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The case for and against the use of thermal imaging for traffic management

The case for and against the use of thermal imaging for traffic management

When used in conjunction with other sensors in a comprehensive traffic management system, thermal imaging sensors, such as thermal cameras, have a lot to offer in terms of accuracy and efficiency. However, despite its many benefits, not all companies believe it is the right technology for the job.

Why Use Thermal

One of the biggest draws of thermal imaging cameras across sectors is their ability to “see” in the dark and inclement weather. They can also measure the temperature of any object in their field of view, allowing them to detect fires at an early stage over the full detection range.

“This unlike other fire detection technologies requires no contact with flames or heated gasses, nor is any smoke propagation needed for the camera to detect excessive heat generated by fire or another vehicle malfunction,” explained Michael Deruytter, Director of Innovation at FLIR Intelligent Transportation Systems. “An additional benefit of thermal imaging is that this technology enables operators to see through smoke. This can be a life-saving feature in smokefilled tunnels and can provide valuable information to firefighting teams about the possible location of people.”

Deruytter further explained that because thermal imaging cameras do not make use of visible light, but rely on thermal radiation or heat given off by everything in their field of view, they do not get confused by sun glare, darkness, headlights, shadows, wet streets, snow or fog. This makes them an ideal component of a 24/7 traffic monitoring solution.

Visible-Light Versus Thermal for Traffic Management

Visible-light cameras have historically been very popular for traffic monitoring. This, according to Deruytter, is because when a traffic event occurs, it provides immediate feedback to an operator in the traffic management center to take futher actions. However, since visible cameras are dependent on the light reflected by objects to produce an image, the reliability of their performance and capacity to detect is extremely sensitive to outside light conditions.

“The majority of cameras used in video surveillance or traffic management are sensitive to light in the visible spectrum, typically 0.4 to 0.8 μm wavelength or up to 1.0 for cameras sensitive in the near infrared. Visible cameras are limited to detecting only those objects exposed to sunlight or an external light source, such as street lighting,” explained Emmanuel Bercier, Strategic Marketing Manager at ULIS.

“Whether an object is human, an animal, a vehicle, a road or tree, it will emit heat energy depending on two elements: its inherent temperature and its material substance. All objects above zero kelvins radiate heat emitted in the far infrared spectral bandwidth 8 to 12μm. Thermal imaging cameras are based on a technology that is sensitive in far infrared spectrum, which means they are only sensitive to the light directly emitted by an object,” he added.

Thus, thermal imaging cameras are able to provide constant visibility and reliable object detection, 24/7, whatever the light, atmospheric or environmental conditions, such as fog or smoke. As such, thermal cameras are well suited for traffic management which is subject to the ever-changing nature of outside elements.

Dissenting Opinion on Thermal Use in Traffic Management

Thermal imaging technology is being used more and more for traffic management, but its use doesn’t necessarily mean it is the best fit. In fact, Daniel Chau, Overseas Marketing Director at Dahua Technology, explained why thermal imaging cameras are not Dahua’s recommended products for traffic management. The company, which has its own line of thermal imaging cameras, mainly applies its products in perimeter protection, forest fire detection and monitoring of high-voltage power transformer substations.
Daniel Chau,
Overseas Marketing Director,
 Dahua Technology

Chau notes that the key advantage of thermal cameras in traffic management is the higher accuracy rate in counting passing vehicles; however, the 5- to 10-percent improvement rate is marginal when compared to good visible-light cameras with artificial intelligence (AI)analytics. Furthermore, it does not bring “material value to the outcome of traffic management.”

“AI and deep learning are enabling visible-light imaging surveillance solutions to recognize vehicle details such as car color, plate number, make, model and use of seat belt. This information could bring significant value to traffic management by understanding the composition of traffic at different times of day,” Chau explained.

“The advantage of thermal cameras does not justify its higher price nor its lack of intelligent recognition and analytics capabilities, thus thermal cameras are not widely applied in traffic management,” he added. Instead, Chau believes AI and deep-learning-powered visible-light imaging surveillance that can deliver advanced analytics function such as video synopsis, human recognition and vehicle recognition are more suitable for traffic management than thermal imaging surveillance.

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