May 11, 2020 dscull 0 Comments

Using analytics to better respond to crowd flow and occupancy levels

Today’s current climate is forcing businesses and organizations to rethink how they operate as they follow the lead of state and federal governments regarding social distancing orders. How can these businesses ensure customers are following social distancing and occupancy limits, as well as other security and safety guidelines, while still efficiently serving their needs? The answer utilizes pos technology for occupancy detection.

Over the past several years, more and more businesses and organizations have been implementing analytics to gain insights into how people are behaving within a confined space. Occupancy detection and people counting analytics, for example, coupled with network cameras can provide real-time data on how many people are present on premise or in a certain area of a store at a specific time. This can help businesses optimize floor layouts to reduce lingering in aisles, help customers find what they’re looking for quickly and expedite the in-store buying process.

On a more general level, this technology can help facilities take measures if occupancy exceeds their threshold or if certain areas are more congregated than others. With occupancy detection technology businesses can analyze individual sites—even remotely—and quickly compare performance across multiple locations, helping them efficiently measure traffic.

Beyond this, businesses need to weigh the cost of implementing this type of network surveillance solution. Edge-based applications that sit within each installed camera reduce bandwidth and storage requirements and thus the needs for expensive servers.

While the current situation has brought to light many new challenges and placed a greater spotlight on existing ones, what we know is today’s network surveillance technology can serve as a valuable tool now and well into the future.

Please feel free to contact us to learn more about implementing this type of solution.

Occupancy Detection was last modified: July 7th, 2020 by dscull