Home Automation Proximity Authorization for Notification Management
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Solution Overview
Problem
Home automation systems often generate 'false positive' notifications due to authorized individuals, leading to information fatigue and potential missed important alerts, as they cannot distinguish between familiar and unfamiliar persons based on proximity.
Innovation Solution
Implementing a system that uses facial recognition and proximity analysis to grant temporary authorization levels to unknown persons based on their physical or temporal proximity to authorized users, thereby suppressing unnecessary notifications and adjusting home automation device operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the home automation system sends notifications for all detected motion, then important security alerts are not missed, but users experience information fatigue and annoyance from false positive notifications
Solution Approach 1:
The system applies different notification rules based on the identity and authorization level of each detected person. Authorized users receive different treatment compared to unauthorized persons, with notification suppression applied selectively to reduce false positives while maintaining security alert reliability
Solution Approach 2:
The system changes the authorization level parameter dynamically based on proximity detection. When an unknown person enters a proximity zone near an authorized user, their authorization level is temporarily upgraded, which triggers different notification behavior - reducing unnecessary alerts while maintaining security monitoring
2Object-generated harmful factors
If the system grants temporary authorization to unknown persons based on proximity, then false positive notifications are reduced, but the system complexity increases due to proximity analysis requirements
Solution Approach 1:
The system pre-defines proximity zones around authorized users and pre-establishes authorization level upgrade rules. When an unknown person enters these pre-configured zones, the authorization change is automatically triggered without requiring complex real-time analysis, thereby reducing system complexity while maintaining effectiveness
Solution Approach 2:
The system introduces a proximity zone as an intermediary mechanism between motion detection and authorization level changes. This intermediary layer simplifies the decision-making process by providing clear spatial boundaries that trigger automated responses, reducing the need for complex judgment logic
3Measurement precision
If facial recognition is performed on all persons in video streams, then accurate identification is achieved, but system processing time and resource consumption increase
Solution Approach 1:
The system performs facial recognition selectively rather than on all detected persons. Unknown persons who enter proximity zones trigger facial recognition and authorization level updates, while already-identified authorized users do not require repeated analysis. This partial application of facial recognition reduces processing time and resource consumption while maintaining identification accuracy when needed
Data Source
AI summary
Various arrangements for determining and setting an authorization level for an unknown person are presented. Facial recognition may be performed on a received video stream. An authorized user may be recognized in the video feed. Additionally, an unknown person may be identified in the video feed. A provisional authorization level may be granted for the unknown person based on proximity between the unknown person and the authorized user in the received video stream.