All Systems Operational 

At the Edge of The Retail Industry

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IoT has already proven itself extremely beneficial in the retail sector across multiple applications from delivering efficiency in energy consumption to monitoring stock levels in real-time.
The-benfits-of-edge-computing-for-real-time-loss-prevention

However, the latest area in which IoT technology is demonstrating real potential is loss prevention by utilising edge computing.

Edge computing refers to an on-premise IT infrastructure that is outside of the datacentre where they would typically be housed. This distributed computing paradigm brings computation and data storage closer to the location where it is needed rather than all data being stored centrally in the cloud. The edge exists wherever the digital world and physical world intersect, and data is securely generated, collected and processed to create new value.

Our loss prevention solution helps reduce loss by capturing customer interactions to provide real-time insight on loss. It enables both people and object detection using machine learning which occurs at the edge. So, instead of the footage from a security camera streaming to the cloud for analysis, it is done in the connecting gateway.

Why Use Edge Computing?

Processes images on the edge – Our solution uses AI specialised chips that are trained to specifically detect objects in images within the edge device rather than sending the data to the cloud. This is both more time and cost efficient. It takes less time for the footage to be analysed and means less storage is needed as the gateway only relays certain data to the cloud.

Speed – The process of transmitting data to distant data centres for analysis introduces latency, whereas edge computing processes data closer to the source and reduces the amount of data flowing to and from the primary network, leading to a faster overall speed and making real-time detection possible. As real-time detection occurs at the edge, on location, it only requires minimal bandwidth.

Reliable Performance – On-premise infrastructure assets for edge computing provides more reliable performance and connectivity to keep systems operational even if internet connectivity fails.

Privacy– No video or image data or personally identifiable information leaves the edge device. Encrypted video frames are transmitted to the gateway where the information is held in accordance with industry-standard security protocols.

Interoperable – Our solution can tie into current edge devices, which in a retail context could be sensors or cameras. The solution works with IP camera’s which are commonplace within many retail stores, reducing implementation costs.

Non-invasive – Customer experience is pinnacle to the retail, so any introduction of new technology needs to ensure it doesn’t interfere with a visitor’s experience in a detrimental way. Our solution is practically unidentifiable to any customer in a store and no distinguishable information is stored.

In terms of security, urgency is everything. Edge-based machine vision is able to offer real-time loss prevention analysis and detect suspicious behaviour or anomalies immediately and instantly notify security personal. This enables retailers to prevent loss before it happens.

If you would like to better understand how edge-based machine vision can revolutionise your loss prevention strategy, then get in touch.

Andrew Hathaway
Andrew Hathaway
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Further Reading

clothing rail in retail store

Post-Covid Retail is Battling 2 Major Issues: Does IoT Solve Both?

It’s interesting isn’t it, how a single industry, like retail, can be simultaneously faced with two completely opposing challenges? On one side of the spectrum, the typical grocers are having to tackle rapid spikes in bulk buying alongside big-spending seasons, which results in supply chain and stock issues.

Read More

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