LSTM-Attention Mechanism

Published: 11 July 2023| Version 2 | DOI: 10.17632/wfhwj6x4h6.2
Contributor:
Fahd Saad

Description

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

Licence