Computer Vision has evolved swiftly under the AI revolution and is now able to perform complex tasks. It has use cases in every industry and benefits users and businesses alike. Computer Vision’s incorporation into heavy machinery and production units has made life-saving differences to the safety levels.
CV has allowed medical professionals to diagnose and treat various kinds of cancer early through intelligent cancer imaging technology.
These achievements in the field of CV can be hard to top. However, AI experts work continuously to improve the technology. develop even more beneficial use cases for the safety and development of humankind. Below are five of the top trends regarding Computer Vision in 2022.
Data-Driven Computer Vision
AI’s ability to identify facial patterns, events, and environmental factors depends on the quality of data provided to it. Along with the self-learning concept, the base of the CV program’s knowledge needs to be optimal to help train the models and algorithms.
Data scientists have prioritized creating high-quality databases in 2022 by iteratively feeding data to modern algorithms and diligently improving the labeling quality. Scientists hope that augmenting the quality of learning sources for CV will help CV products to operate better in conditions where data is not as readily available.
It is also financially burdening to repeatedly collect large volumes of data to build databases for CV algorithms. Data scientists have determined that focusing efforts on the quality of information will contribute to reducing costs associated with training CV models while enabling them to act more effectively.
Connected and Autonomous Cars
Consumers are now readily adopting driverless cars. Tesla is a famous example of a completely driverless car. Whereas BMW, Toyota, and Mercedes have introduced “connected cars” that people drive themselves but are assisted by AI/CV models. Experts are projecting that connected and autonomous cars will gain a higher market share in the automobile industry.
Consumers get unique benefits with autonomous cars; like optimized route planning, assistance with tricky turns, emergency alerts, and intervention in the case of probable accidents to prevent injuries to the driver. This includes stopping the car if the driver falls asleep at the wheel; which is the cause of a fatal accident 25% of the time.
Apart from personal vehicles, companies are adopting the technology more readily in trucks for long-route road transport. Every year, the logistics business suffers human and financial losses due to drivers wearing out after driving for long hours. Assisted driving and autonomous trucks will help reduce these costs significantly, with substantial change expected in 2022.
In the field of navigation, Tesla has announced a shift to computer vision technology rather than lidar or radar, which they were employing previously. CV will determine the quality of the roads while planning the route. It will offer alternatives if the terrain is not fit to travel on, an essential factor that navigation apps currently do not take into account.
Health and Safety Applications of Computer Vision
Real-time safety protocol implementation has been a popular use case of CV. Manufacturing industries have deployed Computer Vision to avoid frequently occurring workplace injuries such as forklift accidents and injuries from hazardous spillages. The introduction of CV in this regard has saved manufacturers millions of dollars in insurance costs while also making workplaces much safer. Not only do AI-powered cameras alert employees to potential hazards; but inbuilt Computer Vision software can stop forklifts immediately if they detect an employee within their path.
Organizations have also employed computer vision to reduce the spread of infections in the workplace, particularly in the case of the pandemic. CV-operated surveillance systems ensure social distancing and proper gear for all employees, including face masks, PPEs, and face shields. The most successful method of preventing the spread of disease is constant vigilance and following precautionary measures that computer vision systems help enforce.
Medical professionals have also put CV algorithms to good use by creating algorithms for the early detection of tumors. CV enhances the ability of CT scanners and PET scanners to identify threatening tumors and inform doctors, which in turn leads to more accurate diagnoses. Medical professionals are empowered to start treatment quickly and increase the chances of survival from cancer, thanks to CV.
Computer Vision in Retail
The retail industry has experienced significant upgrades with the help of CV. The most prominent trend is Amazon’s cashier-less stores. The Amazon Go Stores use cameras to identify what items a consumer has “purchased” and charge them automatically using the payment information they have provided to Amazon. The cameras also track other significant details like customer movement and behavior patterns, products that need to be restocked, and perform security to stop shoplifters.
The introduction of computer vision to retailers has revolutionized the customer experience. One example is CV-activated mirrors that show you how your clothes would look. You can get a realistic idea of what a specific article of clothing looks like on you. Instead of trying on clothes and exposing yourself to germs. Fashion retailers are dubbing this the “virtual fitting room.”
CV at the Edge
The trends we have covered above already include examples of CV at the edge. This means that companies deploy computer vision systems as close as possible to the data source. Deploying CV at the edge is crucial for some applications. In these use cases the AI needs to compute and make decisions at a faster pace. Therefore, businesses are choosing to have CV systems deployed within the facility or machinery.
Apart from computation speed, when cameras collect data for computer vision algorithms, it is stored in the cloud for a long time. Usually, the storage of this data is unnecessary and becomes a security risk in case of a data breach. This is why organizations prefer to keep the system deployed in-house; so they can be content regarding the security of the data collected for processing.
It remains to be seen how widely accepted this trend will be in 2022, as there is a significantly higher cost attached to deploying CV at the edge. Comparatively, CV over the cloud is more affordable. Therefore, businesses might not shift from the cloud unless absolutely necessary.
These applications of computer vision are exciting as their deployment is beneficial for manufacturers, businesses, and consumers. People will experience the emergence of Industry 4.0 as AI and CV become readily adopted by companies throughout 2022. We can also expect computer vision experts to provide more consumer-centric applications in the near future.
Xavor Corporation has an extensive history of providing AI-based services for manufacturers. Xavor’s all-in-one industrial monitoring services provide innovative applications of computer vision using our proprietary algorithms including visual inspection. Learn more here about how your organization can benefit from Xavor’s computer vision services.