Authors: Assistant Professor G. Lakshmi Durga, Gade Bhagya Sri, Guntaka Vahnitha, Shaik Benazil Bhanu, Devarapalli Thanuja
Abstract: The Internet of Things (IoT) technology allows individuals to have new interfaces to communicate with devices that are smart. We present a Smart IoT Interface with Hand Gesture Recognition and Machine Learning in this work to enhance human- machine interaction (HMI) in smart environments. Being a wearable hand gesture recognition and control device, it relies on sensor networks and embedded systems to obtain real-time hand gesture feedback, which is later interpreted by advanced machine learning algorithms to allow natural and natural interaction with IoT devices. The suggested interface takes advantage of wireless communication and edge processing that allows the practical and low-latency processing of real-time data and cloud integration to provide additional device control and gain analytics. Its applications include IoT automation, home automation and an intelligent IoT control to a flexible and reliable system that enables the user to interact with devices connected to it. Findings suggest that the sugg
