7 Top Applications for Computer Vision on the Edge

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Edge computing is reshaping the landscape of computer vision, moving to an era of enhanced perception and intelligent decision-making right at the device level.

Edge computing is driving computer vision into a new era of intelligent systems, smart devices, and immersive experiences. The benefits of edge computing, including faster processing, greater security, and real-time insights, make it a critical tool for computer vision applications.

Edge computing enhances computer vision by enabling super-fast processing and analysis right on devices, such as sensors, mobile phones, and cameras, without the need for cloud-based servers.

From smart cars to warehouse robots to smart home digital assistants, billions of edge computing devices are being deployed in the market, and they’re only getting more advanced with time thanks to developments in artificial intelligence (AI) and machine learning (ML), says Mark Hoopes, director of automotive and industrial segment marketing at Lattice Semiconductor.

“Edge processing is becoming more essential amid the rise of AI. In particular, the automotive industry has been rapidly implementing AI-based computer vision that enables machines to interpret and understand visual data around them.”

There has been a big uptick in interest in critical applications for computer vision on the edge, particularly over the past 12 months, says Rudy de Anda, head of strategic alliances at Stratus Technologies Inc., a provider of edge computing platforms.

Daniel Situnayake, head of machine learning at Edge Impulse, a development platform for machine learning on edge devices, agrees.

“We’re seeing groups now use computer vision with edge AI algorithms for a wide range of purposes, including tracking damage and defects on pallets and products throughout a supply chain; monitoring workplaces for worker health and safety; designing smart cities with intelligent traffic, parking, and emergency integrations

“The transition toward edge computing epitomizes a stride toward a more intuitive, secure, and responsive world.”

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The 7 Top Applications for Computer Vision on the Edge

1. Oil and Gas

To address environmental, health, and safety, companies use vision systems to identify issues previously only routinely checked by people, says de Anda.

“This includes things such as flare or process monitoring to identify hazardous environments, such as process fluid or gas leaks, to determine if hazardous fumes and vapors are being released into the air by monitoring the color of the flames,” he explains.

Additionally, a real-time camera system at the edge can also monitor the use of personal protection equipment, for example, to identify if someone is in a hazardous area or even if someone has fallen or been injured, de Anda adds.

“AI-enhanced monitoring systems can help assure that video surveillance is always monitored and can be trained to identify an injured person,” he says.

2. Autonomous Vehicles

Driverless cars have generated billions of dollars in investments, creating massive potential value for the auto industry, says Sunil Senan, SVP and global head – data, analytics, and AI at Infosys, an IT services and consulting company.

“Through computer vision on the edge and LiDAR [light detecting and ranging], autonomous vehicles can understand their environment and identify visual information, such as pedestrians, traffic signs, and lane markings,” he says. “This, combined with [advanced driver assistance system] modules, allows autonomous vehicles to operate safely without requiring a central server.”

3. Healthcare

Healthcare organizations can use edge-based computer vision to enhance patient outcomes and reduce costs. For instance, wearable devices with computer vision can monitor patients for injuries or illnesses and then alert their doctors’ offices if they need help. This improves patient outcomes and cuts down on hospital readmissions.

4. Smart Spaces

Computer vision on the edge enables spaces to be smarter and better protected, says Senan.

“Through trespassing identification and surveillance, continuous monitoring can be deployed to detect suspicious activities and alert authorities.

Additionally, computer vision can be leveraged in the workplace or school environment to alert for potential dangers through intrusion detection.”

Additionally, edge devices with computer vision can also be used in smart home applications. For example, smart cameras with computer vision can detect when individuals enter or leave a room and adjust the temperature and light settings accordingly.

5. Public Safety

Public safety officials can use edge-based computer vision to enhance their emergency response times and cut down on crime. For instance, cameras with computer vision can analyze crime scene images quickly and notify authorities if they detect any suspects.

Furthermore, they can enable emergency management officials to quickly assess the situations surrounding natural disasters or other emergencies in real-time, speeding their response times.

6. Construction

Construction companies can use edge-based computer vision to continuously monitor their construction sites to ensure their employees aren’t entering unsafe areas and monitor their equipment.

For example, vision-based data, including videos and images, can give construction managers valuable data to better manage and control their projects. By looking at surveillance videos of construction sites constantly being recorded, project managers can identify safety issues, e.g., are workers wearing their hard hats?

They can also use these videos to determine how productive their employees are and if their equipment is operating efficiently.

7. Manufacturing

Manufacturers can enhance operations by applying computer vision systems to help speed up and improve the process of identifying product defects.

Defect inspection through computer vision on the edge can identify defects, such as broken parts or corrosion, to help in industrial asset maintenance, says Senan.

“This generates benefits across industries, such as increased product quality, improved operational efficiency, and greater reliability of assets,” he says

In addition, thermal and infrared cameras can see things people cannot and can go places people cannot, including extreme and harsh environments, de Anda said.

“[Consequently], companies are integrating cameras into their processes to add quality control and quality assurance points into their processes,” he says. “For example, in the food and beverage industry, cameras can continuously monitor to ensure foods are all cooked to the correct temperature, and in the steel industry, they can detect weak points in a beam or welding process.”

The Bottom Line

Edge computing is reshaping the landscape of computer vision, moving to an era of enhanced perception and intelligent decision-making right at the device level, says Situnayake.

“By enabling data processing on edge devices, we’re significantly accelerating response times, bolstering security, and providing real-time insights,” he says.

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Linda Rosencrance
Technology journalist
Linda Rosencrance
Technology journalist

Linda Rosencrance is a freelance writer and editor based in the Boston area, with expertise ranging from AI and machine learning to cybersecurity and DevOps. She has been covering IT topics since 1999 as an investigative reporter working for several newspapers in the Boston metro area. Before joining Techopedia in 2022, her articles have appeared in TechTarget, MSDynamicsworld.com, TechBeacon, IoT World Today, Computerworld, CIO magazine, and many other publications. She also writes white papers, case studies, ebooks, and blog posts for many corporate clients, interviewing key players, including CIOs, CISOs, and other C-suite execs.