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Internet-of-Things (IoT)-based sensor networks have gained unprecedented popularity in recent years and they become crucial for supporting high data rate real-time applications. For efficient data transmission within IoT networks, it is necessary that each IoT node learns and adapts itself to recent time/spectral characteristics of channels to maximize the throughput and perform channel swapping wherever required. Many researchers have proposed channel allocation and channel quality measurement protocols within multichannel sensor networks. However, to the best of our knowledge, there is no literature available that proposes an automated and adaptive protocol that can learn and adapt according to changing channel characteristics in IoT network for achieving maximum data transmission and throughput. Therefore, this paper proposes a fully automated self-learning and adaptive protocol which can …