AI in the Aisles: Redefining Internal Theft Prevention with Video Analytics

Question:

Our leadership has recently revisited the issue of internal theft, a concern that hasn’t been addressed since 2018. The impetus for this is a perceived shortfall in profits during the quarantine period, prompting a shift in focus towards internal loss prevention, especially given the reduced customer footfall.

The task at hand is daunting, with over 300 stores to oversee. Our previous efforts in 2018 to scrutinize video footage for employee theft were incredibly time-consuming, taking three months to complete.

In an effort to streamline this process, I’ve suggested to my superiors the potential adoption of video analytics software. Having perused security publications and international exhibition vendor lists, I’m now seeking to validate the capabilities and limitations of current video analytics technology from professionals in the field. While VMS providers like BriefCam showcase impressive demos, I seek confirmation that such functionality is not only possible but also effectively implemented by reputable VMS manufacturers.

Specifically, is it feasible to identify an individual based on their attire and rapidly pinpoint their appearances across the video network within seconds? Furthermore, could you provide an indication of the cost per channel? Given the multitude of cameras across our stores, a cost estimate is crucial for my proposal to the management team.

Your insights would be invaluable, and I thank you in advance for your assistance.

Answer:

The task of overseeing more than 300 stores is indeed formidable. The previous manual review of video footage for employee theft in 2018 was a laborious process that spanned three months. This is clearly not a sustainable approach, especially when time is of the essence.

The potential solution lies in the adoption of video analytics software. This technology has seen significant advancements in recent years, particularly with the integration of artificial intelligence and machine learning. Video analytics can automatically recognize temporal and spatial events in videos, which includes identifying individuals based on their clothing or other attributes.

However, there are limitations to consider. The accuracy of video analytics can be affected by factors such as video quality, lighting conditions, and environmental complexity. While the technology can drastically reduce the time needed to review footage, it may not always provide instant results and could still require human oversight for complex scenarios.

As for the cost, it varies widely depending on the features required, the number of channels, and the specific software chosen. Some providers offer pricing on a per-year or per-month basis, while others may require a custom quote based on the scale of deployment. For a rough estimate, prices can start from around $5,000 per year for a building or $47 per month for a channel, but these figures can fluctuate greatly.

In conclusion, video analytics software offers a promising avenue for addressing internal theft efficiently. It can potentially identify individuals rapidly and streamline the loss prevention process. However, it’s crucial to understand its capabilities and limitations, as well as the associated costs. With careful consideration and the right technology partner, video analytics can be a powerful tool for any security department aiming to protect its assets more effectively.

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