Machine Vision Will Have a Huge Impact on the IoT
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We’ve all heard the phrase “work smarter, not harder.” The Internet of Things (IoT) helps people and companies live and work more efficiently as they gain more control over their workflows and greater insights into the data they yield.
The IoT is potent on its own, but the technology known as “machine vision” will reveal additional consequential ways to put it to work in the enterprise. With machine vision, industries are using the IoT to automate their processes and cut down on labor costs.
This is an exciting pairing because, together, machine vision and the IoT can reduce waste, improve service delivery, provide transparency, and help companies do more with less time and labor and fewer resources.
How Machine Vision Partners With Industrial IoT
Every sector stands to gain from adopting the IoT, including health care, financial services, retail, agriculture, and food and industrial manufacturing. The IoT continues to grow because of the benefits attached to this important technology and the competitive edge it gives companies.
The concept here is deceptively simple: Connecting machine vision systems to IoT infrastructure provides the means to identify objects on camera even when there is no human present to receive and study the imagery.
The current trends for machine vision involve working with familiar IoT devices, like security cameras or inspection stations, to increase intelligence using algorithms. They are also used to gather better insight into system operations, activities on the premises, or the process of inspecting manufactured goods — such as consumer electronics or foodstuffs.
Machine vision is added to various systems of IoT because of its ability to not just detect objects within a camera frame, but also to render some kind of judgment about its state, condition, or orientation.
Combining machine vision with the IoT provides lots of competition and efficiency opportunities for businesses. Here are some examples already seeing deployment throughout the global economy:
- Neural net machine vision inspection: Machine vision has long been used to inspect product packaging and to read barcodes and other identifiers. The algorithmic intelligence of modern machine vision provides far greater awareness and nuance. Vegetables and fruits, for example, display a range of colors and conditions. Neural net machine vision inspections — paired with appropriate lighting from fluorescent, quartz halogen, LED, metal halide, or xenon lights — bring humanlike judgment to the process of studying large batches of food products and rejecting even single grains of rice in some cases.
- Near-infrared inspections: Ordinary cameras with RGB sensors are orders of magnitude more powerful today than in years past. Even so, they don’t show the whole picture. Machine vision inspection stations equipped with near-infrared (NIR) cameras can find and understand the hidden conditions that signify product damage or imminent spoilage — such as a bruise beneath the skin of a fresh apple or the water content of a frozen food item.
- Machine vision for safety and security: Machine vision provides the means to automate some of the most labor-intensive parts of premises security. Keeping a watchful eye on hours of camera footage from outside or within industrial environments or construction sites takes vigilance. Machine vision identifies subtle changes and movements within the frame so only useful footage needs to be retained. It also aids in access control and in identifying noncompliant conditions that might lead to safety incidents.
The combination of machine vision and the distributed computing of the IoT means greater autonomy, even for geographically distributed work environments and processes. This includes inspecting pipelines, oil and gas wells, tracts of farmland, transportation infrastructure, and much more.
When it’s paired with the IoT, machine vision means greater independence for physical assets and infrastructure and better decision-making abilities for industrial leaders who may not be physically present. Placing sophisticated imaging equipment and logic at the edge of these networks also means the work is done right in place. This means the data doesn’t have to travel and reduces the load on the company’s main servers. The result is a kind of “distributed sovereignty,” which will lead to even more efficient ways of operating than could be named here.
Benefits of IoT and Machine Vision
The Internet of Things enables companies to rethink their attitudes toward business, industries, and markets. IoT provides tools to grow strategies and meet new objectives. Combining IoT infrastructure with machine vision produces a new range of benefits:
- Reducing bandwidth: Inspection systems are one major application for machine vision. High-performance camera systems enhanced with image sensors can better process and make decisions. The camera can respond based on the data gathered, which reduces the need to send information to the network. The machine vision component of the IoT allows for immediate analysis of data. Bandwidth is reduced because the information is not sent to the network servers.
- Increased efficiency: In automated factories, machine vision can be used for robot guidance systems. The inspection machines talk directly to one another instead of communicating through the central enterprise servers. This decreases the load on the network while increasing the efficiency of the process. In addition, machine vision can control automated tools and equipment in materials handling. This could mean placing a line on the floor for autonomous robots transferring material to follow or identifying items and obstacles for automated picking machines in warehouses.
- Predictive maintenance: Machine vision is used to give warning signs when maintenance and repair are needed in an IoT. Within the transportation industry, this was one of the first major developments in applying machine vision. Siemens, the creator of the Internet of Trains project, embedded sensors into trains and used machine learning models to identify signals the track or train might be failing. Machine vision was able to pinpoint which parts of the rail network would be most likely to fail and where repairs were needed. The use of machine vision can transform business through the way companies operate and the products and services they offer.
- Enhanced customer experience: With the use of machine vision, companies can have an impact on their customers’ behavior and purchasing patterns. They can offer a unique approach when interacting with customers. This creative user experience can influence how people gain insights while companies gather information to increase financial advantages. Machine vision significantly changes services by adding more automation, advancing data analytics and communicating need-to-know information. One application is using machine vision to study movement and purchasing patterns in retail locations. Another is improving the planning phases of civil engineering projects through better understanding of pedestrian and vehicle traffic patterns.
How Will Manufacturers Benefit From Machine Vision?
Two of the primary goals of business are to enhance productivity and reduce risk. Manufacturers and other large-scale operations can use machine vision tools to meet their objectives more efficiently. Utilizing these information-driven IoT devices decreases costs, improves workers’ capabilities, and helps companies prepare for unexpected struggles.
Machine vision tools add value to businesses and help them adhere to their mission. Gathering this new information can improve the lives of manufacturers, employees and customers alike.
The market is consistently evolving, so companies utilizing IoT with machine vision will stand out by displaying innovation, flexibility, efficiency and accuracy. Machine vision-based solutions will take over the market with their enhanced power and speed, which is why market forecasters believe the industry is set for close to 8% growth per year between 2018 and 2025. What the market does with these tools given enough time is one of several new frontiers in Industry 4.0.
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