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Wireless Sensing and Networking for the Internet of Things

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lawful interception; hybrid SDN; intercept access point; minimum vertex cover; text detection; natural scene; feature fusion; soil water content; sensor networks; distributed sensing; IoT measurements; Precision Agriculture; moisture sensor; wireless communication; LoRa; LoRaWAN™; indoor localisation; fingerprinting; landmark; wearable device; inertial measurement device; motion mode detection; body shadowing compensation; nearest neighbour; label-free biosensor; machine learning; support vector machine; artificial neural network; principal component analysis; Green IoT; IIoT; edge computing; AI; edge AI; sustainability; digital transition; digital circular economy; Industry 5.0; direction-of-arrival estimation; geometric algebra; ESPRIT algorithm; electromagnetic vector-sensor array; hardware security; electromagnetic sensing; real time; cybersecurity; anomaly detection; the Internet of Things; deep learning; blockchain; 5G/6G; URLLC; tactile Internet; industrial IoT; network emulator; robotic simulator; virtual testbed; wireless power transfer; energy harvesting; power conversion efficiency; single diode rectifier; voltage doubler; harmonic balance method; autonomous sensor node; wireless sensor network; multi-tone signal; full-wave simulations of PCB; millimeter wave; new radio; unmanned aerial vehicles; LoS blockage; closed-from approximation; rooftop deployments; coverage path planning; unmanned aerial vehicle; cell decomposition; decomposition methods; energy-aware approaches; energy optimal path; multi-robot systems; multi-UAV; smart cities; Internet of Things (IoT); sensors; 6G; wireless communications; resilience; climate change; connectivity; data; wireless systems; mobile sensors; D2D; technological development; Internet of things; LoRaWAN; reliability; downlink; safety; IoT; LPWAN; proximal soil sensor device; conventional communication methods; ultralow power consumption; long-distance transmission; economic value; inventoried sensor devices; digital twin; LSTM model; n/a

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