On the Cutting Edge

On the Cutting Edge

Implementing AI for efficiency during growth and development

Video analytics (VA) continue to evolve in sophistication and are fast becoming standard in video surveillance devices and solutions. The rapid evolution of video analytics has also given way to the growing development and adoption of Artificial Intelligence (AI) and deep learning technologies in security applications. Capable of tapping into other information facilitated by sensors, including people counting, identity management, and heat mapping, an AI system can deliver end users much more information than traditional security applications ever could. These data gathering functions enhance operations and are providing new value for many end users, not only from a security standpoint, but from an operational one, as well.


Advanced AI modeling technology continually learns what a typical scene looks like. It significantly reduces false alarms because it can detect atypical events or motion and alert operators in real time to initiate an appropriate response.

Other AI capabilities, such as metadata filtering, are helping to speed up investigations considerably. Metadata filtering automatically recognizes objects, places and movements, and then extracts and stores metadata relating to every scene. This meta data provides classification, identity, and context to video streams, enabling operators to organize, search and retrieve intelligent information from massive amounts of video footage quickly and easily.

Additionally, people matching AI technology extracts the appearance characteristics of a selected individual and rapidly searches through hours of footage for the most similar matches from single or multiple recorded video streams.

Despite all these benefits, cost remains for some, one of the main stumbling blocks for AI adoption. Processing power is also another challenge. Initial solutions required complex server-based set ups, which put them out of reach of most organizations. Fortunately, price points are continuing to come down as new AI functionality becomes accessible through some existing VMS solutions and cloud-based applications. This, coupled with the fact that vendors are presenting clearer and more concise applications that address everyday challenges, is allowing increasingly more end users to leverage the benefits of AI capabilities.

According to The Hill, AI has been steadily on the rise, going from $12 billion in 2017 to a projected $60 billion in 2021. But that projection will likely increase exponentially in the midst of the COVID-19 pandemic. The rapid spread of the virus will inevitably trigger many enterprises – many of which are losing exorbitant amounts of revenue - to replace humans as a factor of production. Machines can’t be infected by the virus and therefore wouldn’t put a halt to production, disrupt the food supply chain or other manufacturing processes. They also don’t need to socially distance.


Health guidelines dictating that people maintain a six foot distance apart from each other are impacting so many facets of our daily lives, both personally and professionally. Everyday function as simple as going to the grocery store now require guards at the entrances to space people apart and admit a limited number of shoppers at a time. Many companies won’t be able to sustain the cost of guards and security staff to enforce social distancing over a long period of time. It is expensive. The automation of processes via analytics will surely be an attractive, more affordable solution.

Especially important in battling the spread of COVID-19 is the ability to combine facial recognition and fever detection AI. Thermal cameras have been used for a while now to detect people with fever.

Cameras equipped with AI-based multi-sensory technology are being used in myriad facilities including airports, hospitals and nursing homes. The technology automatically detects people with a fever, tracks their movements, recognizes their faces and detects whether they are wearing a face mask.

In addition, intelligent drones and robots are being deployed increasingly more to monitor adherence to the strict social distancing measures required to curb the spread of the virus. To further enforce compliance, some drones are being used to track people not wearing face masks in public, while still others are being employed to broadcast information to large gatherings of people. Some are actually even being used to disinfect public spaces.

There will, undoubtedly, be a surge in demand for simpler, more cost-effective heat mapping and people counting to ensure social distancing – be that in retail, warehousing/distribution centers, schools and universities, public gathering places and the list goes on.

Organizations that may not be able to budget for a sophisticated new VMS with AI will likely look to leverage the surveillance investment they already have with a simple add-on. Simple devices such as people counting products, for instance, offer many benefits. In addition to helping to enforce social distancing, they can provide insights to define marketing and operational strategies, and data to inform key business decisions. In-demand capabilities will likely include passive staff detection, dwell time measuring and the ability to connect multiple units to cover wide openings.


Many end users are already employing simple but cost-effective ‘blob’ type analytics, which typically includes images, audio or other multimedia objects, and appliances to meet their operational requirements. These are now commonplace in many applications, as analytics cameras and plug-and-play appliances have proven cost-effective and easy to deploy.

To even better leverage the benefit of AI, the onus is on manufacturers and systems integrators to help customers understand their biggest pain points and challenges. System integrators should explain to their customers how they can operate more efficiently, while continuing to reduce risks, increase safety and meet compliance and duty of care requirements.

Although customers have rapidly adopted onboard analytics, they can deliver false positives in the control room caused by weather or other environmental factors. This can get problematic, especially for large sties as it can lead to monitoring teams either responding inefficiently to false alarms or simply shutting down alerts altogether, potentially missing critical incidents.


It is in these types of environments that deep learning applications are already delivering significant benefits and rapid ROI. They learn from experience and significantly outperform human performance with the capability to analyze vast amounts of data points taken from video footage across single or multiple cameras simultaneously. This allows AI applications to first detect and then identify an event or threat, while filtering out false alarms and, in turn, making first responders far more efficient and ensuring critical incidents are never missed.

The value of and applications for artificial intelligence will inevitably continue to expand, both in general as well as in response to battling COVID-19. While nothing can ever replace the value of human intelligence and decision-making, having AI in the arsenal can surely aid in the fight and help in winning the war on this invisible enemy.

This article originally appeared in the July / August 2020 issue of Security Today.


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