10 Jun 2021

Artificial Intelligence (AI) is an emerging tool for a long list of applications, including the ability to analyze and ensure optimum performance of an HVAC system. Emerson’s Sensi Predict smart HVAC solution is an example of how AI can boost the capabilities of HVAC. It has been recognized with a Silver Edison Award in the Innovative Services – AI category.

Sensi Predict smart HVAC solution

Sensi Predict combines inputs from 10 sensors in an HVAC system and analyzes the performance of heating and cooling systems in real time. Intelligent monitoring alerts home owners and their contractors, when HVAC systems are not operating at full efficiency.

The alerts, which can be accessed on a smartphone, can predict and prevent problems, ensure corrective maintenance, lower utility costs, and prolong the life of an HVAC system. Fault detection and diagnostics are a new frontier in HVAC technology, delivering a seamless and simple user experience.

Sensi Predict HVAC system configuration

Here is how the Sensi Predict system is configured:

  • Sensors monitor the temperature of the air flowing from the HVAC system into the home, and also the return air temperature, coming from the home back into the system.
  • Sensors also monitor temperatures in the liquid and vapor lines in the refrigerant loop, and the indoor and outdoor control lines, communicating back and forth from the thermostat to the outdoor unit.
  • Other sensors monitor the current draw and indoor voltage of indoor units, and current and voltage to the outdoor units.

Data from the sensors is used to analyze how well the HVAC is operating, including detailed monthly performance checks, with results issued to the home owner and the contractor. If a warning is detected, an alert will be sent in real time.

24/7 monitoring

The 24/7 monitoring is summarized in a personalized home owner portal and monthly performance reports

The 24/7 monitoring is summarized in a personalized home owner portal and monthly performance reports that include any alerts, loss of performance, runtime and estimated cost and filter status. Actionable alerts tell when a problem is detected, sent via an email with a straightforward explanation and recommended action.

Our heating and cooling systems are critical to the health and comfort of our families and the environment, yet we have little visibility into how they perform on a day-to-day basis,” said Jamie Froedge, Executive President of Emerson’s Commercial and Residential Solutions business. The Sensi Predict systems seek to provide additional visibility.

Sharing real-time system insights

The Edison Awards highlight top-tier new product innovation, service development and human-centered design. Named after inventor, Thomas Alva Edison, the awards recognize and honor global innovation.

The award to Emerson’s Sensi Predict system recognizes it as a 21st-century solution to the maintenance of home heating, ventilation and air conditioning systems, sharing real-time system insights, in order to help home owners monitor performance and prevent unexpected problems.

Maximize system lifetime and minimize energy costs

We are honored to be recognized for this innovative technology that provides both awareness and peace of mind, when it comes to an essential component of the home,” said Jamie Froedge.

Sensi Predict also provides benefits related to installation, by validating a quality install and eliminating call backs. Over time, it maximizes system lifetime and minimizes energy costs.

service and maintenance information

In terms of maintenance, the system provides information to ensure that all contractor truck rolls generate revenue and decrease the average time on site. The 24/7 monitoring limits home visits to only when needed and increases transparency to the customer of suggested repairs and upgrades.

Home owners can access the Sensi Predict Homeowner Portal on the official website for detailed information, based on real-time data about how their system is functioning and its performance history, energy usages and costs and predicted maintenance needs.