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Artificial Intelligence in the industry contributes to the transformation of the productive sector. Through computer vision, an application of Artificial Intelligence (A.I.), the digital transformation of the most diverse sectors of industry has become a reality. It is one of the most promising trends for the coming years and one of the fastest-growing because it is based on Deep Learning models and is bringing transformative changes to our daily lives. Artificial Intelligence through computer vision is capable of capturing, processing, analyzing, and understanding digital images and videos. It allows computers and other machines to see and recognize just like the human eye, generating actionable insights according to the designed algorithms. It addresses unique business challenges and improves business performance through image processing and enhancement, image classification, object detection, feature and pattern recognition, 3D image reconstruction, and enhanced video analysis. Let's check below some of the applications of artificial intelligence in the industry starting from computer vision in different sectors. READ ALSO: • Learn everything about Computer Vision
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• What is machine learning?
• Quality control in industry and artificial intelligence
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Artificial Intelligence in the Automotive Sector
From the assembly line and the vehicle manufacturing process to the vehicles on the streets, artificial intelligence is proving its acceptance and presence, making driving safer every day.
ADAS Applications
Computer vision applications in ADAS (Advanced Driver Assistance Systems) are prominent. Computer vision through ADAS technologies (camera-based), RADAR, and LIDAR (both based on laser vision) are paving the way for automotive companies toward fully automated self-driving cars. Different systems within a car perform different tasks, such as camera-based ADAS providing visual representation, RADAR functioning in low-visibility conditions, and LIDAR providing a 3D representation of the vehicle's surroundings with object recognition. However, all of these ADAS applications are only possible thanks to computer vision technologies, which together provide a comprehensive solution in ADAS applications. This allows the driver to have a better awareness of their surroundings while driving and, at the same time, have more control over their automotive vehicle.
Automotive gesture recognition
Automotive gesture recognition with artificial intelligence is the next level in road safety, based on deep learning and Machine Learning capabilities. Gesture recognition technology monitors the driver's facial and hand gestures (talking, texting, operating the radio, eating and drinking while driving, etc.) and notifies them if they differ from pre-programmed, recognizable gestures. Facial expressions such as blinking, drowsiness, and head movements are recognized with computer vision technologies and send audible or visual alerts to notify the driver. Artificial intelligence in industry through computer vision is also very useful in transport and fleet management when it comes to managing the safety of passengers, drivers, and goods. Computer vision-based solutions supported by automotive cameras (dash cams, outward-facing) and telematics solutions play a key role in the safety management of these assets and manage fleet operations with extraordinarily reduced risks.
Computer Vision in Retail
Improving the shopping experience
In addition to ensuring safety, spill detection, and theft control, retail video analytics using computer vision and artificial intelligence is more focused on improving the customer's shopping experience and optimizing operations. Retail stores with computer vision and machine learning capabilities deployed at customer touchpoints not only collect customer data but also process information about product placement, shelf stock quantity, and customer needs to help store employees provide better service.
Generating valuable insights
Artificial intelligence in retail, with the help of in-store cameras, shelf cameras, captures images of products in the aisles and processes them to extract actionable insights. This helps to digitize every detail of the products kept in the aisles, such as assortments, share of shelf, product availability, newly launched products, brands and their respective variants, prices and discounts, and out-of-stock products. Technologies based on computer vision and deep learning algorithms help generate product insights, such as finding out if products are placed in the proper location, the impact of product placement on their sales, product promotion, building brand awareness, and much more. The latest trend in the retail industry is to apply computer vision to provide end-to-end solutions and reduce checkout time for their customers. Artificial intelligence, through computer vision, is providing solutions to detect customers and their selected products, thereby facilitating checkout with EPOS integration and object detection.
Artificial Intelligence in Manufacturing
Production lines in high-tech manufacturing plants are highly complex and automated. Computer vision technologies in manufacturing plants are very useful and bring several unprecedented benefits to the business. Here are some of them below:
Predictive Maintenance
Modern manufacturing plants are equipped with automated production lines featuring transport units and robotics, and because of this, a company can never afford an unexpected breakdown of any part of the system. Even a slight breakdown in the production line due to a system defect can be very disastrous for the good practice of industrial processes. And this is where the role of computer vision comes into play, analyzing all components of the production line and detecting even the smallest defects in the system. Based on detailed and precise investigation, computer vision systems can predict any chance of future system failure, notify the technical team responsible to correct the cause, and ensure there is no production downtime.
Defect Identification
Inspecting defects in an industrial setting can be very risky, tedious, expensive, and time-consuming, and sometimes it is nearly impossible to manually detect any defects in machinery. Computer vision technologies in these cases assist in eliminating risks for workers and work precisely to identify cracks, corrosion, leaks, and other anomalies in machinery. Industries such as automotive, pharmaceutical, textile, or energy are utilizing computer vision technologies to run their processes as effectively as possible, free of defects.
Product Quality Inspection
In conventional manufacturing plants, product quality inspection is the last step of the production cycle, which leads to compromised production capacity, time, labor, and production setup cost. With the introduction of computer vision supported by artificial intelligence (AI) and machine learning (ML) techniques, the quality of products and their packaging are inspected at all stages of production with high precision and accuracy, resulting in minimal product waste, cost, and effort.
Computer Vision in Security and Surveillance
One of the first sectors to adopt artificial intelligence technologies is the security and surveillance industry. It was computer vision that exponentially improved techniques and accuracy in video surveillance and intelligent video analysis. The volume of data generated by video surveillance systems depends on the number and types of video cameras and their resolution for specific projects. The huge amount of video feeds is useless unless some critical information can be generated. Computer vision has made this possible through the use of AI and ML in video analysis. Artificial intelligence capabilities through computer vision in security and surveillance are based on: • Video management software and its hardware
• Third-party devices (such as sensors, alarms, access control devices)
• Network
• Interfaces
• Signal processing capabilities
• Pattern and object recognition, etc.
Applications of artificial intelligence in industry and other segments through computer vision
Fleet Management
In fleet management, computer vision is used to ensure the safety and security of vehicles in transit, consignment, driver, and passengers, and assists in optimizing fleet routes. It improves fleet operations by monitoring driver behavior, incident capture, route optimization, shipment tracking, time management, license plate recognition, etc.
City Surveillance
The concept of a smart city is impossible without computer vision technologies. The safety of public places such as parking lots, bus terminals, railway stations, subways, hospitals, highways, intersections, junctions, and their respective monitoring with advanced video analytics is driven by computer vision algorithms. Some of the vision-based applications in city surveillance are crowd detection, face recognition/capture, crowd detection, camera tampering, vehicle tracking, license plate recognition, missing/forgotten object detection, illegal parking, speeding vehicles, wrong-way vehicle detection, etc.
Conclusion
The applications of artificial intelligence in industry through computer vision can be applied in many other sectors, such as agriculture, oil and gas, life sciences, sports, consumer electronics, and much more. The reason behind the adaptability of computer vision in almost every sector is its accuracy, far exceeding human vision. Computer vision algorithms, if properly designed for any of the use cases, can save time, improve productivity, and significantly reduce operational costs. Did you like this article? Learn about Pix Force's work! Get in touch with us!
Fabio Caraça
Fábio Caraça is the Chief Growth Officer at Pix Force. He leads Pix Force's transformation into a scalable SaaS operation, combining strategic vision, culture, and high-impact execution.
