Controlling parameters in a building
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Solution Overview
Problem
Homeowners face inefficiencies and costs due to the need to manually adjust thermostat settings when away, leading to discomfort upon return, as current systems lack reliable occupancy detection for automated adjustments in heating and lighting.
Innovation Solution
A system utilizing multiple sensors (such as motion detectors, video cameras, and mobile devices) to generate a predictive occupancy schedule, adjusting building parameters like temperature and lighting based on reliability scores, ensuring energy conservation when unoccupied and comfort when occupied.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the thermostat is manually adjusted to a lower temperature when the home is unoccupied, then energy costs are reduced, but the home temperature becomes uncomfortable for the homeowner upon return
Solution Approach 1:
The system performs preliminary action by predicting the homeowner's return time using sensor data and occupancy patterns, then proactively adjusting the thermostat to comfortable temperature levels before the homeowner actually returns home, eliminating the need for manual readjustment
Solution Approach 2:
The system implements feedback by continuously monitoring occupancy sensors, door events, and environmental data to dynamically adjust thermostat settings based on real-time and predicted occupancy status, ensuring energy efficiency when unoccupied while maintaining comfort when occupied
2Reliability
If multiple sensors are used to determine occupancy and generate reliability scores, then occupancy detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system applies segmentation by dividing the sensor network into modular components, each responsible for specific detection functions (motion, presence, door events), with independent reliability scoring that can be evaluated and weighted separately to improve accuracy without creating monolithic complexity
Solution Approach 2:
The system uses parameter changes by dynamically adjusting sensor sensitivity thresholds, detection ranges, and reliability weightings based on environmental conditions and historical performance data, allowing the system to adapt to different scenarios while maintaining manageable complexity through standardized adjustment mechanisms
Data Source
AI summary
Methods and systems are described for controlling parameters in a building. According to at least one embodiment, a method for controlling parameters in a building includes using a first sensor type to determine whether the building is occupied and using a second sensor type to determine how reliable the first sensor type determines occupancy.