The increasing food scarcity necessitates sustainable agriculture achieved through automation to meet the growing demand. Integrating the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) is crucial in enhancing food production across various agricultural domains, encompassing irrigation, soil moisture monitoring, fertilizer optimization and control, early-stage pest and crop disease management, and energy conservation. Wireless application protocols such as ZigBee, WiFi, SigFox, and LoRaWAN are commonly employed to collect real-time data for monitoring purposes. Embracing advanced technology is imperative to ensure efficient annual production. Therefore, this study emphasizes a comprehensive, future-oriented approach, delving into IoT-WSNs, wireless network protocols, and their applications in agriculture since 2019. It thoroughly discusses the overview of IoT and WSNs, encompassing their architectures and summarization of network protocols. Furthermore, the study addresses recent issues and challenges related to IoT-WSNs and proposes mitigation strategies. It provides clear recommendations for the future, emphasizing the integration of advanced technology aiming to contribute to the future development of smart agriculture systems.

Mobile communication systems are always in continuous evolution due to the demands of the end-users using this technology. Therefore, before the possible launch of 5G, some technologies have opened the way to the new mobile communication system. The need for technologies that provide more comfort to users has led to the construction of complex communication systems that were only science fiction decades ago. The information society in which we are now immersed has been the result of constant progress over time. In this paper, a survey of multiple access schemes for next-generation wireless communication systems is presented. Multiple access schemes are reviewed for possible use in next-generation wireless communication systems such as orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA), and delta-orthogonal multiple access (D-OMA), etc. General comparisons of 1G to 6G are presented. Different types of OMA are explained, and then orthogonal frequency division multiple access (OFDMA) is chosen as an example of the OMA scheme to compare with NOMA and D-OMA. There are two types of NOMA: power-domain and code-domain, which are discussed and compared. Simulation results are presented, and a comparison among different access schemes is provided.

Acne scarring occurs in 95% of people with acne vulgaris due to collagen loss or gains when the body is healing the damages of the skin caused by acne inflammation. Accurate classification of acne scars is a vital factor in providing a timely, effective treatment protocol. Dermatologists mainly recognize the type of acne scars manually based on visual inspections, which are time- and energy-consuming and subject to intra- and inter-reader variability. In this paper, a novel automated acne scar classification system is proposed based on a deep Convolutional Neural Network (CNN) model. First, a dataset of 250 images from five different classes is collected and labeled by four well-experienced dermatologists. The pre-processed input images are fed into our proposed model, namely ScarNet , for deep feature map extraction. The optimizer, loss function, activation functions, filter and kernel sizes, regularization methods, and the batch size of the proposed architecture are tuned so that the classification performance is maximized while minimizing the computational cost. Experimental results demonstrate the feasibility of the proposed method with accuracy, specificity, and kappa score of 92.53%, 95.38%, and 76.7%, respectively.

Existing research shows that Cluster-based Medium Access Control (CB-MAC) protocols perform well in controlling and managing Vehicular Ad hoc Network (VANET), but requires ensuring improved security and privacy preserving authentication mechanism. To this end, we propose a multi-level blockchain-based privacy-preserving authentication protocol. The paper thoroughly explains the formation of the authentication centers, vehicles registration, and key generation processes. In the proposed architecture, a global authentication center (GAC) is responsible for storing all vehicle information, while Local Authentication Center (LAC) maintains a blockchain to enable quick handover between internal clusters of vehicle. We also propose a modified control packet format of IEEE 802.11 standards to remove the shortcomings of the traditional MAC protocols. Moreover, cluster formation, membership and cluster-head selection, and merging and leaving processes are implemented while considering the safety and non-safety message transmission to increase the performance. All blockchain communication is performed using high speed 5G internet while encrypted information is transmitted while using the RSA-1024 digital signature algorithm for improved security, integrity, and confidentiality. Our proof-of-concept implements the authentication schema while considering multiple virtual machines. With detailed experiments, we show that the proposed method is more efficient in terms of time and storage when compared to the existing methods. Besides, numerical analysis shows that the proposed transmission protocols outperform traditional MAC and benchmark methods in terms of throughput, delay, and packet dropping rate.

In recent times, a fluid antenna system (FAS) has gained attention as a potential contender for 6G wireless networks. Fluid antenna multiple access (FAMA) is a new technology that allows each user to constantly move to the position with the strongest signal-to-interference ratio (SIR) by means of a single RF-chain port fluid antenna. Research works in FAMA mainly focus on propose models and solutions linked to the enhancement of FAMA from several aspects, including FAS system, enhancing orthogonal and non-orthogonal multiple access, channel modeling, diversity gain, artificial intelligence (AI) techniques, FAMA with other emerging technologies for 6G such as intelligent reflecting surface (IRS), massive MIMO, THz communication, etc. There is no survey which covers all these important aspects of FAMA. Based on several concerns, a comprehensive taxonomy of FAMA has been presented in this study. First, FAS system is discussed. Then, FAMA mechanism is presented with its channel modeling and diversity gain. After that, FAMA is investigated with other emerging technologies such as massive MIMO, THz communication, etc. AI approaches to enhance FAMA are provided. In the end, we cover the potential research directions for further study in all areas. When designing and enhancing the FAS system, facilitating communication via FAMA, and integrating it with other cutting-edge technologies for 6G, this article may serve as a reference or guidance.