مشروع البحث: Design of Software Defined Radio Based Testbed for Smart Healthcare
تحميل...
المساهمين
الممولين
رقم التعريف
10
الباحث
Aboajeila Ashleibta
الوصف
Defined Radios (SDRs). The proposed system also allows us to modify the power level of
transceiver model, change the operating frequency, use self-design antennas and change the
number of subcarriers in real-time. The results obtained using USRP based wireless sensing
for activities of daily living are highly accurate as compared to off-the-shelf wireless devices
each time when activities and experiments are performed. This system leverage on the channel
state information (CSI) to record the minute movement caused by breathing over orthogonal frequency division multiplexing (OFDM) in multiple sub-carriers. The proposed system combines
subject count and activities performed in different classes together, resulting in simultaneous
identification of occupancy count and activities performed. Different machine learning algorithms namely K-Nearest Neighbour, Decision Tree, Discriminant Analysis, and Naıve Bayes
are used to evaluate the overall performance of the test-bed and achieved a high accuracy. The
K-nearest neighbour outperformed all classifiers, providing an accuracy of 89.73% for activity
detection and 91.01% for breathing monitoring. A deep learning convolutional neural network
is engineered and trained on the CSI data to differentiate multi-subject activities. The proposed
system can potentially fulfill the needs of future in-home health activity monitoring and is a
viable alternative for monitoring public health and well being.
الكلمات الدالة
Design of Software Defined Radio Based Testbed for Smart Healthcare