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2. PHD Thesis / Tesis PHD
3. Faculty of Engineering and Built Environment / Fakulti Kejuruteraan dan Alam Bina

Title:	Effective algorithm for internet trade with drone networks and warranties
Authors:	Haider Mahmood Jawad Abu-Alshaeer (P83589)
Supervisor:	Rosdiadee Nordin, Assoc. Prof. Ir. Dr.
Keywords:	Universiti Kebangsaan Malaysia -- Dissertations Dissertations, Academic -- Malaysia Algorithm Internet Drone
Issue Date:	19-May-2020
Description:	Wireless sensor networks (WSNs) play a vital role in the future of agriculture through the Internet of Farming. By deploying sensors, farmers can understand their crops at a micro scale, conserve resources, and reduce impacts on the environments. However, employing WSNs in agriculture poses several challenges, especially on energy efficiency. Energy efficiency is important to prolong the lifetime of the sensors on the farm, thus reducing the operational cost for the future modern farmer. This work aims to improve the energy efficiency by developing a data transmission scheme for wireless sensor and router nodes in a farm field based on ZigBee. The drone is utilized in this research to further extend the communication range. However, using drones introduced other limitations, such as short flight time and battery life, in addition to the needs for a battery charging facility. The objective of this research is to increase the energy efficiency of the agriculture sensor and router nodes based on the Sleep/Wake Redundant Data scheme, abbreviated as SWORD. The power consumption and battery life of the drone were formulated mathematically and were later improved through sleep/active strategy. These two different techniques (SWORD and solar cell) are eventually integrated and validated to form an autonomous energy-harvesting platform in a farm. In this study, the drone becomes a mobile router to relay the agriculture sensor parameters from the sensor node to the coordinator node while extending the communication range within a farm field. The path loss between the agriculture sensor and the router nodes was modeled and derived based on the received signal strength (RSS) measurements in the farm field. To predict the path loss effect, the use of particle swarm optimization (PSO) algorithm is considered. A total of two path loss models were formulated based on the linear fit relationship-based exponential (EXP) and polynomial (POLY) equations. Both equations were later combined with the PSO, which later known as the EXP-PSO and the POLY-PSO algorithms, to find the optimal coefficient of equations for accurate path loss models. Hence, the correlation coefficient (R2) of determination between the RSS and the distance was optimized mathematically from 0.9392 (EXP) and 0.8307 (POLY) to a linear fit (R2=1) after applying the EXP-PSO and POLY-PSO algorithms. The power consumption of the sensor and router nodes was improved by 99.48% relative to the normal operations when the SWORD algorithm is applied. In addition, data communication in the SWORD algorithm was minimized by 86.45% relative to the sleep/wake scheme. The battery life of the drone was extended to 996 minutes using the proposed sleep/active strategy relative to normal operations of 32.7 minutes. This translates a 96.7% battery power saving based on this strategy. The outcome from this study is significant towards the implementation of an energy efficient Internet of Farming technology by leveraging on drone, wireless communications and sensors to automate the farmer practice in agriculture.,Ph.D.
Pages:	154
Publisher:	UKM, Bangi
Appears in Collections:	Faculty of Engineering and Built Environment / Fakulti Kejuruteraan dan Alam Bina

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