In this paper, we present an extremely compact ultrawideband (UWB) monopole microstrip patch antenna for a wireless body area network (WBAN). The proposed antenna is fabricated on a flexible Rogers RT-5880 dielectric substrate of thickness 0.5 mm and has an overall size of . The proposed antenna achieves a wideband characteristic with the help of a modified ground plane with a monopole pair. The monopole antenna is fed through a microstrip line and has a good impedance matching over a frequency band of 3.2 to 15 GHz (and beyond), with an axial ratio below 3 dB and a high efficiency of 77–95%. This antenna is designed to cover almost the complete UWB range; bandwidth for antenna is 11.52 GHz (3.48-15 GHz). The antenna has a realized gain of 2.3–7.2 dBi throughout the frequency band and has been tested for conformality. Measured results are found to be in good correlation with the simulated results. The antenna has also been tested for specific absorption rate (SAR) values within the simulation to compare with Federal Communications Commission (FCC) limits and verify their suitability for the Internet of Things- (IoT-) based wearable body area network.

In the farming industry, the Internet of Things (IoT) is crucial for boosting utility. Innovative agriculture practices and medical informatics have the potential to increase crop yield while using the same amount of input. Individuals can benefit from the Internet of Things in various ways. The intelligent farms require the creation of an IoT-based infrastructure based on sensors, actuators, embedded systems, and a network connection. The agriculture sector will gain new advantages from machine learning and IoT data analytics in terms of improving crop output quantity and quality to fulfill rising food demand. This paper described an intelligent medical informatics farming system with predictive data analytics on sensing parameters, utilizing a supervised machine learning approach in an intelligent agricultural system. The four essential components of the proposed approach are the cloud layer, fog layer, edge layer, and sensor layer. The primary goal is to enhance production and provide organic farming by adjusting farming conditions as per plant needs that are considered in experimentation. The use of machine learning on acquired sensor data from a prototype embedded model is investigated for regulating the actuators in the system. Then, an analytics and decision-making system was built at the fog layer, employing two supervised machine learning approaches including classification and regression algorithms using a support vector machine (SVM) and artificial neural network (ANN) for effective computation over the cloud layer. The experimental results are evaluated and analyzed in MATLAB software, and it is found that the classification accuracy using SVM is much better as compared to ANN and other state of art methods.

Blockchain is the consensus-based technology used to resolve conflicts in Byzantine environments. Vehicles validate the messages received from neighboring vehicles using the gradient boosting technique (GBT). Based on the validation results, the message source vehicle generates the ratings that are to be uploaded to roadside units (RSUs), and through that, the trust offset value can be calculated. All RSUs maintain the trust blockchain, and each RSU tries to add their blocks to the trust blockchain. We proposed a blockchain-based trust management model for the vehicular adhoc network (VANET) based on Tendermint. It eliminates the problem of malicious nodes entering the network, and will also overcome the problem of power consumption. Simulation results also show that the proposed system is 7.8% and 15.6% effective and efficient in terms of packet delivery ratio (PDR) and end-to-end delay (EED), respectively, to collect the trusted data between the vehicles.

This work is devoted to the study of the emitting properties of azimuthally inhomogeneous segmental dielectric resonators excited by whispering gallery modes. Due to the diffraction of the azimuthal waves on local nonhomogeneities located equidistantly along the azimuthal coordinate, intense electromagnetic radiation is achieved in the azimuthal sector of the angles 0°-360°. A prototype of an all-around emitting antenna based on basis of a segmental dielectric resonator is proposed, and its characteristics in the far zone are studied. It is shown that such an antenna forms a multilobe radiation pattern (72 lobes) in the circle sector of angles. The antenna gain in the lobes at the resonant frequency reaches 12 dB. Antenna optimization is achieved in the proposed method because of the large gain produced by the antenna. It is also analyzed that these types of radiation patterns observed by antennas are well used for the Internet of Things- (IoT-) based applications.

A compact, dual-port, triband MIMO antenna is designed and tested for three sub-6 GHz WLAN bands for IoT applications. The size and performance of the antenna make it versatile for the emerging IoT applications communicating using the 2.4 GHz, 5.2 GHz, and 5.8 GHz WLAN frequencies. The single radiating element of antenna geometry includes a pair of modified and optimized rectangular patches. A complimentary split ring resonator (CSRR) structure is incorporated in the ground plane as a defect (defected ground structure) to attain the third operational band. The orientation of the elements, orthogonally arranged, along with DGS, enhances the isolation between the radiating elements keeping it below 18 dB throughout the three operating frequency bands. The size of the final antenna is as small as mm² build on commercially available and cheap FR4 substrate of thickness 1.5748 mm. A peak gain of 7.17 dBi is attained for the proposed MIMO system. This MIMO antenna also satisfies the diversity parameter requirements including , , dB, and bits/s/Hz. This makes the proposed antenna a good candidate for IoT applications employing WLAN frequencies.

Summary: A decentralized application runs on the blockchain network without the intervention of a central authority. Transparency in transactions and security in vehicular networks are the issues for central systems. The proposed system uses blockchain‐based smart contracts, which eliminate the requirement for any third‐party verification. Additionally, with signature verification and reduced overhead, smart contracts also help in a fast and secure transaction. This study suggests a trust‐based system paradigm where certificate authority (CA) is employed for vehicle registration. We also propose a blockchain‐based system that provides efficient two‐way authentication and key agreement through encryption and digital signatures. The analysis of the proposed model reveals that it is an efficient way of establishing distributed trust management, which helps in preserving vehicle privacy. The proposed scheme is tested in Automated Validation of Internet Security‐sensitive Protocols (AVISPA), and security parameters verification in Network Simulator 2(NS2) also shows that the proposed scheme is more effective in comparison with existing schemes in terms of authentication cost, storage cost, and overhead.