A huge part of the emerging Internet of Things (IoT) applications can significantly benefit from context awareness, in particular location awareness. This information might pertain to the location of the user, to the location of devices/appliances or both of them and hence enable a lot of powerful applications, for example, in hospitals to track equipment, doctors, and patients or in industrial environments to track and trace persons and assets. However, IoT research rather focuses on architectures, which includes components for context awareness, but pays less attention to how and with which accuracy context is achieved.

Many algorithms and approaches have been proposed for indoor RF-based localization; however, low cost and accurate indoor localization is still very challenging. Many research and commercial solutions claim very high accuracies, which can, however, only be achieved in a very specific setting under ideal conditions. Adbanticsys Research Department is working on the development of cost-effective indoor localization solutions in real-life environments such as warehouses or underground mining sites.

Philips, Siemens, Fraunhofer