In recent years, computer vision has made great strides and has been applied across a wide range of industries to drive efficiency and revenue. But what are the most practical and important uses of computer vision today? From the meat industry to object recognition, automated form reading to data entry, we've put computer vision to work for our clients in ways that have helped them solve complex problems and improve their performance. We understand the unique challenges and requirements of these industries and use this knowledge to craft custom-tailored solutions that deliver results for our clients. To ensure the successful implementation of these solutions, we collaborate with a range of experts in the field of computer vision. One company that we work closely with is SnapIT, a team of specialist software developers and engineers, both in electronics and mechanics, create and produce live cameras, tracking systems, and satellite communication systems.
Based on our experience, we’ve compiled a list of key use cases for computer vision that are delivering a high return on investment (ROI) for businesses just like yours. From quality control in manufacturing to self-driving cars and medical image analysis, these use cases will give you a glimpse of what's possible with computer vision.
One way that retailers can take advantage of their growing popularity is by using computer vision to provide a better customer experience. For example, clothing retailers can use computer vision to enable customers to virtually try on clothes, reducing the need for physical fitting rooms and increasing sales.
Computer vision can be used in manufacturing to improve quality control and reduce defects. The use of computer vision systems on assembly lines can identify defects in products, allowing real-time correction and eliminating manual inspections.
The use of computer vision systems on assembly lines can identify defects in products, allowing real-time correction and eliminating manual inspections. For example, if you're assembling a part that requires 100 screws, but you only put in 90 screws, the computer will instantly recognize this and alert you so that you can correct it before moving on to the next step. This saves time and money by reducing human error and improving workflow efficiency.
This technology has been used for years in other industries like aerospace and automotive manufacturing (and even construction), but only recently has it become available for use in consumer electronics like phones and tablets.
The ability to detect diseases early and treat them quickly is critical for improving patient outcomes and reducing costs for healthcare providers. Computer vision algorithms can be used to identify signs of conditions such as diabetes or cancer before they become symptomatic. This can help doctors catch disease earlier and treat it more effectively, which would reduce hospital stays and help medical staff improve patient outcomes.
Computer vision can be used in transportation to improve safety and reduce accidents. In self-driving cars, computer vision systems can help identify obstacles and navigate roads safely. These systems are able to detect things like lane lines, traffic lights, pedestrians, and other vehicles. They can even identify objects that are not on the road, such as trees or signs. It does this with sensors installed on the exterior of the vehicle—like cameras and lidar—as well as sensors inside the car—like radar detectors and sonar. The computer vision system sends this information to a processor which uses machine learning algorithms to make decisions based on what it sees around it.
In the agriculture industry, improving crop yields is one of the key ways to increase profit, and computer vision can help. For example, computer vision systems can be used to monitor crops and identify areas that need watering or fertilization, enabling farmers to optimize their use of resources. These systems are especially useful for large-scale farmers who have many acres of land to manage. They can also help with weed management by identifying areas where weeds have sprouted so they can be treated before they spread throughout the fields.
In banking, computer vision can improve security and reduce fraud. Computer vision algorithms can be trained to automatically detect fake IDs or credit cards, enabling banks to prevent fraudulent transactions. They can also be used to ensure that account holders are authentic by comparing their face against a database of verified customers.
However, in order to train these algorithms, banks will need access to large amounts of data on real-world examples of both genuine documents and fake ones. This kind of data is very difficult for banks to collect themselves because it requires them to purchase large numbers of fake IDs or credit cards and attempt a variety of frauds against their clients. In order to make this type of training possible without breaking the law or endangering their customers' privacy, banks will need access to a huge database of such images that they can use for training purposes.
Computer vision can be used in the energy industry to improve safety and reduce downtime. A computer vision system can be used to monitor oil and gas pipelines, enabling operators to identify and repair leaks before they cause damage.
This type of technology can also be used to detect anomalies in electrical equipment, such as problems with wiring or cracks in insulation. This enables operators to schedule maintenance before an issue becomes serious enough that it would require replacing parts or shutting down equipment for repairs.
8. Food and Beverage
The food and beverage industry can benefit from computer vision to improve quality control and reduce waste. For example, computer vision systems can be used to automatically detect spoilage in fruits and vegetables, allowing producers to reduce waste and increase profits.
Computer vision solutions allow companies to capture images of food products and analyse them using machine learning algorithms. This process can be used to identify items that are too small or too large, or have an incorrect shape or color (for example, an orange that is too pale).
In addition, it is possible to use computer vision systems for more complex tasks such as identifying defects on the surface of a product (for example, a crack in an egg shell). The system can also identify whether a product has been damaged by handling during packaging or transportation; inspect parts for defects before they are shipped out; check if products are correctly packaged before being transported; or even visually inspect products after they have been assembled at the end of their manufacturing line.
9. Environmental Monitoring
Computer vision is a powerful tool for conservationists, enabling them to monitor the environment and track changes over time. Using computer vision algorithms, conservationists can track the health of ecosystems and take actions to protect them by automatically detecting changes in plant or animal populations.
Computer vision has the potential to drive significant ROI in a variety of industries by improving efficiency, reducing costs, and increasing revenue. As the technology continues to advance, we can expect to see even more exciting and innovative use cases for computer vision in the future. If you’re looking to integrate computer vision into your business, schedule a chat with our team of experts here.