8 Challenges Computer Vision Technology Solves in Real life applications

Computer vision technology hasn’t just grown to be the talk of the town for no reason. This powerful technology has made it possible for computers to process information from images, much like humans would, using deep learning models. This has contributed to its popularity in application across industries to overcome several challenges. Here are some of the challenges that can help overcome in different industrial sectors.

Catching of criminals

Theft, robberies, and other crimes are difficult to keep track of, and surveillance cameras may not always capture license plates with the degree of accuracy required to catch criminals. Police officers can’t be present at all places in anticipation of a crime. Fitting surveillance cameras with computer vision technology can help gather data on license plates and make catching criminals easier.     

Measuring student engagement in classrooms

It’s not always easy to track every student’s interest level and attentiveness when teaching a class, regardless of whether the class is taken online or in a traditional classroom. Computer vision can help draw insights from facial expressions of students to gauge interest levels. This will help educators make changes to their teaching methods and structure modules that promote maximum student engagement.   

Detecting defects

In manufacturing or assembly line work, it’s extremely difficult to detect any defective products because of the speed of processing and volume of products involved. Computer vision can overcome this challenge by identifying any product defects so that changes may be made accordingly. It can also identify machines in need to predictive maintenance and save on expenses related to machine servicing and maintenance.   

Safety and security

With computer vision, security can be enhanced in any industry. This is especially important for banking, finance, and defense sectors where security breaches can occur, and the cost of human error can’t be afforded.

Accident prevention

Preventing accidents is an objective to strive towards, but how to make that a reality through vehicles? Computer vision makes it possible to use self-driving cars, and such autonomous vehicles show lots of promise with regard to accident prevention.  

Accuracy of diagnosis

Even the best medical facilities may struggle to make an accurate diagnosis in some circumstances. With medical imaging made possible through computer vision technology, the accuracy of diagnosis can be enhanced.

Stock and inventory management

Checking stock and inventory manually poses a challenge and is time-consuming. Computer vision automates this task to speed up the pace of operations and give notifications when refilling is needed.

Personalization of customer experience Customer experience can be personalized only to a limited extent through human analysis. Computer vision though, can be used to maintain a database of customers and personalize their shopping experiences based on preferences and past buying behavior. This can result in greater customer satisfaction

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