With the assistance of machine learning, difficult tasks can be completed entirely on their own. In a smart grid (SG), computers and mobile devices may make it easier to control the interior temperature, monitor security, and perform routine maintenance. The Internet of Things (IoT) is used to connect the various components of smart buildings. As the IoT concept spreads, SGs are being integrated into larger networks. The IoT is an important part of SGs because it provides services that improve everyone’s lives. It has been established that the current life support systems are safe and effective at sustaining life. The primary goal of this research is to determine the motivation for IoT device installation in smart buildings and the grid. From this vantage point, the infrastructure that supports IoT devices and the components that comprise them is critical. The remote configuration of smart grid monitoring systems can improve the security and comfort of building occupants. Sensors are required to operate and monitor everything from consumer electronics to SGs. Network-connected devices should consume less energy and be remotely monitorable. The authors’ goal is to aid in the development of solutions based on AI, IoT, and SGs. Furthermore, the authors investigate networking, machine intelligence, and SG. Finally, we examine research on SG and IoT. Several IoT platform components are subject to debate. The first section of this paper discusses the most common machine learning methods for forecasting building energy demand. The authors then discuss IoT and how it works, in addition to the SG and smart meters, which are required for receiving real-time energy data. Then, we investigate how the various SG, IoT, and ML components integrate and operate using a simple architecture with layers organized into entities that communicate with one another via connections.

A dual-band, compact, high-gain, simple geometry, wideband antenna for 5G millimeter-wave applications at 28 and 38 GHz is proposed in this paper. Initially, an antenna operating over dual bands of 28 and 38 GHz was designed. Later, a four-port Multiple Input Multiple Output (MIMO) antenna was developed for the same dual-band applications for high data rates, low latency, and improved capacity for 5G communication devices. To bring down mutual coupling between antenna elements, a parasitic element of simple geometry was loaded between the MIMO elements. After the insertion of the parasitic element, the isolation of the antenna improved by 25 dB. The suggested creation was designed using a Rogers/Duroid RT-5870 laminate with a thickness of 0.79 mm. The single element proposed has an overall small size of 13 mm × 15 mm, while the MIMO configuration of the proposed work has a miniaturized size of 28 mm × 28 mm. The parasitic element-loaded MIMO antenna offers a high gain of 9.5 and 11.5 dB at resonance frequencies of 28 GHz and 38 GHz, respectively. Various MIMO parameters were also examined, and the results generated by the EM tool CST Studio Suite^® and hardware prototype are presented. The parasitic element-loaded MIMO antenna offers an Envelop Correlation Coefficient (ECC) < 0.001 and Channel Capacity Loss (CCL) < 0.01 bps/Hz, which are quite good values. Moreover, a comparison with existing work in the literature is given to show the superiority of the MIMO antenna. The suggested MIMO antenna provides good results and is regarded as a solid candidate for future 5G applications according to the comparison with the state of the art, results, and discussion.

Modern multimedia communications technology requirements have raised security standards, which allows for enormous development in security standards. This article presents an innovative symmetric cryptosystem that depends on the hybrid chaotic Lorenz diffusion stage and DNA confusion stage. It involves two identical encryption and decryption algorithms, which simplifies the implementation of transmitting and receiving schemes of images securely as a bijective system. Both schemes utilize two distinctive non-consecutive chaotic diffusion stages and one DNA scrambling stage in between. The generation of the coded secret bit stream employs a hybrid chaotic system, which is employed to encrypt or decrypt the transmitted image and is utilized in the diffusion process to dissipate the redundancy in the original transmitted image statistics. The transmitted image is divided into eight scrambled matrices according to the position of the pixel in every splitting matrix. Each binary matrix is converted using a different conversion rule in the Watson–Crick rules. The DNA confusion stage is applied to increase the complexity of the correlation between the transmitted image and the utilized key. These stages allow the proposed image encryption scheme to be more robust against chosen/known plaintext attacks, differential attacks, cipher image attacks, and information entropy. The system was revealed to be more sensitive against minimal change in the generated secret key. The analysis proves that the system has superior statistical properties, bulkier key space, better plain text sensitivity, and improved key sensitivity compared with former schemes.

