Temperature sensing based on emerging techniques, such as the novel electromagnetic resonant unit, has been the vital research direction. However, current works only focused on the initial and principal verifications, and it is far away to the real application. In this article, a temperature sensor based on mercury-inspired electromagnetic resonant unit holding high-$Q$-factor and with complete circuit system is proposed. The excellent properties of mercury, including the liquid-shape, highly conductivity, and high-temperature sensitivity, are utilized to achieve the effective fusion of such liquid material and high-$Q$-factor electromagnetic resonant unit, so as to realize the integrated design of high-precision temperature sensing. Furthermore, four functional circuits, including signal generation, temperature sensing, signal reception, and signal processing, are designed and constructed, and finally an integrated mercury-inspired electromagnetic resonant-unit temperature sensor system with good temperature sensing performances is realized. Experimental results show that the temperature measured by the proposed sensor is highly consistent with the actual temperature values, with sensing sensitivity up to 1459 mV/ °C. Such achieved high-precision temperature sensor system can be further integrated and can open a new way for the high-precision environment temperature monitoring in the Internet of Thing (IoT) area.

As one of the healthcare development trends, mobile hospital systems nowadays need more advanced means of treatment and diagnosis and require higher data transmission speed and capacity with lower latency. With its ability to simultaneously support a variety of services in a wide range of application scenarios using network slicing technique, the emerging fifth generation communication system (5G) is expected to offer significant communication performances, including higher throughput, higher mobility, higher connection density, higher transmission reliability with lower latency than the current fourth generation (4G). Hence, 5G can serve as an effective transmission means to meet the modern mobile hospital systems requirements. This article proposes a 5G network slicing-based mobile hospital system where two types of slices, namely, enhanced mobile broadband (eMBB) slice and ultrareliable and low-latency communications (uRLLC) slice, are dedicated to the medical data. We propose an optimization method to maximize the throughput of the medical data assigned to the eMBB slice. We also propose a resource allocation algorithm for very high transmission reliability with very low latency of the medical data assigned to the uRLLC slice. Simulation results indicate that our proposed approach can effectively meet mobile hospital systems requirements for data transmission throughput, reliability, and latency from remote sites to hospital centers.

This article describes the design of a hydrogen concentration monitoring system based on ultrahigh-frequency radio-frequency identification (RFID) passive tags, which adopts ISO/IEC 18000-6 Type C standard. Tag devices have been designed by employing a microcontrol unit, making the proposed solution very suitable for low-cost hydrogen concentration measurement in wireless sensor networks. Furthermore, anti-collision capability has been realized by implementing a new true random number generator based on the hydrogen concentration sensing circuit and analog-to-digital converter, without employing any additional device. The correctness of all operations of the RFID system has been experimentally verified in a multiple-tag environment, as well as the hydrogen concentration monitoring capability. Particularly, measurement on an RFID tag prototype developed for the bandwidth 920-925 MHz has revealed that when the ambient temperature is 25 °C and humidity 80%, a maximum error of 9.8% is found within a hydrogen concentration range from 0.24% to 2.4%.

In the last decade, energy harvesting wireless sensor network (EHWSN) has been well developed. By harvesting energy from the surrounding environment, sensors in EHWSN remove the energy constraint and have an unlimited lifetime in theory. The long‐lasting character makes EHWSN suitable for Industry 4.0 applications that usually need sensors to monitor the machine state and detect errors continuously. Most wireless sensor network protocols have become inefficient in EHWSN due to neglecting the energy harvesting property. In this paper, we propose CPEH, which is a clustering protocol specially designed for the EHWSN. CPEH considers the diversity of the energy harvesting ability among sensors in both cluster formation and intercluster communication. It takes the node’s information such as local energy state, local density, and remote degree into account and uses fuzzy logic to conduct the cluster head selection and cluster size allocation. Meanwhile, the Ant Colony Optimization (ACO) as a reinforcement learning strategy is utilized by CPEH to discover a highly efficient intercluster routing between cluster heads and the base station. Furthermore, to avoid cluster dormancy, CPEH introduces the Cluster Head Relay (CHR) strategy to allow the proper cluster member to undertake the cluster head that is energy depletion. We make a detailed simulation of CPEH with some famous clustering protocols under different network scenarios. The result shows that CPEH can effectively improve the network throughput and delivery ratio than others as well as successfully solve the cluster dormancy problem.

Fast time-varying channel parameters and large penetration losses for signals passing through train carriages are two well-known challenges for wireless communications on high speed rails (HSRs). In this paper, we introduce, for the first time, backscatter technology into HSR wireless communications, which can address these two challenges and yet have low complexity of signal processing and low cost of circuit implementation compared with traditional solutions such as relaying or beamforming. Specifically, we propose a backscatter aided wireless transmission (BAWT) scheme and demonstrate that it outperforms the existing direct wireless transmission (DWT) scheme. We derive the upper and lower bounds of channel capacity for BAWT and prove that it exceeds that of DWT on certain conditions. We also propose the transceiver design for both BAWT and DWT, including joint carrier frequency offset and channel estimator, and signal detector. We show that BAWT, rather than DWT, can obtain the channel statistical information in practical applications due to fixed train antennas and unchanged tracks, which can be utilized to facilitate channel estimation. Finally, simulation results are provided to corroborate the proposed solutions.