Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : WSN

Distance Estimation Based on RSSI and Log-Normal Shadowing Models for ZigBee Wireless Sensor Network

Salim Latif Mohammed

Engineering and Technology Journal, 2016, Volume 34, Issue 15, Pages 2950-2959
DOI: 10.30684/etj.34.15A.15

In the last few years, a mobile wireless sensor and its application in wireless sensor network (WSN) are commonly used. Localization of a mobile sensor node is considered a critical issue in some WSN applications. In this paper, an outdoor environments experiment was carried out to measure the distance between the mobile node and the coordinator node in a simple point-to-point ZigBee WSN. The distance was determined based on the measured Received Signal Strength Indicator (RSSI) of the mobile node by the coordinator node. In addition, a Log-Normal Shadowing Model (LNSM) was derived for outdoor condition. Moreover, the parameters of the propagation channel such as standard deviation and a path loss exponent were estimated. The RSSI was measured and analysed for outdoor environments for a distance range 1-100 m. The measurements were carried out by using 2.4 GHz ZigBee wireless protocol based on XBee series 2 modules.
The results disclosed that the mean absolute error (MAE) of 3.44 and 6.72 m for a distance range 0-65 m and 0-100 m, respectively. These results point that the LNSM is only suited for short distance.

Hardware Implementation of Wireless Sensor Network Using Arduino and Zigbee Protocol

Mahmood F. Mosleh; Duaa SH. Talib

Engineering and Technology Journal, 2016, Volume 34, Issue Issue 5 A, Pages 816-829
DOI: 10.30684/etj.34.5A.1

This paper presents a designed and implemented Wireless Sensor Network (WSN) based on Arduino and IEEE 802.15.4/Zigbee standards. This network consists offour end nodes; each one is connected to an individual type of sensors (lighting, temperature, motion, and distance) to form a safety network for building offices, factories, homes…etc. Also there is a fifth node in this network to collect the information from each node and send it to the base station which is a computer to be process the data and take the appropriate decision according to the program established by the user. Results confirmed that the network performs its functions with high efficiency and gave accurate readings of the surrounding circumstances. Stable reading of temperature and lighting had been achieved in the implemented network. Also, the motion and distance sensors gave good results depending onthe presence ofobjectsclose tothemore peoplemovingnear. In addition, the network is characterized by high flexibility and ease of programing that can be used to give various applications such aswarning of fire by setting a threshold level of temperature to enable an alarm when exceeding such level. It can also be used to preventtheftsbydetectingmovements ofthe humanbody with distance sensor. Inaddition, other uses can be implemented such as controlling heating and lightingdevicesin homes andotherbuildings.