Security System Mode Selection via Occupancy Estimation
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Solution Overview
Problem
Current security systems require manual user input to change modes, leading to unnecessary alerts or failure in detecting intruders due to improper mode settings, as they rely on users to set the system to the correct mode based on their presence or absence.
Innovation Solution
A system that automatically changes the security mode by receiving signals from sensors, using an occupancy model and mode rules to determine the appropriate mode without user input, allowing for automatic or authorized changes based on occupancy estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual user input is required to change security modes, then user control over security settings is maintained, but the system may fail to detect intruders or generate unnecessary alerts due to improper mode settings
Solution Approach 1:
The system automatically determines occupancy status using sensor data and machine learning models, then autonomously selects and switches security modes without requiring manual user input. The system serves itself by making intelligent decisions based on environmental data, eliminating the need for users to manually configure security settings while maintaining reliable security detection.
Solution Approach 2:
The system continuously monitors sensor data from the environment, processes this information through occupancy models, and uses the feedback to dynamically adjust security modes. This closed-loop feedback mechanism ensures the security system adapts to current conditions, maintaining high reliability without manual intervention.
2Productivity
If automatic mode changes are implemented without user input, then unnecessary alerts are reduced and detection capabilities improve, but user control and authorization over security changes are lost
Solution Approach 1:
The system performs preliminary analysis of sensor data and occupancy status before automatically changing security modes. By pre-processing environmental information and predicting occupancy states, the system can make informed mode transitions proactively, improving responsiveness while maintaining appropriate security levels through advance preparation and validation.
Data Source
AI summary
Systems and techniques are provided for automatic security system mode selection. A set of signals may be received from sensors distributed in an environment with a security system. The security system may be in a first mode. An occupancy model may be received. An occupancy estimate may be generated for the environment based on the set of signals from the sensors and the occupancy model. Mode rules may be received. The mode rules associate occupancy estimates with modes of the security system. A second mode for the security system may be determined based on the occupancy estimate and mode rules. The second mode may be different from the first mode. The mode of the security system may be automatically changed from the first mode to the second mode.