IOT Smart home system is becoming common now a days. In this ecosystem if a data packets are corrupted or manipulated by a faulty or compromised node, then detecting the faulty node is difficult because of multi hop mesh like network. The faulty Node might lead to wrong decision and operation failure of system thus impacting the Quality of Service (QoS) of different client devices. In this paper we first create a smart home ecosystem by usingIOT nodes like Raspberry pi and Node MCU models. We apply unsupervised learning technique on statistical data collected from these nodes to accurately detect faulty/Malicious nodes. We also provide alternate route depending up on the QoS of client device.

IOT, Node MCU, Raspberry pi, smart home, unsupervised learning, QoS

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