Omede, Edith Ugochi and Edje, Abel E and Akazue, Maureen Ifeanyi and Utomwen, Henry and Ojugo, Arnold Adimabua (2024) IMANoBAS: An Improved Multi-Mode Alert Notification IoT-based Anti-Burglar Defense System. Journal of Computing Theories and Applications, 1 (3). pp. 273-283. ISSN 3024-9104
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Abstract
Burglary involves forced or unauthorized entry, which leads to damage or loss of property having monetary or emotional value and, more severely, puts lives at risk. The dire need for the safety of lives and properties has attracted so much research on burglary alert system using Internet of Things (IoT) technology. Most of the research focused on alerting the users of burglary attempts using any or a combination of two notification methods: SMS, call, and email. This study emphasizes three-mode notification that combines SMS, call, and email using the application of IoT technology in a burglary alert system, which uses a Passive Infrared (PIR) sensor for burglar detection to ensure that Homeowners or authorized personnel get alerts in events of imminent attempt to break-ins. The study also details the sensor integration with its supporting components, such as the central hub or microcontroller, buzzer, LED, and network interface in the development of the system. The software was developed to facilitate seamless integration with the hardware, ensuring timely and accurate event detection and subsequent alert generation using Arduino IDE programming language, a framework based on the C++ language. The system effected the 3-mode notification to ensure that users get notification in case of an imminent break-in since the failure of the three modes simultaneously is extremely rare. The system’s performance based on its responsiveness on the 3-mode notifications was evaluated, and an average of 83.56% responsiveness was obtained, indicating an acceptable response time.
Item Type: | Article |
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Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Depositing User: | dl fts |
Date Deposited: | 29 Nov 2024 00:59 |
Last Modified: | 29 Nov 2024 01:31 |
URI: | https://dl.futuretechsci.org/id/eprint/46 |