WiFi-based localization became one of the main indoor localization techniques due to the ubiquity of WiFi connectivity. However, indoor environments exhibit complex wireless propagation... Show More

WiFi-based localization became one of the main indoor localization techniques due to the ubiquity of WiFi connectivity. However, indoor environments exhibit complex wireless propagation characteristics. Typically, these characteristics are captured by constructing a fingerprint map for the different locations in the area of interest. This finger print requires significant overhead in manual construction, and thus has been one of the major drawbacks of WiFi-based localization. In this paper, the authors present an automated tool for finger print constructions and leverage it to study novel scenarios for device-based and device-free WiFi-based localization that are difficult to evaluate in a real environment. In a particular, the authors examine the effect of changing the access points (AP) mounting location, AP technology upgrade, crowd effect on calibration and operation, among others; on the accuracy of the localization system. The authors present the analysis for the two classes of WiFi-based localization: device-based and device-free. The authors analysis highlights factors affecting the localization system accuracy, how to tune it for better localization, and provides insights for both researchers and practitioners.

The authors consider two untackled problems in RF-based activity recognition: the distinction of simultaneously conducted activities of individuals and the recognition of gestures from purely... Show More

The authors consider two untackled problems in RF-based activity recognition: the distinction of simultaneously conducted activities of individuals and the recognition of gestures from purely time-domain-based features. Recognition is based on a single antenna system. This is important for the application in end-user devices which are usually single-antenna systems and have seldom access to more sophisticated, e.g. frequency-based features. In case studies with software defined radio nodes utilised in an active, device-free activity recognition (DFAR) system, the authors observe a good recognition accuracy for the detection of multiple simultaneously conducted activities with two and more receive devices. Four gestures and two baseline situations are distinguished with good accuracy in a second case study.

This paper presents the concept of device-free indoor localization using only a passive receiver and ambient FM radio signals. Experimental results based on empirical measurements demonstrate the... Show More

This paper presents the concept of device-free indoor localization using only a passive receiver and ambient FM radio signals. Experimental results based on empirical measurements demonstrate the feasibility of the proposed approach. The authors also evaluate fine-grained localization performance of the system, its temporal stability, and highlight the role of frequency diversity for passive localization.

Indoor radio frequency tracking systems are generally quite expensive and can vary in accuracy due to interference, equipment quality or other environmental factors. Due to these limiting factors of... Show More

Indoor radio frequency tracking systems are generally quite expensive and can vary in accuracy due to interference, equipment quality or other environmental factors. Due to these limiting factors of the technology, many businesses today find it hard to justify investing in RFID tracking technologies to improve the safety, efficiency and security of their working environments. The aim of this project was to provide a budget RFID tracking system that was capable of tracking a person or object through an indoor environment. To minimize the cost of the RFID tracking system, the components of the system were built from existing electronic equipment and hardware. The software was also written to minimize licensing and support fees allowing a cost effective budget RFID tracking system to be developed. The tracking system consists of a tag, reader nodes and a PC reader which utilize synapse RF 100 engines with python scripts embedded on to the chips. The tracking system software operates through a web portal utilizing web technologies such as HTML, JavaScript and PHP to allow the tags location to be represented on a two dimensional map using scalable vector graphics. During development of the system a new trilateration algorithm was developed and used convert the signals received from the tag to a virtual position on the map correlating to the actual physical position of the tag. A unique contribution of this system is the low cost of building which we estimate as less than £200 UK sterling for a five node system.