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This paper proposes an intelligent technique for maximizing the networkconnectivity and provisioning desired quality of service (QoS) of integrationof internet of things (IoT) and unmanned aerial vehicle (UAV). Prediction ofthe signal strength and fading channel conditions enable adaptive datatransmission which turn enhances the QoS for the end users/ devices withreducing the power consumption for data transmissions. UAV is data gatheringrobot from the difficult or impossible area for humans to reach. Hence,Atmospheric dynamics and environment influence the signal strength duringtraveling in space among UAV, IoT devices, and humankind. Therefore, Signalmoving from the smart UAV is sensitive to the effects of attenuation,reflection, diffraction, scattering, and shadowing. We analysis the ability ANNto predictively estimate the signal strength and channel propagation from thedrone and physical medium parameters, using ANN. Moreover, the results showthat the distortion of the signal can be reduced and enhanced significantly.

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