transmitting and analyzing header data before transmitting complete data sets. The header contains essential metadata (route section, time interval, data class) that allows the backend to pre-process and organize information before the actual data sets arrive. This preliminary header transmission enables efficient data organization and reduces processing time when complete data sets are received, as they can be immediately associated with the correct route sections and time intervals.
Solution Approach 2:
The patent implements dynamic data transmission where the system adapts its behavior based on header analysis. Instead of transmitting all data sets immediately, the system dynamically determines which data sets need to be transmitted based on the header information and current processing needs. This dynamic approach allows the system to optimize processing efficiency by only transmitting and processing data that is actually needed, while maintaining data availability through the header information that guides subsequent retrieval operations.
3Adaptability or versatility
If data collection requirements change frequently, then system adaptability is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal header structure that can accommodate multiple data classes, route sections, and time intervals through a single standardized format. The header contains generic fields (route section identifier, time interval, data class) that can be filled with different values depending on the specific data being transmitted. This universal header design allows the system to adapt to changing data collection requirements without increasing complexity, as the same header structure serves all purposes while the backend processes different data based on the header values.
Data Source
AI summary
A method for collecting transportation vehicle-based data and transferring the data to a backend computer, wherein the respective data sets relate to predefined route sections travelled along by a swarm of data-collecting vehicles, wherein parameterized orders for the acquisition of transportation vehicle-based data are stored in the backend computer and each order includes the parameter of route section, which defines the route section for which transportation vehicle-related data is to be collected; the parameter of swarm size, which defines how many transportation vehicles per unit of time are to collect data for the specified route section; and the parameter time interval, which defines the time interval in which data is to be acquired for the route section. Route-related data is continuously transferred to the backend computer from each transportation vehicle of the swarm, wherein a header constitutes an overview of the transportation vehicle-based data stored temporarily in the transportation vehicle.