Automated Quality Control using Computer Vision | AI-driven Image Analysis in Automotive Industry | Vision Analytics Company In Australia

Computer Vision Analytics – 4 Ways to Enhance Industrial Safety

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 the 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 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 analytics solutions providers 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.

computer vision market for the automotive industry
*Source: marketsandmarkets

Soaring the 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’s 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 helps 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 unauthorized and unexpected access entry of personnel into the workplace area. Once detected the unauthorized 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.

ComputerVision - Workplace Safety

2. Workforce Safety

Vision Intelligence solutions use the latest innovation in Neural Networks that are trained with examples of pictures and videos of humans wearing safety gear just like the 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 the cutting-edge Vision Intelligence model, we can track and classify activities performed by the 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 in 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 multi-object detection through Computer vision, with automatic scanners on production lines, etc.

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