Building Utilization System for Dynamic Coworker Clustering
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Solution Overview
Problem
Traditional building management systems struggle to efficiently allocate resources and optimize space usage in hybrid work environments, where occupancy is unpredictable and varies significantly over time.
Innovation Solution
A building utilization system that uses location sensing and occupant identity data to dynamically cluster coworkers, control access, and optimize resource usage in real-time, incorporating sensors such as biometrics, GPS, and environmental sensors to monitor and adjust lighting, temperature, and IT resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional building management systems are used, then system simplicity is maintained, but resource allocation efficiency deteriorates in hybrid work environments
Solution Approach 1:
The building management system integrates multiple functions including occupancy detection via sensors, dynamic workspace allocation, access control, and environmental control into a single unified platform. This multi-functional approach improves resource allocation efficiency across different building areas while managing system complexity through integration rather than separate systems.
Solution Approach 2:
The system dynamically adjusts workspace assignments and environmental settings based on real-time occupancy data and predicted usage patterns. Workspaces are not statically assigned but dynamically allocated to match actual building usage, improving productivity while the automated nature of this dynamic adjustment manages the complexity through algorithmic control.
2Productivity
If static workspace assignments are used, then ease of operation is maintained, but space utilization efficiency deteriorates
Solution Approach 1:
The system automatically detects occupancy through sensors and autonomously assigns workspaces without requiring manual intervention from employees or facility managers. This self-service approach optimizes space utilization by matching actual usage patterns while eliminating the operational complexity of manual workspace management for users.
Solution Approach 2:
The system continuously monitors occupancy data from sensors and uses this feedback to dynamically adjust workspace assignments. This closed-loop feedback mechanism improves space utilization efficiency by responding to actual building usage while the automated feedback processing manages operational simplicity for end users.
3Loss of energy
If dynamic sensor-based control is implemented, then resource optimization is improved, but device complexity increases
Solution Approach 1:
The sensor system performs multiple functions including occupancy detection, environmental monitoring, and triggering automated responses for lighting and HVAC control. This multi-functionality reduces energy consumption across multiple building systems while managing sensor complexity through integrated processing rather than separate control systems.
Solution Approach 2:
The sensor-based system automatically detects occupancy and autonomously controls environmental settings without requiring manual intervention. This self-service approach optimizes energy consumption by matching environmental control to actual usage while the automated control logic manages the complexity of coordinating multiple sensors and actuators.
4Loss of time
If manual building management is used, then system complexity is minimized, but time efficiency deteriorates
Solution Approach 1:
The system pre-assigns workspaces based on predicted occupancy patterns and prepares environmental settings in advance of actual usage. This preliminary action reduces the time required for resource allocation while the automated prediction and assignment algorithms manage the complexity of coordinating multiple building systems.
Solution Approach 2:
The building management system autonomously performs resource allocation and environmental control without manual intervention, dramatically reducing the time required for these operations. The automated self-service approach manages operational complexity through integrated control algorithms that coordinate sensors, workspace assignments, and environmental systems.
Data Source
AI summary
Aspects of the present disclosure include techniques for building utilization. In one example, a method includes receiving, via one or more sensors, a first sensor data indicating a work area of a first individual within a building, and receiving, via the via the one or more sensors, a second sensor data indicating a second individual entering the building. The method additionally include accessing stored data from a data store indicating the existence of a team affiliation between the first individual and the second individual, and calculating a cluster area encompassing the work area of the first individual. The method also includes assigning a second work area to the second individual, wherein second work area is disposed within the cluster area, continually monitoring, via the one or more sensors, a plurality of locations for a plurality of individuals entering the building, and assigning work areas to the plurality of the individuals.