7 Leading Applications for Computer Vision at the Edge
Edge computing is transforming how computer vision operates, enabling faster and smarter decision-making directly on devices.
Edge computing is driving a new wave of intelligent systems, smart gadgets, and immersive experiences in computer vision. The advantages, such as quicker processing, improved security, and real-time data insights, make it essential for computer vision applications.
Edge computing enhances computer vision by allowing rapid processing and analysis directly on devices like sensors, smartphones, and cameras, eliminating the need for cloud servers.
From self-driving cars to warehouse robots and smart home assistants, billions of edge computing devices are hitting the market. These devices are becoming more sophisticated, thanks to advancements in artificial intelligence (AI) and machine learning (ML), according to Mark Hoopes, director of automotive and industrial segment marketing at Lattice Semiconductor.
“Edge processing is becoming increasingly crucial with the rise of AI. The automotive industry, in particular, is quickly adopting AI-based computer vision to help machines understand and interpret the visual world around them.”
There’s been a noticeable surge in interest in key applications for computer vision at the edge, especially over the past year, 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, agrees. His company develops platforms for machine learning on edge devices.
“We’re now seeing groups use computer vision with edge AI algorithms for a wide range of purposes, from tracking damage and defects on products in a supply chain to monitoring worker health and safety, and even designing smart cities with intelligent traffic and emergency systems.
“The shift towards edge computing represents a move towards a more intuitive, secure, and responsive world.”
Let’s explore...
The Top 7 Applications for Computer Vision on the Edge
1. Oil and Gas
Companies in the oil and gas sector are using vision systems to address environmental, health, and safety concerns. These systems can identify issues that used to be manually checked by workers, explains de Anda.
For example, vision systems can monitor flares or processes to detect hazardous environments like gas leaks. They can also observe the color of flames to determine if dangerous fumes are being released into the air.
Real-time camera systems at the edge can also ensure workers are using personal protection equipment and can even detect if someone is in a hazardous area or has been injured.
2. Autonomous Vehicles
Driverless cars have attracted billions in investments, promising huge potential for the auto industry, says Sunil Senan, SVP and global head of data, analytics, and AI at Infosys.
“Using edge-based computer vision and LiDAR (light detection and ranging), autonomous vehicles can interpret their surroundings and recognize visual information like pedestrians, traffic signs, and lane markings,” he says. “When combined with advanced driver assistance systems, this allows autonomous vehicles to operate safely without relying on a central server.”
4. Smart Spaces
Computer vision on the edge makes spaces smarter and more secure, says Senan.
“With capabilities like trespassing identification and continuous surveillance, computer vision can detect suspicious activities and alert authorities.”
Edge devices with computer vision can also be used in smart home applications, like adjusting temperature and light settings when someone enters or leaves a room.
5. Public Safety
Public safety officials can use edge-based computer vision to enhance emergency response times and reduce crime. For example, cameras with computer vision can quickly analyze crime scene images and notify authorities if a suspect is detected.
Additionally, these systems can help emergency management officials assess situations during natural disasters or other emergencies in real-time, speeding up response times.
6. Construction
Construction companies can leverage edge-based computer vision to monitor construction sites, ensuring employees stay out of unsafe areas and equipment is properly managed.
Vision-based data, like videos and images, provide valuable insights for project managers, helping them identify safety issues (e.g., are workers wearing their hard hats?) and monitor productivity.
7. Manufacturing
Manufacturers can use computer vision systems to enhance operations by speeding up and improving the process of identifying product defects.
Edge-based computer vision can detect issues like broken parts or corrosion, aiding in industrial asset maintenance. According to Senan, this leads to increased product quality, improved operational efficiency, and greater reliability.
Thermal and infrared cameras, which can see what humans can’t and reach areas humans can’t access, are being integrated into processes to enhance quality control and assurance. For instance, in the food industry, cameras ensure food is cooked to the correct temperature, while in the steel industry, they can detect weak points in beams or welds.
Conclusion
Edge computing is revolutionizing computer vision by enabling smarter and faster decision-making directly on devices, says Situnayake.
“By processing data on edge devices, we’re greatly speeding up response times, enhancing security, and providing real-time insights.”
