Environmental conditioning system and method for conditioning environment of occupiable region
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing building management systems rely on manually inputted occupancy data for environmental conditioning, which is inefficient and does not accurately predict occupancy patterns, leading to unnecessary energy consumption.
Innovation Solution
An environmental conditioning system with a controller that processes ingress and egress data using rolling means and thresholds to dynamically adjust HVAC operations, optimizing energy usage based on predicted occupancy levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If environmental conditioning systems operate continuously to maintain high comfort standards, then occupancy comfort is improved, but energy consumption increases substantially
Solution Approach 1:
The system dynamically adjusts HVAC operations based on real-time occupancy detection and historical pattern analysis. Instead of continuous operation, the system adapts conditioning intensity and timing to match actual occupancy levels, resolving the contradiction between maintaining comfort and reducing energy consumption
Solution Approach 2:
The system uses occupancy sensors and historical data feedback to continuously optimize conditioning schedules. By monitoring actual occupancy patterns and adjusting operations accordingly, the system maintains comfort standards while eliminating energy waste from conditioning empty spaces
2Use of energy by moving object
If HVAC systems are preprogrammed to start and shut down at prescribed times based on expected occupancy, then energy costs are reduced, but occupancy prediction accuracy deteriorates due to manual data input limitations
Solution Approach 1:
The system automatically collects occupancy data through sensors and uses machine learning algorithms to generate prediction schedules without manual intervention. This self-service approach eliminates the inaccuracies of manual data input while maintaining energy cost reduction benefits through automated optimization
Solution Approach 2:
The system replaces manual data input methods with automated sensor-based occupancy detection and computational algorithms. This substitution of mechanical/manual processes with electronic sensing and processing dramatically improves prediction accuracy while maintaining energy efficiency
3Reliability
If environmental conditioning systems operate at full capacity to ensure comfort, then occupancy comfort is maintained, but energy efficiency deteriorates
Solution Approach 1:
The system applies conditioning selectively based on detected occupancy locations and densities. Instead of uniform full-capacity operation throughout the facility, conditioning is localized to occupied zones with intensity matched to actual needs, maintaining comfort where required while eliminating waste in unoccupied areas
Solution Approach 2:
The system applies partial conditioning action proportional to actual occupancy levels rather than full capacity operation. By scaling conditioning intensity to match occupancy density and presence, the system maintains adequate comfort standards while dramatically improving energy efficiency
Data Source
AI summary
An environmental conditioning system for conditioning the environment of an occupiable region includes environmental conditioning hardware and a controller. The controller includes an occupancy module configured to receive ingress data associated with occupants entering the occupiable region for each of a first plurality of ingress iterations of a first prescribed time period. The controller further performs a first ingress rolling mean of the ingress data over the first plurality of ingress iterations, and compares at least the first ingress rolling mean to a first occupancy threshold. If the first occupancy threshold is exceeded by the first ingress rolling mean, the controller outputs a start command to the environmental conditioning hardware.