Not Too Hot, Not Too Cold: An Automatic Climate Control System

Using remote heat-sensing, researchers are creating a system that autonomously controls the temperature within cars and homes

3 min read
Tracking thermal faces
The detection and tracking processes of interesting points, which are usually located where there are sharper changes in temperatures.
Image: Mohamed Abouelenien/IEEE

Many drivers are familiar with the irritation of being stuck in traffic on a sweltering summer day. Two researchers at the University of Michigan are working to make uncomfortable situations like this a bit more bearable, by developing a system that will automatically control the climate within a car to optimize both the passengers’ comfort level and the efficiency of the HVAC system.

Over the past few years, Mohamed Abouelenien and Mihai Burzo have been developing approaches to analyze and detect various human behaviors, including lying, feeling stressed, remaining alert at the wheel, and expressing affection, among others. Their latest effort has been to develop a system for cars and homes that automatically detects a person’s thermal discomfort and adjusts accordingly, without any human input.

Abouelenien says there are multiple benefits of such a system that extend beyond creating a comfortable environment for passengers. Notably, raising temperatures by just a few degrees Celsius can result in energy savings and increase the efficiency of HVAC systems, he says. “More importantly, a driver with a thermally comfortable sensation will be less stressed, less fatigued, and more alert, which results in safer driving conditions for the vehicle’s occupants as well as for pedestrians.”

But what temperature yields the best comfort level? At a laboratory at the University of Michigan, the researchers had 50 participants sit in a thermally controlled enclosure while they were exposed to air temperatures ranging between 16 degrees Celsius (61 degrees Fahrenheit) and 35 degrees C (95 degrees F). Participants rated their comfort levels as a remote heat-sensing tool and four types of contact-based physiological sensors collected data describing their heart rate, skin temperature, respiration rate, and skin conductance.

The experimental station including an insulating enclosure, physiological sensors, and thermal cameras.The experimental station includes an insulating enclosure, physiological sensors, and thermal cameras.Photos: Mihai Burzo/IEEE

From the thermal imaging data, the researchers segmented participants’ faces, identified interesting points for tracking, and then contrasted thermal maps of each face. Using this data and a total of 59 physiological features captured by the four contact sensors, they applied machine learning algorithms to automatically detect the thermal sensation of the participants. Then they introduced a cascaded machine learning system that further detected different levels of hot and cold discomfort.

Their results show that thermal imaging was sufficient in detecting the discomfort levels of the study participants—but the efficiency of detection was increased by 18.5 percent when the other physiological features are accounted for.

Drivers, however, are probably not interested in wearing the contact sensors while they commute. Now, Abouelenien and Burzo are working on extracting the physiological factors from the thermal images, which could lead to a fully non-contact detection system. They say several companies have expressed interest in this technology.

This recent work, published in IEEE Intelligent Systems on 30 August, also reveals some interesting insights into temperature comfort. “The time duration needed to reach a certain level of cold discomfort is approximately double that is needed (to reach) the hot sensation, which indicates that human bodies have faster adaptation to heat,” Abouelenien says. He also notes that while he expected the skin temperature sensors to be one of the more reliable indicators of discomfort, in some cases the heart rate features were a more accurate indicator of discomfort.

Besides developing the system to be fully non-contact, the researchers plan to explore other thermal comfort factors such as humidity, clothing level, and metabolic rate. They are also faced with the challenge of adapting this technology so that it accounts for multiple passengers or inhabitants.

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We Need More Than Just Electric Vehicles

To decarbonize road transport we need to complement EVs with bikes, rail, city planning, and alternative energy

11 min read
A worker works on the frame of a car on an assembly line.

China has more EVs than any other country—but it also gets most of its electricity from coal.

VCG/Getty Images
Green

EVs have finally come of age. The total cost of purchasing and driving one—the cost of ownership—has fallen nearly to parity with a typical gasoline-fueled car. Scientists and engineers have extended the range of EVs by cramming ever more energy into their batteries, and vehicle-charging networks have expanded in many countries. In the United States, for example, there are more than 49,000 public charging stations, and it is now possible to drive an EV from New York to California using public charging networks.

With all this, consumers and policymakers alike are hopeful that society will soon greatly reduce its carbon emissions by replacing today’s cars with electric vehicles. Indeed, adopting electric vehicles will go a long way in helping to improve environmental outcomes. But EVs come with important weaknesses, and so people shouldn’t count on them alone to do the job, even for the transportation sector.

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