Integration of Multi-Modal Sensors and Robot Arm Vision for Monitoring and Assisting Elderly Activities

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.