Aplikasi Deteksi Orang Jatuh Dengan Memanfaatkan Kinect

This paper describes method for fall detection, because fall is a serious problem and often resulting to injury, which can endanger the safety of the person. Therefore, falling detection is crucially needed. The device that being used is Kinect, which also could be used to detect people. The detection is using the help of Microsoft Kinect SDK. Kinect can detect a person in front of it and processing it to create a skeleton of the person. The method which being used is to get a set of data on the position of the person. Next, the rate of change in position would be calculated with the available formulae. The data obtained would be selected, in order to distinguish the activities undertaken. When fall is detected, the application can provide the alert

Recall-driven Precision Refinement: Unveiling Accurate Fall Detection using LSTM

This paper presents an innovative approach to address the pressing concern of fall incidents among the elderly by developing an accurate fall detection system. Our proposed system combines state-of-the-art technologies, including accelerometer and gyroscope sensors, with deep learning models, specifically Long Short-Term Memory (LSTM) networks. Real-time execution capabilities are achieved through the integration of Raspberry Pi hardware. We introduce pruning techniques that strategically fine-tune the LSTM model's architecture and parameters to optimize the system's performance. We prioritize recall over precision, aiming to accurately identify falls and minimize false negatives for timely intervention. Extensive experimentation and meticulous evaluation demonstrate remarkable performance metrics, emphasizing a high recall rate while maintaining a specificity of 96\%. Our research culminates in a state-of-the-art fall detection system that promptly sends notifications, ensuring vulnerable individuals receive timely assistance and improve their overall well-being. Applying LSTM models and incorporating pruning techniques represent a significant advancement in fall detection technology, offering an effective and reliable fall prevention and intervention solution.Comment: 8 pages, 9 figures, 6th IFIP IoT 2023 Conferenc

Fall Detection Application Using Kinect

This paper describes method for fall detection, because fall is a serious problem and often resulting to injury, which can endanger the safety of the person. Therefore, falling detection is crucially needed. The device being used is Kinect, which also could be used to detect people. The detection is using Microsoft Kinect SDK�s assistance. Kinect can detect a person in front of it and processing it to create a skeleton of the person. The method being used is to get a set of data on the position of the person. Next, the rate of change in position would be calculated with the available formulae. The data obtained would be selected, in order to distinguish the activities undertaken. When fall is detected, the application can provide the alert