Powered by Artificial Intelligence (AI) technology, computer vision (CV) has emerged as the “eyes” for monitoring a variety of applications across industries. For instance, in the manufacturing industry, AI and computer vision are elevating operational excellence with a focus on safety, productivity, and inspection capabilities.
Here are some of the prevalent use cases of CV technology:
- Quality control in a production facility
- Workplace safety in an industrial facility
- Accurate product dimensioning in a warehouse facility
And so on…
Right from human faces to financial documents, computer vision is streamlining business applications across industries – primarily in:
- Manufacturing
- Retail
- Supply chain and logistics
- Healthcare
This is not all. As an AI technology, computer vision is powering a host of new emerging applications in the business domain. Here’s a look at 6 emerging use cases of CV in 2024 and beyond:
- Vehicle insurance claims
Traditional insurance-related activities like underwriting and claims processing have been time-consuming and prone to human mistakes. With computer vision, vehicle insurance companies are gradually automating these activities, thus achieving both speed and accuracy.
By capturing real-time images or videos of damaged vehicles using CV systems, insurance companies can expedite the evaluation of the damage and repair expenses. Computer vision also helps them validate – or invalidate – the insurance claim, thus leading to faster processing. Thanks to benefits like automated damage assessment, insurance companies are investing in AI and computer vision – to the tune of $2 billion.
- Customer footfall
Retail companies are using computer vision for a variety of applications like product placement and inventory management. Among the emerging applications, computer vision (along with machine learning algorithms) can track and analyze customer footfalls in shopping malls and retail stores.
For example, CV algorithms can detect visitors and analyze various parameters like:
- How they spend time browsing for products
- Their attention span when looking at any store display
- Average waiting and queueing time to check out of the store
- Quality of the rendered customer service
Besides, computer vision is effective at distinguishing between new and returning customers. For instance, it can “recognize” store staff and exclude them from the footfall count.
- Worker fatigue and posture
Here are some “shocking” statistics about worker fatigue released by the National Safety Council (NSC):
- 97% of workers have at least one workplace-related fatigue risk factor.
- 80% of workers have at least two risk factors or more.
- 37% of workers are sleep-deprived.
Worker fatigue can lead to a loss of productivity and a high frequency of human errors. Using computer vision systems, logistics and distribution companies can automatically detect worker fatigue and improve safety. For instance, in the transportation industry, CV-enabled systems (fitted in long-haul trucks) can detect symptoms of driver exhaustion or drowsiness.
Similarly, CV-enabled systems can monitor the worker’s posture when lifting or moving heavy objects. It can also automatically generate a list of unsafe practices in warehouse operations.
- Checkout-free retail stores
With computer vision technology, retailers can now automate the checkout process, thus saving both time and space. Equipped with computer vision-enabled cameras, smart carts can automatically scan every added product, thus allowing shoppers to completely skip the checkout queue.
Here’s an example of how Poland-based retail store, Take&GO has created a cashier-less self-service store – without any checkout or payment counters and store personnel. Customers are verified through their mobile app, while “intelligent” CVV-enabled cameras and sensors can identify the purchased products.
- Warehouse automation in logistics
In the logistics industry, computer vision is gradually transforming warehouse management through automation. Enabled by AI and CV technology, warehouse robots are handling individual inventory items. Besides, robots are proving efficient at product packaging and labeling – while being monitored by CV systems.
Additionally, CV-enabled systems can monitor the internal humidity and temperature of warehouses – thus ensuring ideal storage conditions for heat-sensitive products. Here’s an example of how Fetch Robotics used autonomous mobile robots (AMRs) to enable its warehouse and distribution centers to manage their growing volume of e-commerce orders.
- Product design and prototype
Computer vision can also improve product design by helping designers understand their customer’s needs and preferences. With CV technology, designers can make their products more visually appealing, intuitive, and easy to use.
Furthermore, product designers can use 3D computer-aided design tools in conjunction with CV-enabled models. Here’s an example of how Hyundai designed the multi-terrain car, Elevate by integrating computer vision with CAD. Another example is that of toy manufacturer, Moose Toys’ design of Magic Mixies that used CV and CAD technology to convert a concept to a functional prototype in just 3 to 4 months.
Summary
Over the years, computer vision systems have evolved much beyond carrying out simple tasks like inventory counting. This AI-powered technology will power innovative use cases across industries in the coming years. In this blog, we have discussed some of the emerging use cases.
As a member of the NVIDIA startup inception program, KamerAI has enabled customers across 3 continents to leverage the capabilities of its computer vision platform. Here are some more reasons why enterprises choose KamerAI:
- Over 25 site implementations
- Over 15 use cases
- Over 46 trillion processed images
KamerAI is trusted by leading retail, logistics, and manufacturing companies. Are you looking for a trusted and reliable technology partner? Speak to our CV experts.
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