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Advanced Smart Bracelet for Elderly: Combining Temperature Monitoring and GPS Tracking Sugondo Hadiyoso; Indrarini Dyah Irawati; Akhmad Alfaruq; Tasya Chairunnisa; Muhamad Roihan; Suyatno Suyatno
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i1.6182

Abstract

Indonesia is entering an aging population period, marked by an increase in the number of elderly individuals, accompanied by a rise in dementia cases. This situation leads to higher dependency among the elderly on others for assistance or long-term care. Dementia can cause elderly people to lose their sense of direction, often wandering aimlessly, making them difficult to track. To address this issue, a wearable smart bracelet is proposed to monitor the location and a vital body parameter such as body temperature. The system is equipped with a tracking application that can send an alert if the user is outside a designated area. It automatically sends a warning message to the caregiver's or family member's smartphone when abnormal signs are detected. The bracelet is designed like a wristwatch, to be worn on the wrist. It is small, lightweight, and battery-operated. Temperature and location data can be transmitted in real-time using an internet network to mobile devices. The device can notify when the user is outside the specified area. Test results indicate that the device has high accuracy and reliability in monitoring location and body temperature with accuracy around 98.5%, as well as sending notifications through a Telegram bot when certain thresholds are exceeded. This device can work properly for up to 5 hours on a single battery charge. With this device, it is expected to help monitor and support the care of the elderly so that they can improve their quality of life. This device can also provide an emergency alarm if the elderly are outside the area.
Smart Home Security System Using Object Recognition with the EfficientDet Algorithm: A Real-Time Approach Suyatno Suyatno; Yus Natali; Nurwan Reza Fachrurrozi; Muhamad Roihan; Pietra Dorand; Naufal Ghani
International Journal of Engineering Continuity Vol. 4 No. 1 (2025): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v4i1.400

Abstract

The EfficientDet method, which is implemented on the Raspberry Pi for real-time detection in resource-constrained contexts, is the basis for the smart home security system presented in this study.  The system integrates CCTV cameras, motion sensors, and detectors to identify and classify objects, sending notifications via WhatsApp via the Twilio API.  The EfficientDet-D0 model achieves an accuracy of 94.8%, an average processing time of 45 ms, and a memory usage of about 850 MB.  When compared to moving individuals or non-human things, testing shows that stationary human items have a higher detection accuracy.  Notifications are transmitted roughly every three seconds, with an average latency of 1.4 to 1.8 seconds.  The suggested method provides object recognition, real-time monitoring, and configuration flexibility in contrast to traditional IoT-based systems.  These results highlight the potential of EfficientDet as a reliable and adaptable solution for home security.  Future improvements include improving accuracy in a variety of environmental conditions and implementing adaptive learning.