The trend of Computer Vision utilizes cameras to capture photos or videos and applies artificial intelligence (AI) algorithms to analyze data extracted from this digital imagery. Rudimentary visual AI systems are trained to simply differentiate objects from each other, while more advanced – increasingly AI-enabled – versions can track objects across viewpoints and learn on their own and, in recent developments, enable prediction through pattern recognition.
Enabled by AI, the trend of Computer Vision has developed in conjunction with advances in deep machine learning (ML), leveraging the rising quality and decreasing cost of camera devices.
Several things are driving the adoption of computer vision technology, including the growing need for workflow automation and optimization across many industries, from auto-mobility to healthcare and banking, financial services, and insurance to retail.
In 2023, the global computer vision market was valued at around US$ 17.7 billion and – with continual improvements in AI, vision systems, and computer processing – is expected to grow at a compound annual growth rate (CAGR) of 19.6% by 2026.
Today, advanced computer vision technology is perfecting depth perception, 3D reconstruction, and dark and blurred image interpretation, all of which will unlock more opportunities in supply chains. Future deployment will be driven by further implementation of AI, automated ML, edge computing, the Internet of Things (IoT), and more.
Computer vision will become commonly utilized in logistics operations within the next five years, and many new use cases are likely to emerge. This technology will underpin and drive future logistics success by enabling more automated and efficient processes as well as sustainable and safe operations.
However, to be fully realized, this trend will require additional investment. As experienced in the early days of sensor adoption, computer vision applications must be scalable for logistics organizations to maximize benefits.
