What are machine vision cameras used for? (2024) 

Vision may well trigger the next industrial revolution. With a fast-growing number of use cases across multiple sectors and a projected market value of almost $60 billion by 2030, the signs are there, at least. 

When we talk about machine vision, we refer to a form of artificial intelligence (AI) that helps machines observe, analyze, and interact with the world around them. You could say it gives machines a brain – one formed by deep learning models and countless visual stimuli – which they use for tasks like advanced automation and precision manufacturing. 

The eyes of the machine, in this case, are industrial cameras. These provide the images and videos that vision models use to analyze situations in real time. Though they can be as simple as those found in parking lots or on the dashboard of a car, many businesses opt for high-performance cameras designed to survive on the frontlines of industry such as the Tokay Pro and Tokay Lite, which offer advanced features like edge computing and IoT connectivity. 

Thanks to greater computing efficiency, cheaper hardware, and bold innovation, machine vision costs are set to fall in 2024, opening up even more scalable and flexible real-world applications on the journey to Industry 4.0. Here at Maxlab, we believe three main sectors will benefit the most from machine vision cameras in 2024: 

• Manufacturing
• Automotive 
• Greentech

These cameras feed data to vision models which can conduct and automate manufacturing tasks such as:

• Object detection and recognition
• Guiding machinery
• Sorting and counting 
• Identifying malfunctions
• Inspecting parts for defects and anomalies 
• Packaging and labeling
• Taking measurements
• Monitoring compliance with rules and regulations

Machine vision can help factories increase the accuracy and quality of manufacturing processes, streamline production output, cut operational costs, improve the safety and well-being of staff, and ultimately inform better decisions when time is of the essence. 

For these reasons, machine vision also frees up headspace for innovation and logistics, helping businesses focus away from basic tasks and on designing new products and optimizing their supply chains.

From the production line to the road, vision is the main artery of the automotive industry. According to a global survey conducted by Zebra Technologies, 24% of manufacturers in the sector are using machine vision right now, while 44% plan on doing so by 2027.

Vehicles are often mass-produced in automotive factories in line with strict quality requirements. This means that if things go wrong, they can get costly, so machine vision cameras are used to ensure the utmost precision. 

In the factory, they can:

• Spot scratches on machined surfaces 
• Identify, select, and inspect automotive parts and coatings
• Uphold stringent quality control processes
• Save money and boost efficiency 

Once a vehicle is on the road, vision can help it drive autonomously. Connecting to conventional dashboard cameras and other technology such as lidar sensors allows machine vision algorithms to visualize the road ahead and recognize hazards, road signs, and speed levels, warning drivers of potential collisions. Cameras inside the car, meanwhile, can monitor driver behavior. By drawing up a 3D depth map that tracks a driver’s head, face, and eyes, machine vision models can inform software that alerts drivers if they get distracted – one of the main causes of traffic accidents. In the same way, they can also detect if a driver’s hands are on the steering wheel, whether they’re wearing a seatbelt, the seat occupancy of the vehicle, and even adapt the way the airbag opens depending on how someone is sitting to prevent injuries – all to help encourage safer habits on the road.

Industry 4.0 is a pipedream if the planet can’t support it. Thankfully, machine vision cameras are helping pave the way to a more sustainable future. 

In 2024, industrial cameras will have important applications in areas of Greentech such as:

• Recycling 
• Agriculture 
• Wildlife monitoring

The world throws away over 2 billion tons of waste every year, a figure expected to increase by 70% by 2050, and only around 30 percent of it actually gets recycled.

Vision can help change this. By automatically scanning waste items using industrial cameras, disposal plants can find out what they are and what they’re made of, as well as if they can be recycled or not, before firing off the information to a database or delegating the heavy lifting to a robot that picks and sorts the materials.

Semantic segmentation is a common machine vision technique used to classify waste based on the pixels captured in an image or video. Spectral cameras, though, are a hot topic in recycling right now, particularly for plastic detection, as they can see beyond the visible light range. These cameras sort plastics – which are otherwise very hard to detect – by their chemical composition based on the wavelengths they give off in spectrums such as infrared, x-ray, and ultraviolet. 

The information captured by machine vision at waste disposal plants can increase the turnover of recycled products, improve quality control processes, and help facilities and governments monitor the type and amount of waste being produced. Knowing this can lead to better waste reduction strategies and improve the cleanliness of our cities.

Climate change sadly threatens a growing number of animal species and ecosystems, which is why it’s more important than ever to monitor and protect them. 

Ever tried to film a wild animal, though? It’s tough – they’re often camera shy, following erratic or nocturnal patterns while blending into their environment and spreading themselves out across very large areas. Processing the sheer amount of visual data collected afterward can present an even bigger challenge too.

Industrial cameras driven by machine vision can automate what is often a tedious and expensive job of counting and classifying animals in the wild. Whether it’s via camera trapping – a method of capturing images of animals as they walk past a motion sensor – or alongside technology such as thermal imaging, night vision, and drones, machine vision cameras use annotation techniques to audit different species and their habitats, monitor their behavior, and help experts advise on best practices for conservation and combating climate change. 

Industrial cameras can even help law enforcement stay one step ahead of poachers. How? Drones recording footage of endangered animals in real time can do the same for the criminals tracking them on the ground – killing two birds with one stone (metaphorically).

Farmers have a lot on their plate right now. They need to figure out how to feed a growing population – which is set to surpass 10 billion by 2050 – and replace a shrinking workforce. That’s all while protecting animals and crops against disease, pests, and the effects of climate change. 

Industrial cameras driven by machine vision on farms can automatically (and non-invasively) count, classify, and monitor animals in real-time, as well as play doctor – monitoring their heart rate, temperature, food and water supplies, and behavior. This information in particular can be cross-referenced with disease symptoms to flag outbreaks before they spread. 

In terms of their crops, farmers can tackle hard-to-see threats such as weeds using drones equipped with industrial cameras to spray herbicides with extreme precision, while spectral cameras can help distinguish between different plant species and grade the quality of food products. 

Machine vision can also be used in agriculture to:

• Monitor the nutrient and moisture content of soil 
• Detect diseases in produce
• Analyze and improve the structure of irrigation channels
• Predict harvest times
• Sort produce

As industrial cameras lead the charge toward Industry 4.0, there’s no better time to start implementing them. 

Here at Maxlab, we have a deep understanding of industrial cameras and AI. We know that every project is different and each problem is unique, and we also realize that many businesses are dealing with machine vision for the first time. 

That’s why we want to offer a reliable and expert helping hand. Whether you’re facing challenges in manufacturing, greentech, logistics, construction, or something else, get in touch and our world-class team of experts will work with you to find a solution.