Robust human locomotion and localization activity recognition over multisensory
Air University · Prince Sattam Bin Abdulaziz University · +4 more institutions
Abstract
Human activity recognition (HAR) plays a pivotal role in various domains, including healthcare, sports, robotics, and security. With the growing popularity of wearable devices, particularly Inertial Measurement Units (IMUs) and Ambient sensors, researchers and engineers have sought to take advantage of these advances to accurately and efficiently detect and classify human activities. This research paper presents an advanced methodology for human activity and localization recognition, utilizing smartphone IMU, Ambient, GPS, and Audio sensor data from two public benchmark datasets: the Opportunity dataset and the Extrasensory dataset. The Opportunity dataset was collected from 12 subjects participating in a…
Citation impact
- FWCI
- 24.84
- Percentile
- 100%
- References
- 164
Authors
7Topics & keywords
- Activity recognition
- Computer science
- Inertial measurement unit
- Artificial intelligence
- Wearable computer
- Convolutional neural network
- Smartwatch
- Benchmark (surveying)