Skip to main content

Machine Vision Tech Revenue will Reach $36 Billion

More organizations are exploring machine vision use cases. Machine vision combines hardware and software to provide operational guidance to devices in the execution of their functions based on the capture and processing of images.

Machine vision is rapidly becoming an enabling technology for emerging automation requirements in automotive, healthcare, manufacturing, retail, smart buildings, smart cities, transportation, and logistics applications.

The total revenue of machine vision technology in the seven major global markets is expected to reach $36 billion by 2027 -- that's up from $21.4 billion in 2022. This growth translates to a CAGR of 11 percent, according to the latest market study by ABI Research.

Machine Vision Market Development

Traditionally, machine vision was primarily focused on surveillance and security, asset monitoring, and defect inspection. These mature applications continue to drive the main bulk of total camera shipments within the enterprise market.

However, the industry is going through the next phase of evolution. The COVID-19 pandemic and the desire for digital business growth have led to the emergence of new use cases -- such as occupancy detection, crowd monitoring, predictive maintenance, high precision automated inspection, automated picking, and sorting systems in warehouses.

"These innovative use cases are expected to drive future growth of the industry. A key enabler of these innovation use cases is Machine Learning (ML), particularly Deep Learning (DL) technology in machine vision," said Lian Jye Su, a principal analyst at ABI Research.

Most technology suppliers offer DL-based solutions that are flexible, scalable, and highly efficient. At the same time, enterprises are waking up to the benefits of DL-based machine vision.

When combined with factors such as decreasing component and engineering cost, increasing ease of integration with third-party solutions, growing open-source software and toolkits, the barrier to adopting an effective machine vision solution has lowered significantly for many enterprises.

Moving forward, distributed computing will become the central theme in the implementation of ML in machine vision. IT platform vendors have been actively launching processors that can run ML models on cameras directly or on gateways and on-premise servers.

Instead of having ML models running in the cloud, these vendors have developed a suite of solutions ranging from ML processors to ML development environment and embedded security enhancement to ensure timely development and deployment of ML models and smooth integration into existing workflows.

Furthermore, this IT domain is expected to become more competitive with the emergence of innovative startups focusing on machine vision at the edge.

Currently, hardware revenue is the main component of the revenue at around 89 percent. However, the share of software and services is expected to grow over time, growing from 11 percent to 16 percent.

Outlook for Machine Vision Applications Growth

With the emergence of DL-based machine vision, more ML solution providers are likely going to build their revenue models around the development, deployment, and maintenance of vertical-specific DL-based machine vision models.

"Instead of fully relying on internal expertise, enterprises can partner with companies to develop targeted solutions together. Such partnerships are critical in reducing the complexity in building and maintaining custom ML models, accelerating time-to-market while maximizing Return On Investment (ROI)," concluded Su.

That said, I expect more enterprise CIOs and CTOs could explore additional applications that combine machine vision with other emerging technologies. The expanding application possibilities are limited only by IT developer imagination and creativity.

Popular posts from this blog

How a Digital-First CEO Leads Transformation

Some leaders reject the notion that "wait and see" is the best response to disruptive change. Savvy senior executives are already driving digital business transformation throughout their organization in an effort to gain a bold strategic advantage. According to the latest market study by International Data Corp (IDC), Digital-First CEOs plan to drive at least half of their income from digital business products, services, and experiences by 2027 -- that's ahead of the market average of 39 percent. Driven by their response to the COVID-19 pandemic, these business leaders have changed how they think about the relationship between business and technology, and how they approach the next digital transformation era -- from scaling digital technology to guiding a viable digital business. Digital Business Market Development IDC defines digital business as value creation based on technology, which entails: 1) Automated customer-facing processes and internal operations; 2) Provision

Digital Solutions for Industrial & Manufacturing Firms

Executive leaders of fast-moving consumer goods (FMCG) are seeking guidance on how to apply new business technology in their manufacturing operations. CIOs and CTOs are tasked with gaining insight into the best solutions for digital transformation. ABI Research evaluated the impact politics, regulation, the economy, supply chain, ESG, and technology are having on FMCG, pharma, producers of steel, chemicals, pulp and paper -- as well as the mining and oil & gas sectors. Digital Transformation Market Development "Our assessment found that the FMCG sector is under pressure from all sides," says Michael Larner, industrial & manufacturing research director at ABI Research . Securing raw materials is challenging considering lockdowns in China and limited grain supplies from Ukraine. Supply shocks are raising input costs, and operating costs are rising with higher energy costs coupled with the pressure to pay higher wages and work sustainably. "We all hoped that with th

Retail Transformation Gains New Momentum

Forward-thinking retailers now have a bright future. In contrast, those that failed to enhance their business model via digital transformation have struggled, declined, and their assets were eventually liquidated. The key difference between these two business outcomes is applied strategic foresight. Even as the world continues to emerge from a global pandemic, retail is growing at levels not seen in the last two decades. Retail sales grew by 7 percent in 2020 and by over 14 percent in 2021, which is in stark contrast to the 3.7 percent annual growth between 2010 and 2019. The increased demand for retail has put a strain on supply chains and retail operations worldwide. As a result, retailers and stakeholders are turning to automation solutions such as mobile robotics for operational ease. Retail Transformation Market Development According to the latest market study by ABI Research, worldwide commercial robot revenue in retail stores will have a Compounded Annual Growth Rate (CAGR) of o