Mobile Delivery Device Compression for Location Tracking
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Solution Overview
Problem
The transmission of large volumes of location and acceleration data from mobile delivery devices in distribution networks is cumbersome, inefficient, and costly due to bandwidth and battery constraints, particularly when using cellular networks.
Innovation Solution
Implementing data compression techniques such as delta encoding and numeric base conversion on mobile devices to reduce the size of GPS and acceleration data before transmission, including methods like eliminating redundant fields and applying delta encoding to numerical values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If raw location and acceleration data is transmitted directly from mobile delivery devices, then data completeness is maintained, but transmission efficiency deteriorates and network costs increase
Solution Approach 1:
The mobile delivery device performs data compression operations (delta encoding, numeric base conversion, field elimination) locally before transmission. This preliminary action reduces the data volume to be transmitted over the network, improving transmission efficiency without requiring complex processing at the remote system.
Solution Approach 2:
The system changes the parameters of the data representation by applying delta encoding to numerical fields and converting to numeric base 62. These parameter changes reduce the data size while maintaining information integrity, directly addressing the contradiction between data completeness and transmission efficiency.
2Measurement precision
If frequent data transmission is performed to maintain real-time tracking, then tracking accuracy is improved, but battery consumption increases and network bandwidth is exceeded
Solution Approach 1:
By changing the data representation parameters through compression techniques, the system enables more frequent transmissions without proportionally increasing energy consumption. The reduced data size means less energy is required for transmission while maintaining real-time tracking capability.
Solution Approach 2:
The device prepares and compresses data locally before transmission, so that when transmission occurs, it uses less network bandwidth and energy. This allows the system to transmit more frequently while controlling battery consumption through efficient data packaging.
3Quantity of substance
If data compression is applied at the mobile device, then transmission size is reduced, but device processing complexity increases
Solution Approach 1:
The system uses relatively simple parameter changes (delta encoding, base conversion) that can be implemented with standard processing capabilities on mobile devices. These changes reduce data size while avoiding the need for complex compression algorithms.
Solution Approach 2:
The compression process is segmented into distinct operations: identifying compressible fields, applying delta encoding to numerical values, converting to base 62, and eliminating redundant fields. This segmentation makes the complex task manageable and implementable on resource-constrained mobile devices.
4Reliability
If all location and acceleration data is transmitted, then data completeness is maintained, but network bandwidth is exceeded and transmission delays occur
Solution Approach 1:
The system changes data parameters through compression techniques that reduce size while preserving information. Delta encoding maintains the relative relationships between data points, and base conversion preserves numerical accuracy, ensuring data completeness is maintained even at reduced size.
Solution Approach 2:
The system extracts and eliminates redundant fields from the data before transmission. By identifying and removing unnecessary fields while retaining essential information through compression, the system maintains data completeness for critical tracking parameters while reducing overall data volume to improve transmission speed.
Data Source
AI summary
A system and method for tracking mobile devices. The system can include a data center and a plurality of mobile devices in communication with the data center via the network. Each mobile device can include at least one sensor configured to periodically generate tracking data records, a memory, and a processor in communication with the at least one sensor and the memory. The mobile devices can transmit sets of tracking data records to the data center using reduced bandwidth relative to the original records by implement compression algorithms that can include delta encoding and/or numeric base conversion of number valued fields, as well as additional compression techniques that may be reversed at the data center to reconstruct the original records or otherwise decompress the data.