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Analysis of an Advanced, Automated and Secured Home System for the People with Disabilities- Special Reference to the Deaf People

Authors: Md. Niaz Mostakim; Md. Shahjahan Ali; Md. Khalid Hossain Jewel; Md. Anowar Hossain;

Analysis of an Advanced, Automated and Secured Home System for the People with Disabilities- Special Reference to the Deaf People

Abstract

Abstract: This paper presents the implementation of an advanced home automation and security system designed for people with disabilities, with a particular focus on those who have hearing problem. The system is designed to improve accessibility and provide advanced security features through the use of modern microcontroller and machine learning technologies. Many modern sensors were utilized to detect changes in the environment- including fire, temperature, motion, and sound sensors. The machine learning algorithm was trained to analyze the sensor data and provide advanced security features, such as facial recognition, to enhance safety. The system was also equipped with a notification system that alerts individuals of any emergency situations even if they are not in the same room. The system was made user-friendly and customizable, allowing individuals to control their home environment according to their specific needs and preferences. The machine learning algorithm was effective in analyzing sensor data and providing advanced security features, such as facial recognition to enhance safety. By providing an accessible and reliable home automation and security system, individuals can have greater independence and autonomy in their daily lives.

Keywords

Home system, Security, Disabilities, Machine Learning, Arduino, Deaf.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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