Development of Smart Light Control and Intruder Detection with Voice and Motion Based on Internet of Things Using Raspberry Pi

In the digital era of mobile technology, smart light control via voice and motion on the internet of things through the use of Raspberry Pi may assist them in managing their daily lives more conveniently, efficiently, and securely. The security of their lives and possessions is critical. The primary...

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Bibliographic Details
Published in2022 6th International Conference on Business and Information Management (ICBIM) pp. 190 - 195
Main Authors Netinant, Paniti, Rukhiran, Meennapa, Rattanakorn, Pattarin
Format Conference Proceeding
LanguageEnglish
Published IEEE 26.08.2022
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Summary:In the digital era of mobile technology, smart light control via voice and motion on the internet of things through the use of Raspberry Pi may assist them in managing their daily lives more conveniently, efficiently, and securely. The security of their lives and possessions is critical. The primary objective of this research is to design and develop a smart light control and intruder detection system using Raspberry Pi based on the internet of things. The proposed prototype supports Wi-Fi and 4G mobile connections in a home or outdoor environment. The methodology used in this study is for manual control of on-off lights and detection of an intruder with a range of response times, including low, medium, and high response delays (1, 2.5, and 5 seconds). The testing results compare the Average Response Time and the Average Effectiveness Response Time for mobile connections over 4G and Wi-Fi. The results support the on-off lights, with response accuracy rates of 78 percent, 84 percent, and 100 percent for Thai and English voice commands on Google Assistance and the Blynk mobile application, respectively. As a result, the research examines the response time for various environments with varying levels of mobile communication. The proposed system has designed and evaluated a prototype of smart light control and intruder detection using the Internet of Things. This prototype can be used in daily life to increase convenience, reduce time spent on tasks, reduce costs, and increase security.
DOI:10.1109/ICBIM57406.2022.00041