학술논문

A Comparative Analysis of Real-time Crash and Fall Detection Mechanisms based on sensor-fusion, aural inputs, and visual recognition techniques
Document Type
Conference
Source
2023 4th International Conference for Emerging Technology (INCET) Emerging Technology (INCET), 2023 4th International Conference for. :1-5 May, 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Surveys
Accelerometers
Visualization
Wearable computers
Smart cameras
Medical services
Automobiles
Fall Detection
Crash Detection
Activities of Daily Life
Inertial Measurement Unit
Audio Sensors
Smart Devices
Wearable sensors
Language
Abstract
Fall and crashes can have serious consequences to people of all ages, making the development of crash and fall detection systems a critical area of research. This survey paper aims to provide a overall view of the current trends pertaining to the field related to fall detection mechanisms and sound-based car crash detection. We have discussed about recent researches in the domain, with varied approaches to fall and crash detection systems. We analyze each system's architectural design, datasets, accuracy, and limitations. We also compare and contrast the different approaches and discuss future research directions. The results of this survey research paper will help form a basis for future research in the fall and crash detection domains and further contribute to developing effective algorithms for related prevention measures.