Estimation of User's Orientation via Wearable UWB

User's orientation in indoor environments is an important part of her context. Orientation can be useful to understand what the user is looking at, and thus to improve the interaction between her and the surrounding environment. In this paper, we present a method based on wearable UWB-enabled devices. The position of the devices in space is used to estimate the user's orientation. We experimentally evaluated the impact of some operational parameters, such as the distance between worn devices, or some environmental conditions, such as the position of the user in the room. Results show that the accuracy of the method suits the needs of a wide range of practical purposes

Sensor Network-based and User-friendly User Location Discovery for Future Smart Homes

User location is crucial context information for future smart homes where a lot of location based services will be proposed. This location necessarily means that User Location Discovery (ULD) will play an important role in future smart homes. Concerns about privacy and the need to carry a mobile or a tag device within a smart home currently makes conventional ULD systems uncomfortable for users. Future smart homes will need a ULD system to consider these challenges. This paper addresses to design such a ULD system for context-aware services in future smart homes stressing on the following challenges: (i) users’ privacy, (ii) device/tag-free, and (iii) fault tolerance and accuracy. On the other hand, emerging new technologies such as Internet of Things, embedded systems, intelligent devices and machine-to-machine communication are penetrating into our daily life with more and more sensors available for use in our homes. Considering this opportunity, we propose a ULD system that is capitalizing on the prevalence of sensors or home while satisfying the aforementioned challenges. The proposed sensor network-based and user-friendly ULD system relies on different types of cheap sensors as well as a context broker with a fuzzy-based decision maker. The context broker receives context information from different types of sensors and evaluates that data using the fuzzy set theory. We demonstrate the performance of the proposed system by illustrating a use case, utilizing both an analytical model and simulation