5 Impactful Ways Computer Vision Is Transforming Business Operations
The potential of artificial intelligence (AI) is continually growing, assuming new responsibilities as its capabilities expand. One of its major draws is its ability to use resources like neural networks to engage in deep learning, making precise decisions and predictions based on ever-growing datasets.
Computer vision is one of the most leveraged features in the modern era of AI development because of its industry-agnostic benefits. How are businesses using it, and why does it work so well?
What Is Computer Vision, and How Does It Work?
Computer vision is a technology within AI that allows it to view and assess the world. Using cameras, data and training, it can eventually learn to identify, categorize and define patterns between visual stimuli. It works by leveraging sensors and cameras to gather images and videos. Then, it processes the pixels within them, learning about the subject's qualities. It can work like a human brain, steadily noticing more about its surroundings.
For example, after viewing enough plastic bottles running along a conveyor belt, an AI will eventually recognize the proprietary model. Then, it spots variances and defects against the known ideal. Computer vision is also helpful for applications like workplace security, where it compares badges against faces entering the premises.
5 Ways Computer Vision Impacts Business
These are multiple use cases across industries and how computer vision can transform operations.
1. Enhanced Security and Threat Detection
An AI agent could be a company's biggest asset for isolating and responding to threats. In sensitive environments like airports and government buildings, computer vision can oversee baggage and cross-reference employees with access controls to confidential spaces. Its proven surveillance empowered with computer vision has improved accuracy by reducing human error, while also being able to separate between real and fake hazards.
2. Personalizing Shopping Experiences in Retail
Imagine standing in front of a mirror at a clothing store and trying on an outfit without having to go to a changing room. Virtual mirrors and similar digitized try-on technologies are being deployed due to advancements in computer vision.
Conversion rates are higher if customers can see jewelry, shoes and even makeup on them in-store. Lancôme is a strong case study, using this tech at pop-up shops in the U.K. It improved interactivity and immersion for customers, making them feel more connected to the brand.
3. Improving Quality Control on Production Lines
Research shows computer vision can achieve an accuracy rate of up to 80% when visually inspecting manufacturing products for quality. It saves production lines from costly and time-consuming manual inspections.
However, human-in-the-loop operations could upskill technicians on the line by teaching them how to categorize and observe products informed by data. The algorithms enhance consistency while gradually introducing employees to the ideal standard.
4. Decarbonizing Precision Farming in Agriculture
Although AI consumes resources, it has the potential to transform operations, making them more sustainable and efficient. Computer vision enables more comprehensive oversight over farmlands for agriculturalists, allowing them to improve yields and optimize resource utilization. Incorporating an AI vision system on all-terrain vehicles increased yields by up to 20% and boosted efficiency by up to 25%.
5. Accelerating Diagnostics in Health Care
Algorithms could review more patient data in seconds than humans could in months. The quick decision-making skills of computer vision in AI could expedite critical diagnoses, pulling from imaging technologies like X-rays, CT scans and MRIs.
Over time, the model becomes adept at identifying unique biomarkers and judging them against individualized patient information to provide a more accurate determination and a suggested recovery plan. Early implementation suggests autonomous AI lends a sharper eye when observing chest X-rays. In a study of 1,500 patients, the model demonstrated a nearly 27-percentage-point improvement in sensitivity ratings compared to those reported by radiologists.
The Future Is in Sight
The applications for computer vision technology are as resourceful as the minds behind it. From inventory stocking to airport security, these data-informed, constantly learning visual assets could enable businesses to enter a new phase of digital transformation. The best organizations will identify a use case singular to their niches, deploying computer vision in a way that empowers employees, provides returns and betters customers through innovation.