Data is the new oil. The adage, coined by the UK mathematician Clive Humby in 2006, refers to how, like oil, data must undergo a refinement process before it can be put to real use. It is the raw material capable of powering innovation. For this reason, data is a strategic asset for any organization today. It promises to enhance every aspect of business – from customer experience to product design to sales strategy.
Massive amounts of this data come from the plethora of CCTV and IP cameras operating throughout enterprises and public arenas. Adoption of these cameras is being driven by a growing interest in smart cities, IoT, cloud, and industry 4.0. At the same time, advancements in AI have improved the ability to extract actionable insights from this raw video data – to process it and refine it – leading to a surge of opportunities to develop smarter applications and more innovative use cases.
One such advancement is intelligent video analytics, a set of computer-vision-based AI technologies that uses deep-learning neural networks to analyze videos and “learn” to identify objects, people, activities, emotions – in real time or post facto. This paper explores six key use cases of intelligent video analytics across industries such as retail, healthcare, and manufacturing.
Why regular analytic techniques fall short
Video analytics has huge growth potential, but it is still an emerging field. A 2018 IPVM survey shows more than half of the companies polled use video analytics sparingly or not at all, and fewer than one in five report using them often.
Most enterprises today use some kind of data analysis to make key decisions, but they may be missing out on valuable insights by not exploring video analytics. AI-powered video analytics can capture more data from day-to-day business operations, leading to more insights and more informed business decisions.
For example, a retailer might traditionally use PoS data to learn about customer behavior, restricting them to transaction statistics and sale logs. AI-powered video analytics can reveal how customers interacted with the entire store – time spent in each section, average wait time for checkout, even interest in products they liked but didn’t buy.
The manufacturing floor can be dangerous for workers, and supervisors can have a hard time identifying potential anomalies. An AI-powered system can help monitor video feeds and trigger an appropriate action based on insights thus improving product quality and worker’s safety.
Thankfully, organizations across industries are gradually realizing the power of intelligent video analytics. Last year, the video analytics market size was valued at $4.10 billion and is projected to reach $20.80 billion by 2027, growing at a CAGR of 22.7% from 2020 to 2027.
Deriving value from intelligent video analytics: Six key use cases
Traditionally, increasing security threats and the need for advanced surveillance have driven demand in the video analytics market. Recent advances in AI and machine learning, big data, edge computing and specialized multi-spectral camera hardware have increased adoption of AI-powered video analytics to move beyond providing basic security and surveillance. These advances have increased adoption of AI-powered video analytics to move beyond providing basic security and surveillance to strengthen operations and improve customer satisfaction.