LSTM-Attention Mechanism
Published: 11 July 2023| Version 2 | DOI: 10.17632/wfhwj6x4h6.2
Contributor:
Fahd SaadDescription
The dataset comprises recordings of seven activities that were captured using Raspberry Pi (RPi) devices. Each activity was captured using 64 subcarriers, which refer to specific frequency components within the wireless signal. The dataset includes 300 packets, representing multiple instances of each activity.
Files
Steps to reproduce
The RPi devices equipped with appropriate firmware such as Nexmon to collect the wireless signals associated with the activities. These signals were then processed to extract the necessary features for activity recognition.
Institutions
Universiti Teknikal Malaysia Melaka
Categories
Active Remote Sensing, Algorithm Development for Remote Sensing
Funding
Ministry of Higher Education, Malaysia
FRGS/1/2020/ICT02/UTEM/02/1
Universiti Teknikal Malaysia Melaka
FRGS/1/2020/ICT02/UTEM/02/1