Experimental Results on Agent-Based Indoor Localization using WiFi Signaling

This paper discusses experimental results on the possibility of accurately estimating the position of smart devices in known indoor environments using agent technology. Discussed localization approaches are based on WiFi signaling, which can be considered as an ubiquitous technology in the large majority of indoor environments. The use of WiFi signaling ensures that no specific infrastructures nor special on-board sensors are required to support localization. Localization is performed using range estimates from the fixed access points of the WiFi network, which are assumed to have known positions. The performance of two range-based localization algorithms are discussed. The first, called Two-Stage Maximum-Likelihood algorithm, is well-known in the literature, while the second is a recent optimization-based algorithm that uses particle swarm techniques. Results discussed in the last part of the paper show that a proper processing of WiFi-based range estimates allows obtaining accurate position estimates, especially if the optimization-based algorithm is used.