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A dataset named RF-PSignal for controlling smart home devices

Citation Author(s):
Xiaohang Zhang (Xinjiang University)
Submitted by:
Xiaohang Zhang
Last updated:
DOI:
10.21227/a5pg-pq72
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Abstract

With the accelerating pace of population aging, the urgency and necessity for elderly individuals to control smart home systems have become increasingly evident. Smart homes not only enhance the independence of older adults, enabling them to complete daily activities more conveniently, but also ensure safety through health monitoring and emergency alert systems, thereby reducing the caregiving burden on families and society. Integrating smart homes into the lives of the elderly has thus become a crucial measure to address the challenges of aging populations and promote sustainable social development. However, traditional control methods are often constrained by factors such as lighting conditions and reliance on wearable devices. Our research aims to overcome these limitations, enabling elderly individuals to control smart home devices with greater ease and accuracy.

Instructions:

By analyzing the internal relationships within the data, we constructed a lightweight neural network model. Using the collected dataset, we enable users to control smart home systems.

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