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Non-Contact Monitoring of Dehydration using RF Data Collected off the Chest and the Hand
Compared to prior work where the reported accuracy is 97. 83%, our proposed non-contact method is slightly inferior (as we report a maximum accuracy of 96. 15%); nevertheless, the advantages of our non-contact dehydration method speak for themselves.
Energy Disaggregation & Appliance Identification in a Smart Home: Transfer Learning enables Edge Computing
Non-intrusive load monitoring (NILM) or energy disaggregation aims to extract the load profiles of individual consumer electronic appliances, given an aggregate load profile of the mains of a smart home.
Countering Active Attacks on RAFT-based IoT Blockchain Networks
When the IoT network is under the jamming attack, we utilize the stochastic geometry tool to derive the closed-form expressions for the coverage probabilities for both uplink and downlink IoT transmissions.
