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|Title:||SDQ-6WI: Software Defined Quadcopter-Six Wheeled IoT Sensor Architecture for Future Wind Turbine Placement|
|Keywords:||Wind turbine;OF;SDN;control plane;power management|
|Publisher:||Institute of Electrical and Electronics Engineers|
|Citation:||IEEE Access, 2018|
|Abstract:||Although wind-generated power was estimated to be 4%  of the entire world electricity usage, wind turbines are considered to be a growing technology with many experts considering new approaches to wind turbine design and farmland selection to increase the wind turbine output efficiency. When implementing a new wind turbine install on a farm, many concerns are taken into consideration such as environmental challenges and cost. Thus, the power of the wind turbine can be increased at least ten times when the most efficient wind power location is selected before the wind turbine is placed. In this paper, we propose a novel Software-Defined Quadcopter – 6 Wheeled Industrial IoT (SDQ-6WI) architecture that is based on a developed quadcopter system to collect wind speed data from a mobile IoT vehicle base station that is based on a developed Open Flow (DOV) protocol operation. The mobile ground vehicle act as a wind speed measurement system that travels on a given set of waypoints to measure the best optimal wind speed quality and send the collected information to the quadcopter-based SDN controller then to the cloud for further processing. Our proposed system can handle a heterogeneous environment that lacks Wi-Fi and cellular coverage and uses the minimum total transmission power when sending data. The experiential results showed that the measured wind speed data could be collected in a time-efficient manner compared to a traditional process which is considered to be costly, time wasting and non-effective. Our extensive testing showed that about 23.19% in power was reduced in the wind measurement process in comparison with the fixed sensor nodes. In essence, the proposed architecture help reduce the high cost of relocating wind turbines to an efficient location and increase the generated power by selecting the best optimal windy location.|
|Appears in Collections:||Dept of Electronic and Computer Engineering Research Papers|
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