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Understanding the Three Levels of Location: Presence, Proximity and Positioning
To maximize ROI when utilizing the Internet of Things, invest in an RTLS solution that covers all levels of accuracy and multiple use cases, and that will be scalable for future growth.
Using the warehouse example, approximate location information may be adequate. With the Bluetooth/AoA system, locators can be placed in strategic areas within the warehouse to identify tracked items as they enter certain areas, generating real-time location information by zone. In a well-designed deployment, where locators are positioned at strategic choke points, basic movement tracking also becomes available. Optimizing the infrastructure deployment and locator density to enable higher location accuracy only where needed helps with budget concerns without limiting potential use cases.
Other technologies commonly used for proximity-level location accuracy are Wi-Fi and Bluetooth received signal strength indication (RSSI)-based beaconing, but their weakness lies in their inflexibility to allow for deployments with a non-uniform locator density for optimizing the accuracy across the different zones.
Ultra-wideband (UWB) is also being used for use cases requiring this high level of location accuracy. However, UWB cannot be adapted to also cover both proximity and positioning requirements, limiting its effectiveness as a solution that covers all use cases. The high cost of tags and the limits to radio certifications across different geographical areas also limit UWB's usability as a positioning solution.
As seen with the warehouse example, organizations of all types and sizes—ranging from manufacturing and supply chain and logistics to health care and retail—have a wide variety of use cases in which knowing the location of an object or person provides tremendous value. The level of accuracy, however, depends on the specific use cases currently in use, as well as those that might be considered in the future. Investing in an RTLS solution that covers all levels of accuracy and multiple use cases, and that is scalable for future growth, can help organizations minimize TCO and maximize their return on investment (ROI).
Fabio Belloni is the chief customer officer and cofounder of Quuppa, which is focused on accelerating the success of its partner companies. He is a frequent contributor and the author or co-author of numerous academic papers, and has several granted patents and pending patent applications.
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