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Three new areas of use for AI-powered cameras

It’s no secret that 2020 presented unforeseen challenges to many organisations in nearly every business sector. While these companies adjusted to changing workforce or economic conditions, COVID-19 has proven to be a catalyst for some organisations to accelerate their long-term technology and digitalisation plans. These initiatives centre on long-term technology solutions that can be used for today’s new world of social distancing and face-mask policies, and flexibly repurposed for tomorrow’s renewed focus on efficiency and business optimisation.

For many, this emphasis on optimisation in a variety of different industries will likely be precipitated by not only the resulting economic impacts of the pandemic, but also the growing sophistication and maturity of technologies powering smart cameras, such as artificial intelligence (AI) and machine learning (ML) – technologies that are coming of age just when they seem to be needed the most.

Manufacturing and logistics

The transportation industry and logistics sector has seen global growth, but with that, new challenges have arisen. Surveillance offers an entirely new way to monitor and control the physical side of logistics, correcting problems that often go undetected by the human eye, but have significant impact on overall customer experience.

Alexander Harlass.

Video analytics can assist logistics service providers in successfully delivering the correct product to the right location and customer in immaculate condition, requiring the supply chain to be both secure and efficient. The latest camera technology and intelligent software algorithms can analyse footage directly on the camera – detecting a damaged package at the loading dock before it is loaded onto a truck for delivery.

When shipments come in, smart cameras can also alert drivers of empty loading bays for offloading, or alert facility staff of potential blockages or hazards for incoming and outgoing vehicles that could delay delivery schedules that are planned down to the minute.

Industrial

In the case of an industrial setting, smart surveillance and AI-enabled applications can be used to ensure compliance with organisational or regulatory safety measures. Object detection apps can identify if employees are wearing proper safety gear, such as facial coverings, hard hats or lifting belts. Cameras equipped with behaviour detection can help to automatically recognise accidents or unusual behaviour in real time, in the event a worker falls to the ground or is hit by a falling object.

For preventive maintenance on machinery and structures, a smart camera can identify potential safety hazards – such as a loose cable causing sparks, potential wiring hazards or even defects in raw materials. Other more subtle changes, such as gradual structural shifts/cracks or increases in vibrations – ones that would take the human eye months or years to discover – are detectable by smart cameras trained to detect the first signs of mechanical deterioration.

Agriculture

Surveillance and monitoring technologies are offering value to industries such as agriculture by providing a cost-effective solution for monitoring of crops, business assets and optimising production processes. Smart cameras are among the new technologies that can assist in reducing energy usage, as well as reduce the environmental strain of modern farming. For users who face environment threats, such as mould, parasites or other insects, smart surveillance monitoring can assist in early identification of these pests and notify proper personnel before damage has occurred.

Using video monitoring in the growing environment as well as along the supply chain can also prove valuable to large-scale agriculture production. Applications can also track and manage inventory in real time, improving knowledge of high-demand items and allowing for better supply chain planning, further reducing potential spoilage.

The future of smart surveillance in these markets

With the rise of automation in all three of these markets, from intelligent shelving systems in warehouses to autonomous-driving trucks, object detection for security threats and the use of AI in monitoring agricultural crops and livestock, the overall demand for computer vision and video analytics will only continue to grow. That is why now is the best time for decision-makers across a number of industries to examine their current infrastructure and determine if they are ready to make an investment in a sustainable, multi-use and long-term security and business optimisation solution.

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