Dec 16, 2020

How AI and cloud are changing video surveillance

Rishi Lodhia
4 min
AI technologies are disrupting established approaches and transforming systems from simple motion-based alerting devices to unified solutions.
AI technologies are disrupting established approaches and transforming systems from simple motion-based alerting devices to unified solutions...

Organisations are increasing their use of video surveillance as its benefits now extend beyond security into business efficiency. However, the challenge that many businesses are facing is that their existing video system was built using outdated, legacy technology. This either requires consistent monitoring by employees or a time-consuming manual review of footage after events have occurred to gain insights on what could be improved in the future. This creates limitations on what this technology can achieve and the improvements that it can make for organisations in meeting their security, safety and business needs. 

Traditional on-premises infrastructure has also created challenges for businesses in the video surveillance industry that are trying to develop this sector and its capabilities. However, the rapid advances in cloud-based video surveillance applications, powered by artificial intelligence (AI) technologies, are disrupting established approaches and transforming systems from simple motion-based alerting devices to unified proactive and preventive solutions. 

When AI and video collide

The use of smart technology with video surveillance is creating a wealth of new opportunities for businesses to gather new insights more efficiently. AI technologies can automatically overcome many of the common performance limitations of existing solutions, including issues such as bad weather, changes in light levels and obscured images, and even detecting the motion of a person on-premises versus an animal. AI also removes the need for constant monitoring by employees during off hours, as it is able to precisely detect human activity in the live video stream and only sends relevant alerts for intervention as they’re required.

These capabilities are expanding every day, and they not only improve the speed of data analysis and the accuracy of the surveillance, but they also allow the technology to be applied to a much wider range of operational, efficiency and safety use cases than traditional CCTV. AI-enabled applications are introducing a huge range of options that can benefit businesses such as monitoring employee arrivals, the presence of intruders, vehicle detection, moisture detection on floors, and other smart features such as detecting loitering or when people are wearing masks. Because of these abilities, AI-powered surveillance has been – and will continue to be – applied to help organisations and their teams keep within the latest COVID-19 compliance guidelines.

When applied to video surveillance systems, AI technology can enable users to significantly broaden their use of intelligent analytics. In doing so, businesses can monitor and enhance existing operational processes or adopt innovative new capabilities that provide new insights. For instance, retailers can use AI-powered video systems to measure the impact of marketing campaigns on store traffic, identify buying trends, and understand customer preferences. It’s like the in-store equivalent of how analytics on retail websites track customers as they navigate the site. It offers them a powerful way to understand the effectiveness of their promotional campaigns and their wider in-store strategy, enabling teams to make changes if necessary in real time.

Retail security is another area in which this technology can make an impact. By integrating AI-powered surveillance with POS technologies, any suspicious transactions can be identified immediately and monitored for review and potential follow-up action. 

There are a huge number of markets that are adopting cloud-based video surveillance technology, with retail being just one example – banking, healthcare, government, hospitality and education are all markets powering significant growth in this area. As a result, global revenue from AI-powered surveillance analytic technologies is set to increase from $1.1bnin 2018 to $4.5bn in 2025, according to research from Omdia.

Adding cloud into the mix 

For all of these benefits of AI in video surveillance to be realised, cloud technology plays a huge part. Services hosted in the cloud are more convenient for most businesses – they’re typically cheaper, more reliable and more secure than the on-premises infrastructure often required to deliver and support legacy technologies. Scalability is also a popular benefit of cloud, which can be utilised at short notice and, by offering users an open platform, organisations can implement any additional third party technologies to meet their specific needs. 

This level of flexibility is crucial for expanding the wider application of AI in the video surveillance market. To increase this, outsourcing the platform and infrastructure to a specialist third party opens up the possibility for a greater range of services. This enables users to select whichever AI-powered functions most precisely meet their requirements. In addition, the impact of the COVID-19 pandemic has further increased the reliance organisations are placing on video surveillance technologies, driven by cloud-enabled remote access and monitoring capabilities that help organisations to increase efficiency and often reduce face-to-face contact. 

AI technology is driving innovation across many markets, and video surveillance is currently undergoing a full transform into a smarter, more impactful industry. Older and less efficient video systems are increasingly being updated for the latest innovations that are advancing the value for businesses. Because of this, video surveillance will not only continue to drive advances in safety and security, but will also deliver a greater business impact as AI and cloud together take this technology to new heights.

By Rishi Lodhia, Managing Director EMEA, Eagle Eye Networks 

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Jun 23, 2021

Google launches Visual Inspection AI tool for manufacturers

3 min
Google has launched Visual Inspection AI, a new Google Cloud Platform solution designed to help reduce defects during the manufacturing process

Google Cloud has launched Visual Inspection AI, a new tool to help manufacturers identify defects in products before they're shipped. 

Poor production quality control often leads to significant operational and financial costs. The American Society for Quality estimates that for many organisations this cost of quality is as high as 15-20% of annual sales revenue, or billions of dollars annually for larger manufacturers. Google Cloud’s new Visual Inspection AI solution has been purpose-built for the industry to solve this problem at production scale. 

How does it work? 

The Google Cloud Visual Inspection AI solution automates visual inspection tasks using a set of AI and computer vision technologies that enable manufacturers to transform quality control processes by automatically detecting product defects.

Google built Visual Inspection AI to meet the needs of quality, test, manufacturing, and process engineers who are experts in their domain, but not in AI. 

  • Run autonomously on-premises: Manufacturers can run inspection models at the network edge or on-premises. The inspection can run either in Google Cloud or fully autonomous on your factory shop floor. 
  • Short time-to-value: Customers can deploy in weeks, not the months typical of traditional machine learning (ML) solutions. Built for process and quality engineers, no computer vision or ML experience required. An interactive user interface guides users through all the steps. 
  • Superior computer vision and AI technology: In production trials, Visual Inspection AI customers improved accuracy by up to 10x compared with general-purpose ML approaches, according to benchmarks from several Google Cloud customers. 
  • Get started quickly, with little effort: Visual Inspection AI can build accurate models with up to 300x fewer human-labeled images than general-purpose ML platforms, based on pilots run by several Google Cloud customers.
  • Highly scalable deployment: Manufacturers can flexibly deploy and manage the lifecycle of ML models, scaling the solution across production lines and factories.

Industry use cases

The demo video shows how Visual Inspection AI addresses use cases to solve specific quality control problems in industries such as automotive manufacturing, semiconductor manufacturing, electronics manufacturing and general-purpose manufacturing. 

Kyocera Communications Systems, a manufacturer of mobile phones for wireless service providers, has been able to scale its AI and ML expertise through the use of the solution. “With the shortage of AI engineers, Visual Inspection AI is an innovative service that can be used by non-AI engineers,” said Masaharu Akieda, Division Manager, Digital Solution Division, KYOCERA Communication Systems. “We have found that we are able to create highly accurate models with as few as 10-20 defective images with Visual Inspection AI. We will continue to strengthen our partnership with Google to develop solutions that will lead our customers' digital transformation projects to success.”

Visual Inspection AI has fully integrated with Google Cloud's portfolio of analytics and ML/AI solutions, giving manufacturers the ability to combine its insights with other data sources. The tool integrates with existing products from Google Cloud partners, including SOTEC, Siemens, GFT, QuantiPhi, Kyocer and Accenture. 

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