Updated: May 3
Part 2: The Competitive Advantages of AI Video Analytics
AI video analytics can offer enormous benefits to businesses using new or existing IP cameras. In part 2 of the AI Video Analytics 101 series, we will be highlighting the competitive advantages of video analytics technologies in extracting people’s demographic information and their behaviours in physical facilities in comparison to other people tracking technologies.
Passive and automated analysis
Wi-Fi trackers or beacons, two widely adopted people tracking technologies, often require visitors to contribute before they can begin to collect data on visitors, such as connecting to a network. For this reason, such technologies typically collect less than 60% of people traffic data as not all visitors will complete the necessary opt-in process. On the other hand, AI video analytics technologies use surveillance cameras to capture visitors’ behaviours and engagement and therefore do not require any action from either the business or visitor, making it a fully passive and automated data collection approach.
Accurate data and fine-grained localization for large scale analysis
As most facilities have an extensive network of surveillance cameras, AI video analytics technologies have a comprehensive view of traffic flow, visitor behaviour and engagement across the entire space. Moreover, if the video analytics technology provider trains their AI and computer vision algorithms with real-world video images, where ambient conditions, image resolutions, camera types, and angles vary then the system reliability and accuracy of the analyzed data significantly increase.
The localization accuracy, meaning the technologies’ ability to accurately find the location of people within a space, is also another benefit of AI video analytics. Unlike wi-fi trackers that have a localization accuracy of 5 meters for an analysis zone that can be as small as 40-50 meters, video analytics technology has a localization accuracy of 30-50cm for an analysis zone as small as 1-2 meters. The fine-grained localization of people and their movements will allow businesses to accurately analyze and predict crowd behaviour in critical areas like an airport check-in zone for the waiting time and the prediction of the queue size. With a more accurate and reliable data source, businesses can spend less time validating and fixing errors, and more time building data-driven strategies that maximize operational efficiency, increase revenue and rapidly generate ROI across key business objectives.
Figure 1. The efficiency of AI video analytics: various points of interest can be covered under one camera view.
In addition to providing more accurate quantitative data on people traffic like counting and occupancy monitoring at the entrance area than other people tracking technologies, AI video analytics also introduces more qualitative and comprehensive insights within the facility, such as demographic analysis, visitor journeys, dwell time, time spent in certain areas, the conversion rate between multiple points of interest, providing businesses operating in the physical spaces with a 360-view into critical business operations and visitor behaviour insights. With more comprehensive qualitative insights, decision-makers will be more realistic and reflecting businesses’ challenges and address them more effectively, increasing the level of confidence in their decision making, the potential outcome and its ROI. Moreover, with deeper insights on customers’ needs through qualitative analysis, organizations can uncover new business development opportunities and revenue streams.
Cost-effective and extendable SaaS model
By reusing a facility’s existing surveillance camera infrastructure, AI video analytics technologies require minimal hardware set-up and investment. Moreover, due to the localization accuracy of video analytics technologies allowing one surveillance camera to cover multiple points of interest as shown in the picture above, the cost of hardware is significantly lower than other people tracking technologies, allowing for a cost-effective and quick deployment at scale. Furthermore, in addition to providing people behaviour and demographic analysis, AI video analytics can be seamlessly extended to additional AI software capabilities in a SaaS model, such as intelligent safety analysis or social distancing analysis while reusing the same hardware. This is particularly useful in situations where there is a need for effective large-scale screening and public safety monitoring solutions in physical facilities in a short period of time. Such agile safety features can provide government and private sectors with the means to monitor public behaviour and key health indicators to ensure preventive measures are in-placed with minimum effort and investment in a very short period.
About the AI Video Analytics Series
In this series, C2RO shares their expertise, as a thought leader and recognized pioneer in AI video analytics technology, on how AI-powered video analytics (e.g., AI Video Analytics) is transforming indoor physical spaces by providing businesses into a 360-degree view into people behavior and business operations insights. In part 3 of this series, we are going to discuss why data privacy compliance is critical for AI video analytics. A video analytics technology that offers aggregated and anonymous insights while being fully compliant with data privacy regulations, will not only build trust among the public and potential customers of a business but also enable the widespread adoption of the technology in various market segments.