Power Line Noise Detection for Home Activity Sensing
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Solution Overview
Problem
Existing solutions for detecting electrical device actuation in home settings are either costly, aesthetically unappealing, or require complex installations, and often rely on multiple sensors that increase the risk of failure points and privacy concerns.
Innovation Solution
A system that uses electrical noise monitoring on a power line to detect changes in electrical device states, employing a single plug-in module connected to a computer that analyzes noise patterns using machine learning techniques to identify specific devices and events, such as switching on or off, without the need for extensive sensor deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are deployed to detect electrical device actuation, then detection coverage is improved, but device complexity and installation difficulty increase
Solution Approach 1:
The patent combines multiple sensor functions into a single power line monitoring device that detects electrical device actuation by analyzing voltage changes, current variations, and electrical noise on the power line, eliminating the need for multiple separate sensors throughout the home
Solution Approach 2:
The power line monitoring device serves multiple detection purposes simultaneously, identifying various electrical events such as device switching, plugging/unplugging, and appliance operation states through a single multi-functional system
2Measurement precision
If multiple sensors are installed throughout the home, then activity detection capability is improved, but installation time and maintenance effort increase
Solution Approach 1:
The system merges the functionality of multiple distributed sensors into a single centralized power line monitoring device, reducing installation from requiring multiple sensor placements to simply plugging in one device into a power outlet
Solution Approach 2:
The system automatically detects and identifies electrical events without requiring manual configuration or calibration, performing self-service detection and classification of appliance operations through automated signal analysis
3Measurement precision
If high-fidelity sensors are used to capture detailed activity information, then measurement accuracy is improved, but cost and system complexity increase
Solution Approach 1:
The patent replaces complex mechanical sensor systems with electrical signal analysis, using voltage, current, and noise measurements on the power line to infer mechanical events such as switch actuation and appliance operation
Solution Approach 2:
The system changes the measurement parameters from direct physical sensing to electrical parameter monitoring, analyzing voltage transients, current harmonics, and electrical noise characteristics to detect device actuation events
Data Source
AI summary
Activity sensing in the home has a variety of important applications, including healthcare, entertainment, home automation, energy monitoring and post-occupancy research studies. Many existing systems for detecting occupant activity require large numbers of sensors, invasive vision systems, or extensive installation procedures. Disclosed is an approach that uses a single plug-in sensor to detect a variety of electrical events throughout the home. This sensor detects the electrical noise on residential power tines created by the abrupt switching of electrical devices and the noise created by certain devices while in operation. Machine learning techniques are used to recognize electrically noisy events such as turning on or off a particular light switch, a television set, or an electric stove. The system has been tested to evaluate system performance over time and in different types of houses. Results indicate that various electrical events can be learned and classified with accuracies ranging from 85-90%.