User Presence Detection via Multi-Process Voting
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Solution Overview
Problem
Existing systems fail to accurately and efficiently detect a user's current location, identity, and direction within multiple spaces, such as home and office environments, due to limitations in calibration processes and reliance on signal strength and device orientation.
Innovation Solution
The system employs multiple processes, including lag and reactive techniques, to determine user location by analyzing RSSI data, accelerometer data, and user device orientation, using a presence engine that combines votes from various techniques to enhance accuracy and reliability, and adjusts terminal device settings based on user location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple processes and techniques are used to determine user location, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system divides user location detection into multiple independent processes (lag technique, reactive technique, RSSI-based process, accelerometer-based process) that operate separately and contribute votes to the final determination. Each process handles specific aspects of location detection, improving overall precision while maintaining modular complexity management.
Solution Approach 2:
The system merges results from multiple independent location detection processes through a voting mechanism. Each process generates a location result with an associated confidence level, and the final user location is determined by evaluating and combining these weighted votes, achieving high precision through ensemble decision-making.
2Measurement precision
If calibration is performed for multiple spaces, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs calibration in advance for multiple spaces, storing baseline RSSI values and terminal device locations during an initial calibration phase. This preliminary action enables accurate location detection without requiring real-time calibration, reducing time loss during actual usage while maintaining high measurement precision.
3Measurement precision
If monitoring of RSSI data and accelerometer data is performed continuously, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system implements periodic monitoring of RSSI data and accelerometer data at defined intervals rather than continuous monitoring. The presence engine evaluates location results at periodic intervals, adjusting monitoring frequency based on user activity states, which maintains measurement precision while significantly reducing energy consumption compared to continuous monitoring.
Solution Approach 2:
The system dynamically adjusts the intensity of data monitoring based on detected user states. When user motion is detected, monitoring frequency increases to maintain precision; when user is stationary, monitoring intensity decreases to conserve battery energy, optimizing the balance between measurement precision and energy usage.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for presence determination. Systems can include one or more user devices and terminal devices. A current location may be determined of a user that is associated with a particular space of a plurality of different spaces. A plurality of location results may be calculated, wherein each location result is computed using a distinct process of a plurality of processes; and evaluating the plurality of location results to determine a current space of the user; wherein the determining is performed by one or more of, a particular user device, a terminal device, or a server system.