Motion Data Compression for Wearable Tracking Devices
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Solution Overview
Problem
Wearable devices transmitting high amounts of data over cost-prohibitive networks, such as cellular networks, incur significant expenses, especially for non-human entities like pets, due to the need for continuous data transmission for accurate monitoring.
Innovation Solution
Implementing a method to compress high-fidelity motion data and selectively transmit either compressed or high-fidelity data based on network bandwidth and conditions, using a tracking device with processing logic to manage data transmission, storing data locally and transmitting it over low-cost networks when high-fidelity data is required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all captured data is transmitted from wearable device to server, then accurate and comprehensive visualizations are provided, but substantial transmission expenses are incurred over cellular networks
Solution Approach 1:
The patent segments data into two categories: high-fidelity data (raw accelerometer data) and low-fidelity data (processed motion data). The wearable device performs local processing to extract essential motion information, transmitting only the necessary data over cellular networks while sending comprehensive data over Wi-Fi networks when available.
Solution Approach 2:
The patent applies partial action by transmitting only the minimum necessary data over cellular networks (low-fidelity data) to maintain accurate monitoring while minimizing costs. When Wi-Fi is available, the system transmits excessive data (all captured data) to ensure complete accuracy without cost concerns.
2Loss of energy
If compressed data is transmitted over cellular networks, then transmission costs are reduced, but data fidelity and monitoring accuracy may be compromised
Solution Approach 1:
The patent dynamically adjusts data transmission fidelity based on network conditions and device state. The system toggles between transmitting high-fidelity and low-fidelity data depending on whether the device is inside or outside geo-fenced areas, and whether Wi-Fi connectivity is available, optimizing both cost and accuracy in real-time.
Solution Approach 2:
The patent changes the data fidelity parameter based on transmission context. High-fidelity raw data is transmitted when complete accuracy is required (outside geo-fences, Wi-Fi available), while low-fidelity processed data is transmitted during normal operation within geo-fenced areas to minimize costs.
3Reliability
If wearable device on non-human entity continuously transmits data without interruption, then accurate monitoring is maintained, but data transmission expenses become prohibitive
Solution Approach 1:
The patent implements periodic action by having the wearable device continuously monitor motion data locally but transmitting data periodically based on significant events or time intervals. The device processes data continuously to detect motion events, then transmits only relevant data packets over cellular networks rather than continuous streams.
Solution Approach 2:
The patent introduces an intermediary processing layer at the wearable device that acts as a mediator between data collection and transmission. The device's processor analyzes raw accelerometer data locally, filtering and preprocessing it to identify significant motion events, thereby reducing the volume of data requiring expensive cellular transmission while maintaining monitoring reliability.
Data Source
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AI summary
A system, method, and apparatus for compressing and transmitting motion data. The method comprises receiving high fidelity motion data from a motion sensing device, the high fidelity motion data including a plurality of motion data samples; transmitting the high fidelity motion data to a server; compressing the high fidelity motion data, wherein compressing the high fidelity motion data comprises identifying a subset of the motion data samples and generating a value representing the summary of activity based on the subset of the motion data samples; and transmitting the compressed high fidelity motion data to a server.