Smart machine vision moves to the edge

06 January 2023

Given that machine vision technology is merging with Machine Learning (ML) to lead the transition to Industry 4.0, the possibilities are enormous, especially at the edge, according to ABI Research, which forecasts that by 2027, total shipments of camera systems will reach 197 million, with revenue of US$35 billion.

The shift from machines that can automate simple tasks, to autonomous machines that can see to optimise elements for extended periods will drive new levels of industrial innovation, says ABI Research’s Edge ML-Based Machine Vision Software and Services application analysis report. “ML can augment classic machine vision algorithms by employing the range and reach of neural network models, thus expanding machine vision far beyond visual inspection and quality control, the locus classicus of good, old-fashioned computer vision,” explained David Lobina, Artificial Intelligence and Machine Learning Analyst at ABI Research.


Of all the trends in the ML market, edge computing has the most exciting applications and benefits – namely, in devices that are part of embedded systems and the Internet of Things (IoT). Smart manufacturing is perhaps the most straightforward case, where smart cameras, embedded sensors, and computers can bring ML analyses to every process step. 

Smart machine vision is on the job in factories, warehouses, and shipping centres, aiding and assisting human workers by handling the more mundane tasks, freeing workers to use their expertise to focus on the essential parts. 

The best way for the technology, according to ABI Research, is to advance through a combination of hardware and software solutions and employing information-rich data. It is through a holistic approach of how all these factors can merge and combine that will achieve fruitful results. Vendors are aware that they need to provide a competitive product. The ‘whole package’ approach is perhaps not the most common example in the market. However, vendors must be increasingly aware of how their offerings can mesh with other solutions, often requiring hardware-agnostic software and software-agnostic data analysis. 

The Edge ML-Based Machine Vision Software and Services application analysis report is part of the company’s Artificial Intelligence and Machine Learning research service, which includes research, data, and ABI Insights. 


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