Predictive Estimation of the Optimal Signal Strength from Unmanned Aerial Vehicle over Internet of Things Using ANN.

This paper proposes an intelligent technique for maximizing the network connectivity and provisioning desired quality of service (QoS) of integration of internet of things (IoT) and unmanned aerial vehicle (UAV). Prediction of the signal strength and fading channel conditions enable adaptive data transmission which turn enhances the QoS for the end users/ devices with reducing the power consumption for data transmissions. UAV is data gathering robot from the difficult or impossible area for humans to reach. Hence, Atmospheric dynamics and environment influence the signal strength during traveling in space among UAV, IoT devices, and humankind. Therefore, Signal moving from the smart UAV is sensitive to the effects of attenuation, reflection, diffraction, scattering, and shadowing. We analysis the ability ANN to predictively estimate the signal strength and channel propagation from the drone and physical medium parameters, using ANN. Moreover, the results show that the distortion of the signal can be reduced and enhanced significantly.