Radio Tomographic Imaging for Ambient Assisted Living

Abstract

Abstract. Accurate localization of people in indoor and domestic environments is one of the key requirements for ambient assisted living (AAL) systems. This chapter describes how the received signal strength (RSS) measurements collected by a network of static radio transceivers can be used to localize people without requiring them to wear or carry any radio device. We describe a technique named radio tomographic imaging (RTI), which produces real-time images of the change in the radio propagation field of the monitored area caused by the presence of people. People's locations are inferred from the estimated RTI images. We show results from a long-term deployment in a typical single floor, one bedroom apartment. In order to deal with the dynamic nature of the domestic environment, we introduce methods to make the RTI system self-calibrating. Experimental results show that the average localization error of the system is 0.23 m. Moreover, the system is capable of adapting to the changes in the indoor environment, achieving high localization accuracy over an extended period of time.

Simulating a Multi-Vehicle Traffic Sensing System Based on Radio Tomographic Imaging

“…As demonstrated by Bocca et al [2], a higher (lower) fade level generally leads to less (more) RSS link variance. Positive (negative) fade level links are referred to as anti-fade (deep fade) links, as a result of constructive (destructive) multipath interference at the receiver.…”

“…The researchers used the Texas Instruments (TI) CC2531 transceiver that communicates through the ZigBee protocol [9] in the 2.4 GHz ISM band, so the simulation model is based on the ZigBee protocol (which relies on the IEEE 802.15.4 standard) and the transceiver's properties. The simulation model is also based on the RSS dynamics outlined by Bocca et al [2]. Furthermore, this section shows how the simulation model can be utilized to implement and evaluate the performance of the proposed RTI system.…”

“…These curves were found by ignoring some of the data in the higher variance levels on the positive fade level side. This data was regarded as outliers, because they do not explain the behavior as described by Bocca et al [2]. Curve (1) …”

“…The procedure described in this subsection contains three stages and was repeated for every network scan, as it changes the RSS data according to the behavior described by Bocca et al [2].…”

“…RTI is an emerging and promising technology. Recent relevant RTI research were presented by [2], [3].…”