Outlet-Level Occupancy Detection for Building Energy Management
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Solution Overview
Problem
Existing building utility management systems lack efficient methods to dynamically adjust heating and cooling based on real-time occupancy patterns, leading to inefficient energy usage and comfort issues.
Innovation Solution
A system comprising smart thermostats, electricity monitors, and a cloud-based service that uses machine learning and sensor data to model occupancy, adjust temperature settings, and optimize energy usage by classifying and tracking occupied seats, incorporating weather forecasts and user reports for precise control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If building utility management systems use traditional monitoring methods at the building level, then the system structure is simple, but the occupancy detection precision and real-time control capability are insufficient
Solution Approach 1:
The patent segments the building into multiple zones with individual thermostats and electricity monitors, and further segments monitoring to the outlet level with seat classification. This hierarchical segmentation enables precise occupancy detection at each level while maintaining overall system manageability, resolving the contradiction between precision and complexity.
Solution Approach 2:
The patent adds a spatial dimension to traditional building-level monitoring by implementing zone-level and outlet-level monitoring. This dimensional expansion from building → zone → outlet hierarchy enables precise occupancy detection without overwhelming system complexity, as each level operates semi-independently.
2Reliability
If the system continuously monitors and adjusts temperature settings for all areas, then occupancy comfort is improved, but energy consumption increases
Solution Approach 1:
The patent applies partial action by monitoring and adjusting temperature only in occupied zones and outlets rather than continuously monitoring all areas. The seat classification system enables targeted control where occupancy is detected, avoiding unnecessary energy consumption in unoccupied areas while maintaining comfort where needed.
Solution Approach 2:
The system uses periodic occupancy detection through electricity monitor readings and adjusts temperature settings based on detected occupancy patterns. This periodic rather than continuous adjustment reduces energy consumption while maintaining reliability by responding to actual occupancy changes.
3Productivity
If the system uses detailed seat classification and tracking, then energy optimization precision is improved, but device complexity increases
Solution Approach 1:
The patent applies local quality by classifying seats into different types (e.g., workstation seats, meeting room seats, common area seats) with different occupancy patterns and energy optimization strategies. Each seat type receives tailored monitoring and control, improving energy optimization precision without requiring complex centralized control of all seats uniformly.
Data Source
AI summary
Smart electricity monitors with unique identities placed at individual power outlets within a building communicate frequent power measurements to a service which determines, from this power usage data, which outlets are associated with occupied seats within the building. This occupancy information can be used to update an occupancy model for the building that is used to forecast the building's occupancy. Based on present occupancy, projected occupancy, and other data, in some instances, the building's thermostats can be controlled and unoccupied seats can be assigned dynamically.