A novel approach to indoor RSSI localization by automatic calibration of the wireless propagation model

Context-aware systems unobtrusively assist people by predicting their needs. This prediction is often based on context information acquired from the environment. To this purpose we envision an assisted living supportive (also called Ambient assisting living AAL) scenario in which various embedded device (like sensors, actuators, display, and wireless medical devices) either operate independently or are coordinated under the local intelligence node. AAL is currently seen as the next evolution step in the information society. Thereby the computing science is being widened from stationary systems to ubiquitous, smart, and human-centric systems. In other words all systems are intelligent computer systems, which are not invasively embedded in the human environments, with the goal to improve the lifestyle based on the individual human needs. The first efforts to introduce context-awareness have been related to the localization of users [1], [2], [3], [4] and up to now localization is still one of the main building blocks of AAL architectures. The general solution based on Global Positioning System (GPS) is unfortunately available only in outdoor environments. In AAL scenario a viable solution to localization of users exploits wireless sensor networks. Sensor network-based solutions can estimate the (unknown) location of mobile sensors (placed on the users) with respect to a set of fixed sensor (called anchors), whose position is known, by using two different approaches, range-based or range-free localization schemes. The former is defined by protocols that use absolute point-topoint distance estimates for calculating location. The latter make no assumption about the availability or validity of such information.