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An IoT-Based Multimodal Real-Time Home Control System for the Physically Challenged: Design and Implementation

Okokpujie, Kennedy O. and Jacinth, David and James, Gabriel Ameh and Okokpujie, Imhade P. and Akingunsoye, Adenugba Vincent (2023) An IoT-Based Multimodal Real-Time Home Control System for the Physically Challenged: Design and Implementation. Information Dynamics and Applications. pp. 90-100.

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Physical impairments affect a significant proportion of the global populace, emphasizing the need for assistive technologies to increase the ability of these individuals to perform daily activities autonomously. This study discusses the development and implementation of a multimodal home control system, designed to afford physically challenged individuals greater control over their home environments. This system utilizes the Internet of Things (IoT) for its functionality. The system is primarily based on the utilization of the Amazon Alexa Echo Dot, which facilitates speech-based control, and a sequential clap recognition system, both made possible through an internet connection. These methods are further supplemented by an additional manual switching option, thereby ensuring a diverse range of control methods. The processing core of this system consists of an Arduino Uno and an ESP32 Devkit module. In conjunction with these, a sound detector is employed to discern and process a variety of clap patterns, which is set to function at a predefined threshold. The Amazon Alexa Echo Dot serves as the primary interface for voice commands and real-time information retrieval. Furthermore, an Android smartphone, equipped with the Alexa application, provides alternate interfaces for appliance control, through both soft buttons and voice commands. Based on an analysis of this system, it is suggested that it is not only viable but also effective. Key attributes of the system include rapid response times, aesthetic appeal, secure operation, low energy consumption, and most importantly, increased accessibility for physically disabled individuals.

Item Type: Article
Uncontrolled Keywords: Physically challenged; Home automation; Internet of Things; Voice control; Speech recognition; Amazon Alexa; Arduino; ESP32; Sound sensor; Clap detection
Subjects: T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User: AKINWUMI
Date Deposited: 17 Nov 2023 07:55
Last Modified: 17 Nov 2023 07:55

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