Grocery Store Surveillance

The strength of artificial intelligence (AI) technologies is that they empower users to see both the big picture as well as the granular details: AI can make sense of Big Data and business analytics, so that companies can forecast and plan predictively based on actionable intelligence about consumer behavior, supply streams or staffing activity.

Another example of how grocery stores can enhance existing infrastructure with AI technology for data-driven decision making is Video Content Analytics: Many grocery stores have already deployed video surveillance systems for security purposes, such as monitoring various areas of a store or warehouse, and reviewing footage for post-incident investigations. Video content analytics software driven – based on deep learning – enables grocery stores to maximize their existing investments in video surveillance by making video searchable, actionable and quantifiable. Leveraging video content analytics, grocery stores can more effectively prevent inventory loss, improve store layout, streamline the purchasing and stocking of goods and, ultimately, improve the customer in-store experience.

According to the National Association for Shoplifting Prevention, more than $13 billion of goods are stolen from retailers each year. That’s more than $35 million per day. And it isn’t always customers who engage in this type of behavior. Employees account for 42.7 percent of inventory shrinkage in retail. Surveillance cameras help to prevent employees from taking advantage of their positions and pocketing money or other goods.

Surveillance footage is also a powerful fraud deterrent. If someone were to claim they fell and were injured in your store, video footage of the event provides an unbiased, visual record that will help to support or refute their claim that you are at fault.

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