Multimedia encryption innovation is one of the primary ways of securely and privately guaranteeing the security of media transmission. There are many advantages when utilizing the attributes of chaos, for example, arbitrariness, consistency, ergodicity, and initial condition affectability, for any covert multimedia transmission. Additionally, many more benefits can be introduced with the exceptional space compliance, unique information, and processing capability of real mitochondrial deoxyribonucleic acid (mtDNA). In this article, color image encryption employs a confusion process based on a hybrid chaotic map, first to split each channel of color images into n-clusters; then to create global shuffling over the whole image; and finally, to apply intrapixel shuffling in each cluster, which results in very disordered pixels in the encrypted image. Then, it utilizes the rationale of human mitochondrial genome mtDNA to diffuse the previously confused pixel values. Hypothetical examination and trial results demonstrate that the anticipated scheme exhibits outstanding encryption, as well as successfully opposes chosen/known plain text, statistical, and differential attacks.

In this article, a single-layer frequency selective surface (FSS)-loaded compact coplanar waveguide (CPW)-fed antenna is proposed for very high-gain and ultra-wideband applications. At the initial stage, a geometrically simple ultra-wideband (UWB) antenna is designed which contains CPW feed lines and a multi-stub-loaded hexagonal patch. The various stubs are inserted to improve the bandwidth of the radiator. The antenna operates at 5–17 GHz and offers 6.5 dBi peak gain. Subsequently, the proposed FSS structure is designed and loaded beneath the proposed UWB antenna to improve bandwidth and enhance gain. The antenna loaded with FSS operates at an ultra-wideband of 3–18 GHz and offers a peak gain of 10.5 dBi. The FSS layer contains 5 × 5 unit cells with a total dimension of 50 mm × 50 mm. The gap between the FSS layer and UWB antenna is 9 mm, which is fixed to obtain maximum gain. The proposed UWB antenna and its results are compared with the fabricated prototype to verify the results. Moreover, the performance parameters such as bandwidth, gain, operational frequency, and the number of FSS layers used in the proposed antenna are compared with existing literature to show the significance of the proposed work. Overall, the proposed antenna is easy to fabricate and has a low profile and simple geometry with a compact size while offering a very wide bandwidth and high gain. Due to all of its performance properties, the proposed antenna system is a strong candidate for upcoming wideband and high-gain applications.

The world population is on the rise, which demands higher food production. The reduction in the amount of land under cultivation due to urbanization makes this more challenging. The solution to this problem lies in the artificial cultivation of crops. IoT and sensors play an important role in optimizing the artificial cultivation of crops. The selection of sensors is important in order to ensure a better quality and yield in an automated artificial environment. There are many challenges involved in selecting sensors due to the highly competitive market. This paper provides a novel approach to sensor selection for saffron cultivation in an IoT-based environment. The crop used in this study is saffron due to the reason that much less research has been conducted on its hydroponic cultivation using sensors and its huge economic impact. A detailed hardware-based framework, the growth cycle of the crop, along with all the sensors, and the block layout used for saffron cultivation in a hydroponic medium are provided. The important parameters for a hydroponic medium, such as the concentration of nutrients and flow rate required, are discussed in detail. This paper is the first of its kind to explain the sensor configurations, performance metrics, and sensor-based saffron cultivation model. The paper discusses different metrics related to the selection, use and role of sensors in different IoT-based saffron cultivation practices. A smart hydroponic setup for saffron cultivation is proposed. The results of the model are evaluated using the AquaCrop simulator. The simulator is used to evaluate the value of performance metrics such as the yield, harvest index, water productivity, and biomass. The values obtained provide better results as compared to natural cultivation.