Computer Vision is a field of artificial intelligence that works on enabling computers to see, identify and process images in the same way that human vision does, and then provide the appropriate output. Computer Vision is the same as imparting human intelligence and instincts into a computer. A computer vision (CV) model is a processing block that takes uploaded inputs, like images or videos, and predicts or returns pre-learned concepts or labels. Examples of this technology include image recognition, visual recognition, and facial recognition.

According to marketsandmarkets, the computer vision market is expected to grow from USD 10.9 billion in 2019 to USD 17.4 billion by 2024-growing at a CAGR of 7.8% during the forecast period.

Major factors driving the market growth include increasing need for quality inspection and automation, growing demand for vision-guided robotic systems, rising demand for application- specific computer vision systems. The ability of machine vision systems to process massive amounts of information in a just a few seconds is one of the other major factors driving the market.

Computer vision strives to replicate the human eyes effectively, together with the brain’s ability to tell the difference between different objects or situations. Using this in an industrial setting should result in fewer accidents and prevention instead of correction.

The automotive industry is one of the early adopters of computer vision systems and continues to hold the largest share of the computer vision market among other industries in the industrial vertical. Automation is widely used for assembling vehicles in this industry; hence, the adoption of computer vision systems is high. This is contributing to the growth of the computer vision market for the automotive industry.

Soaring need for vision-guided robotic systems across the pharmaceutical & chemical, food & beverage, automotive, and packaging industries is expected to augment the market. Surging demand for application-oriented machine vision systems is also boosting the adoption of the technology over the forecast period.

Computer vision is extensively used for inspection purposes, which include presence/absence checking, secure detection of Personal Protective Equipment, Activity Recognition, Forklift safety, etc.  A computer vision solution can work with an existing CCTV network and act as an advanced and effective replica of the human eyes. However, these CV eyes will have the added ability to classify different objects or situations and react accordingly, such as in the form of alerts.

Here are the 4 ways to enhance industrial safety using CV technology:

• Workplace Safety
• Workforce Safety
• Activity Recognition
• Object Recognition

1. Workplace Safety:

The Computer Vision solution will ensure workplace safety and maintain the workplace minimal error prone zone. Computer Vision would be able to detect unexpected occurrences at the workplace that are not acceptable with the standard operating procedures. CV capturing movement on a fork-lift or other vehicles help to prevent accidental human-machine collision due to blind spots or when the vehicle is unprepared. For example, the system would have the potential to monitor unauthorised and unexpected access entry of personnel into workplace area. Once detected the unauthorised and unexpected access entry of personnel in the way of forklift, it triggers an alarm and notifies the machine handler and the personnel. This process helps in minimizing accidents that cause in the workplace area due to forklifts.

2. Workforce Safety

Vision Intelligence solutions uses the latest innovation in Neural Networks that are trained with examples of pictures and videos of human wearing safety gear just like human Brain. With the ability to monitor security camera footage, the solution will accurately identify hardhats, visibility vests, work goggles, etc., making workforce safety and compliance extremely viable. Workers without prerequisite safety equipment or protective gear will be identified and real-time notification/alert will be sent to the safety manager.

3. Activity Recognition

With the help of cutting-edge Vision Intelligence model, we can track and classify activities performed by workforce in the workplace. The computer vision technology will be able to monitor and capture the data of real-life activities of the workforce such as bending, lifting, pushing, pulling, moving, sitting, etc. These activities can be tabulated to measure employee chances of repetitive stress, physical pain and injuries etc.

4. Object Recognition

The computer vision can classify and detect objects present in the workplace. By the ability to detect multiple objects on the workplace, it can identify any faults with raw materials that may be too small for the human eye but could prove detrimental for the final product. The application of the solution can further encompass operational safety compliance. This would include material safety, such as the multi-object detection through Computer vision, with automatic scanners on production lines, etc.

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