Smart Home AR Hazard Warnings via Sensor Fusion
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Solution Overview
Problem
Household accidents are a significant cause of death and injury in the United States, largely due to hazardous conditions that are often not identified or addressed, and existing technologies for providing warnings are either ineffective in preventing accidents or annoying to users, leading to frustration and disregard.
Innovation Solution
A smart home management system (SHMS) that uses sensors to identify objects and humans in a environment, determines potential hazardous conditions, and generates augmented reality warnings selectively to prevent accidents by providing predictive analysis and sparingly delivering warnings to avoid user annoyance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If warnings are constantly provided to users about hazardous conditions, then user safety is improved, but user annoyance increases leading to service disregard
Solution Approach 1:
The system dynamically adjusts warning provision based on real-time analysis of hazard likelihood and user context. Rather than constant warnings, the system adapts its behavior to provide warnings only when predictive analysis indicates a hazardous condition is likely to occur, thereby maintaining safety while reducing user annoyance
Solution Approach 2:
The system changes the parameter of warning frequency based on the assessed probability of hazardous conditions. By modifying this parameter dynamically according to environmental sensors, object classifications, and human proximity data, the system optimizes the balance between safety assurance and user acceptance
2Reliability
If home inspectors identify hazardous conditions at purchase, then initial safety is improved, but conditions are not rechecked for decades allowing dynamic hazards to develop
Solution Approach 1:
The system performs preliminary identification and classification of objects in the environment, establishing a baseline inventory of potential hazards. This preliminary action enables continuous monitoring without requiring full re-inspection, allowing the system to detect dynamic hazardous conditions that develop over time
Solution Approach 2:
Rather than periodic inspections with gaps in between, the system maintains continuous useful action through persistent environmental scanning and object classification. Sensors continuously monitor for changes in the environment, ensuring that dynamic hazardous conditions are detected as they materialize rather than waiting for the next scheduled inspection
3Difficulty of detecting and measuring
If augmented reality warnings are provided frequently, then hazard detection is improved, but user frustration increases causing service shutdown
Solution Approach 1:
The system applies partial action by providing augmented reality warnings only for hazardous conditions that meet a certain probability threshold. Rather than warning for all detected conditions, it selectively applies warnings to those most likely to materialize, maintaining effective hazard detection while minimizing user frustration from false or low-risk alerts
Data Source
AI summary
Systems and methods are described for identifying, using a sensor, a location of an object in an environment, and determining a classification of the object. A human may be identified in proximity with the object, an identity of the human may be determined, and a determination may be made that a hazardous condition may occur, based on a combination of the location of the object, the classification of the object, and the identity of the human in proximity with the object. In response to determining that the hazardous condition may occur, an augmented reality scene associated with the potentially hazardous condition associated with the object may be generated for presentation, at a user device.