Organisations faced a number of unforeseen challenges in nearly every business sector throughout 2020 – and continuing into 2021. Until now, businesses have been on the defensive, reacting to the shifting workforce and economic conditions, however, COVID-19 proved to be a catalyst for some to accelerate their long-term technology and digitalisation plans.
This is now giving decision-makers the chance to take a proactive approach to mitigate current and post-pandemic risks. These long-term technology solutions 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 will likely be precipitated by not only the resulting economic impacts of the pandemic but also the growing sophistication and maturity of technologies such as Artificial Intelligence (AI) and Machine Learning (ML), technologies that are coming of age just when they seem to be needed the most.COVID-19 proved to be a catalyst for some to accelerate their long-term technology and digitalisation plans
Combined with today’s cutting-edge computer vision capabilities, AI and ML have produced smart cameras that have enabled organisations to more easily implement and comply with new health and safety requirements. Smart cameras equipped with AI-enabled intelligent video analytic applications can also be used in a variety of use cases that take into account traditional security applications, as well as business or operational optimisation, uses – all on a single camera.
As the applications for video analytics become more and more mainstream - providing valuable insights to a variety of industries - 2021 will be a year to explore new areas of use for AI-powered cameras.
Optimising production workflows and product quality in 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. As many in the agriculture sector seek to find new technologies to assist in reducing energy usage, as well as reduce the environmental strain of modern farming, they can find an unusual ally in smart surveillance. Some niche farming organisations are already implementing AI solutions to monitor crops for peak production freshness in order to reduce waste and increase product quality.
For users who face environment threats, such as mold, parasites, or other insects, smart surveillance monitoring can assist in the early identification of these pests and notify proper personnel before damage has occurred. They can also monitor vast amounts of livestock in fields to ensure safety from predators or to identify if an animal is injured.
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 track and manage inventory in real-time, improving knowledge of high-demand items and allowing for better supply chain planning, further reducing potential spoilage.
Efficient monitoring in manufacturing and logistics
New challenges have arisen in the transportation and logistics sector, with the industry experiencing global growth. While security and operational requirements are changing, smart 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 a significant impact on the overall customer experience. Smart 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.
Video analytics can assist logistic service providers in successfully delivering the correct product to the right location and customer in its original condition, which normally requires the supply chain to be both secure and ultra-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 available for offloading or alert facility staff of potential blockages or hazards for incoming and outgoing vehicles that could delay delivery schedules planned down to the minute.
For monitoring and detecting specific vehicles, computer vision in combination with video analysis enables security cameras to streamline access control measures with license plate recognition. Smart cameras equipped with this technology can identify incoming and outgoing trucks - ensuring that only authorised vehicles gain access to transfer points or warehouses.
Enhance regulatory safety measures in industrial settings
Smart surveillance and AI-enabled applications can be used to ensure compliance with organisational or regulatory safety measures in industrial environments. Object detection apps can identify if employees are wearing proper safety gear, such as facial coverings, hard hats, or lifting belts. Similar to the prevention of break-ins and theft, cameras equipped with behaviour detection can help to automatically recognise accidents at an early stage. For example, if a worker falls to the ground or is hit by a falling object, the system recognises this as unusual behaviour and reports it immediately.
Going beyond employee safety is the ability to use this technology for vital preventative maintenance on machinery and structures. A camera can identify potential safety hazards, such as a loose cable causing sparks, potential wiring hazards, or even detect defects in raw materials. Other more subtle changes, such as gradual structural shifts/crack 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 that could potentially pose a physical safety risk to people or assets.
Early recognition of fire and smoke is another use case where industrial decision-makers can find value. Conventional fire alarms are often difficult to properly mount in buildings or outdoor spaces and they require a lot of maintenance. Smart security cameras can be deployed in difficult or hard-to-reach areas. When equipped with fire detection applications, they can trigger notification far earlier than a conventional fire alarm – as well as reduce false alarms by distinguishing between smoke, fog, or other objects that trigger false alarms.
By digitising analogue environments, whether a smoke detector or an analogue pressure gauge, decision-makers will have access to a wealth of data for analysis that will enable them to optimise highly technical processes along different stages of manufacturing - as well as ensure employee safety and security of industrial assets and resources.
Looking forward to the future of smart surveillance
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 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.