Energy-Efficient Time-Stampless Adaptive Nonuniform Sampling

Nowadays, since more and more battery-operated devices are involved in applications with continuous sensing, development of an efficient sampling mechanisms is an important issue for these applications. In this paper, we investigate power efficiency aspects of a recently proposed adaptive nonuniform sampling. This sampling scheme minimizes the energy consumption of the sampling process, which is approximately proportional to sampling rate. The main characteristics of our method are that, first, sampling times do not need to be transmitted, since the receiver can compute them by using a function of previously taken samples, and second, only innovative samples are taken from the signal of interest, reducing the sampling rate and therefore the energy consumption. We call this scheme Time-Stampless Adaptive Nonuniform Sampling (TANS). TANS can be used in several scenarios, showing promising results in terms of energy savings, and can potentially enable the development of new applications that require continuous signals sensing, such as applications related to health monitoring, location tracking and entertainment

Three dimensions positioning based location tracking tehcnique for indoor environment

Traditional tracking system with Two Dimensions-image (2D-image) standard presents only few and dull information to users. In addition, 2D localization only supports one level platform (i.e. horizontally). Thus, the Three Dimensions (3D) location tracking system has been developed to support multilevel building. The aim of this research is to develop a positioning based indoor tracking system with 3D locations which are able to provide more useful location tracking information to users using radio signals. In this research, a Wireless Fidelity (Wi-Fi) based indoor location tracking approach is introduced. We used the existing Wireless Local Area Network (WLANs) attached devices called the Access Point (AP) to the edge of the wired network. Mobile Node (MN) communicates with the three APs to receive signals. The Receive Signal Strength Indicator (RSSI) is used to calculate the distance between MN and APs. To determine the location of the MN the trilateration method is used. Finally, the database file is developed to store all the results calculated by the location server. The location tracking system is able to detect positions of MN without using Global Positioning System