Smart-home system facilitating insight into detected carbon monoxide levels
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Solution Overview
Problem
Existing hazard detectors in smart-home environments often produce false alarms, leading to user frustration and potential safety risks due to their sensitivity to non-hazardous conditions, and they may be disabled to avoid these false alarms, which can result in accidental deaths from undetected hazards like home fires or carbon monoxide poisoning.
Innovation Solution
The development of intelligent, network-connected, multi-sensing hazard detection units that can communicate with each other and a central server to accurately detect hazardous conditions, such as carbon monoxide levels, and automatically control climate control systems to mitigate risks, while also providing user-friendly setup and management features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hazard detectors are made highly sensitive to detect hazardous conditions, then detection capability is improved, but false alarm rate increases
Solution Approach 1:
The hazard detection function is divided into multiple specialized sensors (smoke detector, heat detector, CO detector) distributed throughout the home, each optimized for specific hazard types. The central controller segments the analysis by evaluating data from multiple sensors to distinguish true hazards from false alarm sources.
Solution Approach 2:
A central controller acts as an intermediary between the distributed sensors and the alarm output. It processes sensor data, applies algorithms to distinguish hazardous conditions from benign sources (like shower steam), and coordinates the alarm response, thereby reducing false alarms while maintaining detection sensitivity.
2Area of stationary object
If multiple hazard detectors are installed throughout the home, then detection coverage is improved, but system complexity increases
Solution Approach 1:
Multiple distributed detectors are merged into a unified networked system with a central controller. This allows comprehensive coverage while simplifying user interaction through centralized monitoring and location identification displayed on remote devices.
Solution Approach 2:
The system provides feedback to occupants through remote devices (smartphones, tablets) that display which specific detector is alarming and its location. This feedback loop eliminates the confusion of searching for the alarm source and enables informed decision-making about the hazard.
3Speed
If hazard detectors provide immediate alarm upon detection, then response time is improved, but user stress and false alarm impact increase
Solution Approach 1:
The system performs preliminary analysis of sensor data before triggering an alarm, using algorithms to evaluate whether detected conditions represent true hazards or benign sources. This preliminary action reduces false alarms while maintaining rapid response to genuine threats.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
These smart hazard detectors effectively reduce false alarms, enhance user safety by accurately identifying hazards, and automatically respond to dangerous conditions, such as turning off combustion-based heat sources when elevated carbon monoxide levels are detected, thereby preventing accidents.
Implementation Method 1
measuring a level of CO in the smart-home environment to generate a CO measurement
Data Source
AI summary
In an embodiment, a method determines one or more sources of carbon monoxide (CO) in a smart-home environment that includes a plurality of smart devices that have at least measurement and communication capabilities. The method includes measuring a level of CO in the smart-home environment to generate a CO measurement, and providing the CO measurement and one or more current characteristics of the smart-home environment, from one or more of the smart devices to an analyzing device. The method further includes evaluating, by the analyzing device and with the CO measurement and the current characteristics of the smart-home environment, a set of CO correlation scenarios that attribute generation of CO to a corresponding one of a set of specific sources, and selecting one or more of the specific sources as the most likely source of the CO, by aggregating results of the correlation scenarios.