Distributed Sensor Networks for HVAC Filter and Performance Monitoring
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Solution Overview
Problem
Current sensing technologies in HVAC systems lack comprehensive monitoring capabilities to efficiently detect filter replacement needs, balance HVAC operations, identify performance issues, and adjust operations based on occupancy and environmental data, leading to suboptimal performance and maintenance inefficiencies.
Innovation Solution
A distributed sensor network system that includes pressure, temperature, motion, and occupancy sensors to monitor air pressure across furnace filters, balance HVAC operations by adjusting vent statuses, and identify issues with HVAC components, while also adjusting climate control operations based on user behavior and environmental data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If distributed sensor networks are implemented to monitor HVAC systems, then monitoring precision and system reliability are improved, but device complexity increases
Solution Approach 1:
The HVAC monitoring system is divided into multiple independent sensor nodes distributed throughout the system. Each sensor monitors specific parameters (temperature, pressure, occupancy) locally, and results are aggregated by a controller. This segmentation enables precise localized monitoring without requiring a single complex centralized system.
Solution Approach 2:
The sensor network uses standardized multi-functional sensor nodes that can monitor various HVAC parameters. These universal sensors can detect temperature, pressure, and occupancy, and communicate through standard protocols, reducing overall system complexity while maintaining high monitoring precision across different locations.
2Productivity
If multiple sensors are deployed to monitor air pressure, temperature, and occupancy, then HVAC performance optimization is improved, but manufacturing cost increases
Solution Approach 1:
Multiple sensing functions (temperature, pressure, occupancy detection) are merged into integrated sensor nodes. By combining these functions in single units rather than deploying separate sensors for each parameter, the system achieves comprehensive HVAC optimization while reducing the total component count and manufacturing complexity.
Solution Approach 2:
The sensor network operates autonomously, with sensors continuously monitoring parameters and the controller automatically adjusting HVAC operations based on collected data. This self-service capability optimizes HVAC performance in real-time without requiring manual intervention or complex external control systems, reducing operational and maintenance costs.
3Reliability
If real-time sensor data is processed to identify HVAC problems, then system reliability is improved, but energy consumption increases
Solution Approach 1:
The sensor network performs periodic monitoring and data processing at intervals rather than continuously. Sensors collect data at regular cycles, and the controller processes this information periodically to identify HVAC problems. This periodic operation maintains system reliability by detecting issues timely while significantly reducing energy consumption compared to continuous real-time processing.
Data Source
AI summary
Methods and systems for monitoring multiple sensors over a distributed sensor network to enhance various monitoring operations. In some implementations, an identification of a sensor located in a property and a token that enables the mobile device to obtain data from the sensor are each received by a mobile device from a server. The mobile device is then determined to be within a communication range with the server that is indicated by the identification from the server. In response, data is obtained from the sensor by the mobile device using the token received from the server.