Computer Vision

Real-time insights through artificial intelligence and machine learning modeling

Sensormatic Solutions’ innovative computer vision technology delivers retail operational insights based on best-in-class deep learning artificial intelligence (AI) models. Our computer vision solutions are created in partnership with Intel and optimised for retail using Sensormatic IQ’s proprietary AI algorithms.

Each analytic is developed with our foundational pillars of retail success in mind, driving sales, reducing risk, optimising labour and enhancing the shopper experience.

Real-time insights on retail-specific use cases help you to make informed decisions and take a more proactive approach to problem solving.
Analytics can be added and removed easily, to help you focus on what is most important to your changing business needs. New analytics are continuously being developed to address front-of-mind retail challenges.
You have the capability to leverage your existing camera infrastructure and a smart hub device, which helps to make this technology cost effective and easy to deploy.

Computer Vision

Computer vision automates tasks and derives meaningful information from video footage in real time. Our wide range of computer vision analytics help you to strengthen your loss prevention efforts, gather insights for improved shopper experiences and maintain a safe environment for both shoppers and store assistants. Easy to deploy and powerful, computer vision analytics leverage your existing video infrastructure and a smart hub appliance to tap into the data you need to open up a world of problem-solving solutions across the retail landscape. All analytics are presented in a one-stop, consolidated dashboard for easy access to key metrics.

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360 degree video camera in ceiling of retail store
graphic representation of retail video surveillance camera

Watch the video to see how computer vision technology can provide powerful insights across the retail experience

Measurable Loss Prevention Outcomes

With shrink and organised retail crime (ORC) activity on the rise, retailers are looking for ways to combat these threats while optimising in-store labour usage. Our comprehensive suite of computer vision analytics can play an important role in loss prevention and in keeping an environment safe and secure. Computer vision analytics are developed specifically to address some of the most critical loss prevention issues today. Below are just a few of the analytics available.

video surveillance camera in aisle of retail grocery store

Shelf Sweep Detection

Many retailers are seeing an increase in shelf sweep activity, resulting in huge losses. With this analytic, shelf activity is monitored to capture occurrences of when a predetermined number of items are removed from a shelf at one time, so that in-store personnel can take pre-emptive measures to mitigate the theft.

You can also configure this analytic to provide an indication that specific items on a shelf need to be replenished. Plus, you can keep track of when a high-value item is removed from a shelf so you can keep a close eye on it, or offer the shopper extra customer assistance.

video surveillance camera in retail store with a group of shoppers blurred in the background

Group Detection Alert

Knowing when groups of people gather in a specific area or enter a store as a mob can be a game-changer in identifying and possibly diverting potential ORC or theft activity. Get real-time notifications of these occurrences for a more preventative approach.

several vehicles in a retail store parking lot in spots reserved for package pickup

Vehicle Alert

Making sure the parking area is safe and free from criminal activity is crucial to loss prevention efforts. With Vehicle Alert, you will be able to spot cars parked for time periods exceeding a predetermined amount of time or in an unauthorised area. This analytic can also provide average vehicle wait times for Click & Collect metrics.

overhead video surveillance camera in retail shopping mall

Loitering Monitoring

Criminal activity can often occur after normal business hours. With this analytic, lingering in low-traffic areas and after business hours are monitored and provide notification when loitering activity is detected.

Meaningful Shopper Insights

To stay ahead of the competition and provide shoppers with an outstanding in-store experience, retailers are always looking to better understand shopper behaviour and the shopper journey. With this information on hand, retailers can create the ideal environment and develop appropriate marketing plans that ultimately lead to increased sales. Our growing list of computer vision analytics can help you get a better handle on shopper traffic patterns, path to purchase, and even the demographics and sentiment of shoppers visiting your stores.

female shopper looking at cups and plates on a display in a retail store

Audience Measurement

Having insights into the demographics and sentiment of shoppers entering your store provides useful data to help you make decisions about marketing opportunities, content and advertising. This analytic provides the demographic and approximate mood of shoppers lingering in an assigned camera’s view for an extended period of time. Use these insights to develop more customised and targeted experiences.

video surveillance camera with false color heatmaps of shoppers in retail store

Traffic Pattern Insights

This analytic captures data on traffic patterns and helps you to observe the path-to-purchase of shoppers within your store. Shopper behaviour is better understood when data on dwell time, customer movements and traffic counts are known.

female shopper looking at display of makeup in a retail health and beauty store

Dwell Time Measurement

Dwell Time Measurement can help to capture the amount of time shoppers remain in a certain area, such as in front of an end-cap display, and can be a valuable tool in understanding the effectiveness of a marketing campaign or promotion.

Learn more about Computer Vision today.

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