Theft prevention with video analytics

The most common method for deterring and identifying theft is currently CCTV cameras. 54% retailers have said that CCTV systems have significantly reduced theft and fraud by staff and contractors. However, they have limitations, and theft cost UK retailers £2.2 billion and US retailers nearly $62 billion in 2019. 2020 also made retail stores a target for theft due to the lack of occupancy.

Video analytics is highly effective in preventing theft swiftly. It can help eliminate shoplifting, employee theft, and fraud as well as prevent security incidents such as intrusion, trespassing, and other suspicious activities.

Video analytics can be set to alert staff in real-time when someone has spent an unusual amount of time in store or is behaving suspiciously. Staff can then decide to continue to monitor the individual or speak with them.

Suspicious activity will be defined by you, the retailer. Using this, video analytics can alert you when someone is trespassing, moving too fast, or simply prioritise a live feed on high-risk areas, such as the cash registers or places with no staff members.

Overtime, machine learning will be able to identify the behaviours of shoplifters and even assign danger levels. For high level threat, it can alert the authorities without the knowledge of the shoplifter. Pre-emptive alerts for potential dangers can save retailers a lot of stress and money by detecting fraud and shoplifting before they occur.

For example, many retailers have alerts for when someone is trying to break in. With the power of analytics, you can be alerted before the incident. You can mark zones for alerts which the trespasser will have to pass in order to break in, giving you time to take action (you will have to set the parameters cleverly so not miss things with too narrow a parameter, or receive too many notifications with a large parameter).

Such zone markings can also be used in other no-go areas, such as the cash registers, stock room etc.

Moreover, as it often happens, a thief may attempt to cut wire, break, or spray paint the camera before attempting theft. In such occasion, the AI system can automatically send notification to security and management teams in real time so they can take action swiftly.

In the long run, the automation offered by video analytics is the best tool for retailers to tackle shoplifting.Where it would take a human hours and hours, the AI can scan huge amounts of data in seconds and detect suspicious behaviour. Furthermore, using existing CCTV systems whilst adopting AI video analytics is also saving retailers from purchasing expensive hardware or even hiring security staff.

For more information on AI video analytics, please visit https://trackin.tech/

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