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All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika IKRA-ITH Informatika : Jurnal Komputer dan Informatika JURNAL INSTEK (Informatika Sains dan Teknologi) ILKOM Jurnal Ilmiah JURNAL IT: Media Infromasi STMIK Handayani Makassar Jurnal Onoma: Pendidikan, Bahasa, dan Sastra E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Technology Research in Information System and Engineering Jurnal Fokus Elektroda (Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Jurnal Rekayasa elektrika
Jura, Suwatri
STMIK Handayani Makassar
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media

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Integration of Multi-Modal Sensors and Robot Arm Vision for Monitoring and Assisting Elderly Activities Jura, Suwatri; Jalil, Abdul
Jurnal Rekayasa Elektrika Vol 21, No 1 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i1.41273

Abstract

This research aims to develop an integration device combining Multi-Modal Sensors and Robot Arm Vision (MMS-RAV) for monitoring activities and assisting in healthcare services for the elderly at home. The method used to develop this device involves integrating MMS, which consists of PIR sensors for detecting the presence of the elderly, LDR sensors for detecting home light conditions, fire sensors for detecting flames, and DHT11 sensors for measuring temperature and humidity. Additionally, the RAV component assists and supports the activities of the elderly and includes a camera for vision-based object detection, ultrasonic sensors for robot navigation, Raspberry Pi as the data processing center, an arm for object retrieval and camera movement, LCD for displaying messages, omni-wheels for robot navigation, and buzzer for early warnings in case of anomalous conditions with the elderly. In this research, MMS functions to monitor elderly activities, while RAV supports healthcare services for the elderly, particularly in medication intake using image processing techniques. The software used to control the entire MMSRAV system is the robot operating system. The results of this study indicate that the developed MMS-RAV device is effective for monitoring elderly activities and assisting in providing healthcare services for medication intake.
Multi-modal sensor integration in chicken-fish-vegetable greenhouse agriculture based on internet of things Risal, Muhammad; Wahyuningsih, Pujianti; Jura, Suwatri; Iskandar, Irmawaty; Jalil, Abdul
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v15.i1.pp138-149

Abstract

Integrated chicken-fish-vegetable farming is a type of agriculture that combines the benefits of them within a single ecosystem. The objective of this study is to develop a control and monitoring system for integrated greenhouse-based chicken-fish-vegetable farming using the internet of things (IoT). The monitoring method employs the integration of multi-modal sensors in the greenhouse, consisting of a camera, water level, DHT11, pH, TDS, DS18B20, light dependent resistor (LDR), and infrared (IR) sensor. The camera functions as a visual monitoring tool for the farm, water level sensor detects hydroponic water levels, DHT11 measures air temperature and humidity, pH sensor measures water acidity, TDS sensor detects water nutrients, DS18B20 measures pond water temperature, LDR detects weather conditions, and IR sensor measures sunlight intensity. The processing units used to control the sensors and output devices are the ESP32 and Raspberry Pi. The system outputs include a relay for pump control, an LCD for text messages, and IoT information visualization using the Blynk platform. The results of this study demonstrate that the multi-modal sensor device can effectively monitor the conditions of integrated greenhouse-based chicken-fish-vegetable farming, achieving an accuracy of up to 96%, with an average data transmission time of 6 seconds through the Blynk IoT platform.
Co-Authors Abdul jalil Abdul Rochman Billy Eden William Asrul Fuari Anatasya, A. Edeth Iskandar, Irmawaty Jefry Samuel JUSMAN, HERY ILHAMSYAH Muhammad Akbar Muhammad Akbar Muhammad Firman Muhammad Risal, Muhammad Najirah Umar Nurfaedah Nurmadinah, Nurmadinah Wahyuningsih, Pujianti Yundari, Yundari Zuhriyah, Sitti