Space utilization patterns for building optimization
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Solution Overview
Problem
Existing methods lack an efficient and effective way to identify and manage space utilization within buildings, leading to suboptimal resource allocation and maintenance schedules.
Innovation Solution
A method that utilizes occupancy sensors to track space usage over time, calculates occupancy and utilization values, and adjusts building operations based on these metrics to optimize space utilization and maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If occupancy sensors are deployed throughout the building to track space usage, then space utilization data accuracy is improved, but device complexity and implementation cost increase
Solution Approach 1:
The building is divided into multiple zones with occupancy sensors deployed in each zone rather than every single space. This segmentation approach provides sufficient space utilization data for building optimization while reducing the total number of sensors required, thereby lowering implementation complexity and cost.
Solution Approach 2:
The occupancy sensors are designed to serve multiple functions: tracking occupancy for space utilization analysis, providing data for maintenance scheduling, and supporting building operations optimization. This multi-functionality reduces the need for separate systems, thereby reducing overall device complexity while maintaining measurement precision.
2Ease of operation
If detailed occupancy tracking is implemented across all spaces, then space utilization management is improved, but loss of time for data processing increases
Solution Approach 1:
The system pre-calculates and stores occupancy metrics such as average occupancy, peak usage times, and utilization patterns during off-peak periods. This preliminary processing allows for rapid retrieval and analysis of space utilization data when making operational decisions, thereby reducing data processing time while maintaining effective space utilization management.
Solution Approach 2:
The system automatically processes and analyzes occupancy data without requiring manual intervention. The building management system autonomously generates utilization reports, identifies optimization opportunities, and recommends operational changes, thereby reducing the time loss associated with manual data processing while improving ease of operation.
3Productivity
If utilization values are calculated and used to adjust building operations, then productivity and resource allocation are improved, but device complexity increases
Solution Approach 1:
The system calculates utilization values based on simple parameters such as occupancy duration and frequency rather than complex multi-dimensional metrics. By focusing on key parameters that directly impact building operations, the system achieves improved productivity through data-driven decisions while minimizing the complexity of data processing algorithms.
Data Source
AI summary
Occupancy data over time is received for each of several spaces within a building from occupancy sensors that are disposed within each of the spaces. An occupancy value is determined for each of at least some of the several spaces based on the received occupancy data, each occupancy value representative of a percent of time that the respective space was occupied over an identified period of time. The space that had a highest occupancy value over the identified period of time is identified. A utilization value is determined for each of the spaces, wherein the utilization value is representative of a ratio of the occupancy value of the respective space and the highest occupancy value. An operation of the building is changed based at least in part on the utilization value of at least one of the plurality of spaces.