## 2 Technologies for Indoor Localization
Smartphone sensors and low-signal Bluetooth beacons are also used in the indoor positioning solution proposed by Nextome [44], while an inertial engine with geomagnetic fingerprinting, sensor fusion and radiofrequency mapping is at the core of GIPStech's technology [45]. Finally, the integration of a Low-Power Wide Area Network (LPWAN) and a trilateration algorithm is the solution for a large-scale indoor localization system by Behr Technologies Inc. (North York, ON, Canada) [46]. In the following, localization and navigation solutions to be adopted in the Active and Assisted Living framework (AAL), aiming to assist frail people during the exploration of indoor environments, are detailed. In the case of AAL contexts, the need for very accurate indoor positioning solutions emerges, which should also fulfill the user acceptability requirement. More specifically, navigation assistive systems are in charge of getting awareness of surroundings and of the User-Environment Interaction, as well as to provide the user with suitable information (in terms of the contents, quantities and the form) that is useful for assuring safe mobility. To this aim, two main approaches have been investigated: Obstacle Detection and Location-Based Service. Solutions in these two classes can exploit different technologies, among those described above, to acquire information about the surrounding environment, such as ultrasonic, infrared, laser and cameras, RFID, wireless networks, etc. Moreover, auditory, tactile, electromagnetic and optical technologies are used to provide a form of feedback to end-users [47; 48; 49]. A case study related to an indoor localization system for AAL is presented in Section 3. For the sake of completeness, in the following, a basic background on related works available in the literature is reported. A CANBUS (Controller Area Network BUS) sensor network aimed to provide weak users (elderly or impaired people) with a continuous spatio-temporal form of assistance during the exploitation of indoor environments is presented in [50]. The system allows for a continuous update of the user's position within the environment (with an uncertainty of less than 10 cm) by a continuous interaction between a user worn module and a distributed ultrasound sensor network. Dedicated paradigms have been developed to provide awareness of the User-Environment Interaction (UEI), such as the presence of obstacles or services. Improvements to both the architecture and functionalities have been discussed in [51]. A Wireless Sensor Network (WSN) has been used to replace the CANBUS network, thus providing the architecture more flexibility and ease of installation. The main improvement is represented by the capability of the system of building awareness of the User-Environment Contextualization (UEC), which relates the user status by monitoring the user's inertial behavior (posture and dynamic) to the environmental status by checking the presence of hazards such as fires, gas leakages, smoke, etc. The information coming from the UEC and UEI tools is automatically processed by a Decision Support System (DSS) tool, which can provide optimal information to help the supervisor make decisions and perform actions to manage hazards or specific user needs. Indoor localization systems using other wireless technologies are known to have accuracies that are often not compatible with the task of tracking people in indoor environments with a high degree of accuracy.