Monday, January 25, 2016: 11:00 AM-12:00 PM
Cutting-Edge Technologies
Chair:
Stephen Roth, P.E., Carmel Software Corp.
Technical Committee: 01.05 Computer Applications
CoSponsor: 07.03 Operation and Maintenance Management
This seminar discusses how the Internet of Things (IoT), which has been popularized by consumer devices such as fitness trackers, can be applied to HVAC maintenance and operations. Specifically, this seminar focuses on how light-weight sensors can easily be installed inside HVAC rooftop units to measure a wide variety of conditions and how these sensors can better aid in fault detection and diagnose equipment issues. This seminar also focuses on how much of the data from these sensors is being collected by remote, “cloud-based” databases so it can be further analyzed by mobile-based applications.
1 Using Simple Internet-Connected Sensors to Monitor HVAC Equipment
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Janet Peterson, Western HVAC Performance Alliance / CQM-180 |
Light-weight, Internet-connected sensors are able to better monitor HVAC equipment, including economizers. Why maintaining economizers are the low-hanging fruit for improving rooftop unit energy efficiency and why over 50% of economizers are not functioning properly. How Internet-connected HVAC sensors with fault-detection and other diagnostic capabilities are able to better monitor economizer usage and aid in both installation and maintenance. What is being done with all of the data provided that is being transmitted to the "cloud" by these Internet-connected sensors?
2 Using Mobile Apps to Conduct HVAC Maintenance and Operations
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Stephen Roth, P.E., Carmel Software Corp. |
Mobile software applications can work with Internet-enabled HVAC sensors to help HVAC technicians better install and maintain them. This paper shows how mobile apps can help technicians install Internet-enabled airflow, temperature, pressure, and other types of sensors. A step-by-step installation process shows how mobile apps can aid in fault detection and diagnose issues with HVAC equipment based upon data received from the sensors and mobile apps can better aid technicians in addressing these issues by displaying a decision-tree user interface.