Distributed Sensor Data Processing for Mobile Trip Detection
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Solution Overview
Problem
Processing large datasets of remotely captured sensor data requires significant computing resources and poses challenges in efficient deployment and configuration, particularly in systems handling data from mobile computing devices.
Innovation Solution
A distributed data processing system that receives and analyzes sensor data from mobile devices to detect trip characteristics, such as vehicle mode, user roles, and other features, using modules like trip detection, driver detection, and geo-fencing, while aligning reference frames and identifying anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a centralized system is used to process large datasets of sensor data, then processing capability is improved, but system complexity and resource consumption increase
Solution Approach 1:
The patent divides the data processing system into distributed computing nodes that independently process sensor data in parallel. Each node handles specific portions of the dataset, eliminating the need for a single complex centralized processor while maintaining high processing capability through distributed computation across multiple simpler nodes.
2Productivity
If more computing resources are allocated to process sensor data, then processing speed is improved, but resource efficiency deteriorates
Solution Approach 1:
The system implements self-service mechanisms where computing nodes automatically allocate and manage their own resources based on data processing requirements. The distributed architecture enables nodes to dynamically adjust resource consumption, processing data only when needed and entering low-power states when idle, thereby maintaining high processing speed while improving overall resource efficiency.
3Loss of energy
If a distributed system is implemented to process sensor data, then resource efficiency is improved, but system configuration difficulty increases
Solution Approach 1:
The patent employs universal configuration protocols and standardized interfaces that enable distributed computing nodes to be deployed and configured consistently across different hardware platforms. This multi-functional approach allows the same configuration framework to manage diverse nodes, reducing configuration difficulty despite the distributed nature of the system.
4Quantity of substance
If sensor data from multiple mobile devices is collected, then data comprehensiveness is improved, but network bandwidth consumption increases
Solution Approach 1:
The system extracts and processes only the essential sensor data elements needed for trip detection and analysis, filtering out redundant information before transmission. This selective extraction approach maintains data comprehensiveness for trip detection purposes while significantly reducing the volume of data transmitted over the network, thereby lowering bandwidth consumption.
Data Source
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AI summary
Aspects of the disclosure relate to processing remotely captured sensor data. A computing platform having at least one processor, a communication interface, and memory may receive, via the communication interface, from a user computing device, sensor data captured by the user computing device using one or more sensors built into the user computing device. Subsequently, the computing platform may analyze the sensor data received from the user computing device by executing one or more data processing modules. Then, the computing platform may generate trip record data based on analyzing the sensor data received from the user computing device and may store the trip record data in a trip record database. In addition, the computing platform may generate user record data based on analyzing the sensor data received from the user computing device and may store the user record data in a user record database.