Combined Human, Antenna Orientation in Elevation Direction and Ground Effect on RSSI in Wireless Sensor Networks

In this paper, we experimentally investigate the combined effect of human, antenna orientation in elevation direction and the ground effect on the Received Signal Strength Indicator (RSSI) parameter in the Wireless Sensor Network (WSN). In experiment, we use MICAz motes and consider different scenarios where antenna of the transmitter node is tilted in elevation direction. The motes were placed on the ground to take into account the ground effect on the RSSI. The effect of one, two and four persons on the RSSI is recorded. For one and two persons, different walking paces e.g. slow, medium and fast pace, are analysed. However, in case of four persons, random movement is carried out between the pair of motes. The experimental results show that some antenna orientation angles have drastic effect on the RSSI, even without any human activity. The fluctuation count and range of RSSI in different scenarios with same walking pace are completely different. Therefore, an efficient human activity algorithm is need that effectively takes into count the antenna elevation and other parameters to accurately detect the human activity in the WSN deployment region.Comment: 10th IEEE International Conference on Frontiers of Information Technology (FIT 12), 201

Mobile Indoor Positioning for Augmented Reality Systems

This thesis explores the creation and setup of a prototype that allows users of the device to interact within an indoor real world environment and a virtual environment simultaneously using high-tech common technology. The prototype is comprised of a small mobile device such as a cellular mobile phone, Raspberry Pi computer, a battery powered handheld Pico projector, and software developed for the Android OS. The software can easily be ported to other mobile and non-mobile operating systems. The mobile device must contain accelerometer, magnetometer, and gyroscope embedded sensors as well as 802.11 wireless network chip. The prototype software implements an indoor positioning system to track the current location and orientation of the prototype device in real time. It also displays a virtual world projection upon the surfaces of the real world in relation to the prototype’s physical location and orientation. Three different orientation estimation methods were tested and compared in this thesis. Accelerometer and magnetometer based method, gyroscope based method, and a combined method using a technique called sensor fusion were implemented. A multilateration approach was used for location estimation. Location estimates were calculated from the measured received signal strength of multiple 802.11 wireless network access points. The location of all wireless access points were known and fixed. Received signal strength data was converted to meters using a log distance propagation model, and tests were conducted to compare actual distance with converted distance. Tests were also conducted to compare multilateration estimates from unfiltered or raw RSS and filtered RSS data using a Kalman filter