Background: Application of Artificial Intelligence (AI) and the use of agent-based systems in the healthcare system have attracted various researchers to improve the efficiency and utility in the Electronic Health Records (EHR). Nowadays, one of the most important and creative developments is the integration of AI and Blockchain that is, Distributed Ledger Technology (DLT) to enable better and decentralized governance. Privacy and security is a critical piece in EHR implementation and/or adoption. Health records are updated every time a patient visits a doctor as they contain important information about the health and wellbeing of the patient and describes the history of care received during the past and to date. Therefore, such records are critical to research, hospitals, emergency rooms, healthcare laboratories, and even health insurance providers. Methods: In this article, a platform employing the AI and the use of multi-agent based systems along with the DLT technology for privacy preservation is proposed. The emphasis of security and privacy is highlighted during the process of collecting, managing and distributing EHR data. Results: This article aims to ensure privacy, integrity and security metrics of the electronic health records are met when such copies are not only immutable but also distributed. The findings of this work will help guide the development of further techniques using the combination of AI and multi-agent based systems backed by DLT technology for secure and effective handling EHR data. This proposed architecture uses various AI-based intelligent based agents and blockchain for providing privacy and security in EHR. Future enhancement in this work can be the addition of the biometric based systems for improved security.

With the increasing number of cybercrimes, the digital forensics team has no choice but to implement more robust and resilient evidence-handling mechanisms. The capturing of digital evidence, which is a tangible and probative piece of information that can be presented in court and used in trial, is very challenging due to its volatility and improper handling procedures. When computer systems get compromised, digital forensics comes into play to analyze, discover, extract, and preserve all relevant evidence. Therefore, it is imperative to maintain efficient evidence management to guarantee the credibility and admissibility of digital evidence in a court of law. A critical component of this process is to utilize an adequate chain of custody (CoC) approach to preserve the evidence in its original state from compromise and/or contamination. In this paper, a practical and secure CustodyBlock (CB) model using private blockchain protocol and smart contracts to support the control, transfer, analysis, and preservation monitoring is proposed. The smart contracts in CB are utilized to enhance the model automation process for better and more secure evidence preservation and handling. A further research direction in terms of implementing blockchain-based evidence management ecosystems, and the implications on other different areas, are discussed.

Repowering a wind farm enhances its ability to generate electricity, allowing it to better utilize areas with high mean wind speeds. Pakistan’s present energy dilemma is a serious impediment to its economic development. The usage of a diesel generator as a dependable backup power source raises the cost of energy per kWh and increases environmental emissions. To minimize environmental emissions, grid-connected wind farms enhance the percentage of wind energy in the electricity system. These wind generators’ effects, on the other hand, are augmented by the absorption of greater quantities of reactive electricity from the grid. According to respective grid codes, integration of commercial onshore Large-Scale Wind Farms (LSWF) into a national grid is fraught with technical problems and inter-farm wake effects, which primarily ensure power quality while degrading overall system operation and limiting the optimal use of attainable wind resources. The goal of this study is to examine and estimate the techno-economic influence of large-scale wind farms linked to poor transmission systems in Pakistan, contemplating the inter-farm wake effect and reactive power diminution and compensating using a range of voltage-ampere reactive (VAR) devices. This study presents a partial repowering technique to address active power deficits produced by the wake effect by raising hub height by 20 m, which contributed to recovering the active power deficit to 48% and so reduced the effects of upstream wind farms. Simulations were conducted for several scenarios on an actual test system modeled in MATLAB for comparative study using capacitor banks and different flexible alternating current transmission system (FACTS) devices. Using the SAM (System Advisor Model) and RETscreen, a complete technical, economic, and environmental study was done based on energy fed into the grid, payback time, net present value (NPV), and greenhouse gases (GHG) emission reduction. The studies suggest that the unified power flow controller (UPFC) is the optimum compensating device via comparison analysis as it improved the power handling capabilities of the power system. Our best-case scenario includes UPFC with hub height augmentation, demonstrating that it is technically, fiscally, and environmentally viable. Over the course of its lifespan, the planned system has the potential to save 1,011,957 tCO₂, resulting in a greener environment. When the energy generated annually by a current wake-affected system is compared to our best-recommended scenario, a recovered shortfall of 4.851% is seen, with improved system stability. This modest investment in repowering boosts energy production due to wake effects, resulting in increased NPV, revenue, and fewer CO₂ footprints.

Blockchain (BC) with a clustering scheme can be used to build secure and smart Vehicular Ad-Hoc Networks (VANETs), which provide improved data integrity, enhanced security, efficient resource allocation, and streamlined processes. This technology has revolutionized the transport industry by enabling safer, more efficient, and transparent transportation networks. Therefore, this paper concentrates on the design of a new Blockchain with a Quantum Mayfly Optimization-based Clustering Scheme for Secure and Smart Transport Systems (BQMFO-CSSTS) technique. The objective of the presented BQMFO-CSSTS technique is to build a secure VANET via a BC-based technology and clustering process. Moreover, the BQMFO-CSSTS technique initially uses a Quantum Mayfly Optimization (QMFO) system with a fitness function for the selection of cluster heads (CHs) and the cluster construction process. In addition, BC technology is used as trust infrastructure to provide trustworthy services to the user and protect the privacy of the CHs and cluster members (CMs). The proposed scheme leverages the decentralized and immutable nature of BC to establish trust and ensure the integrity of cluster formation in VANETs. Finally, the BQMFO-CSSTS technique uses trajectory similarity metrics to protect the integrity of the CMs against attacks. The simulation results of the BQMFO-CSSTS technique are validated using a series of measures. The comprehensive results reported the superior outcomes of the BQMFO-CSSTS method over other recent approaches, with the maximum throughput being 1644.52 kbps. Therefore, integration of BC technology provides a transparent and secure framework through which to manage cluster membership, data sharing, and trust establishment among vehicles.

Dynamics in rainfall patterns due to climate change are posing a threat to crop production globally. The core issue of food security is expected to intensify, and improving crop yield using motorized power irrigation mechanisms can help in curtailing the impact of drought and changing weather patterns to meet the crop water requirement. To meet the energy demand of irrigation systems, this paper explores the use of hybrid energy sources, i.e., wind and solar energy, taking Shaqra Saudi Arabia as case study. This paper presents a systematic case study that evaluates crop water requirements for 3 different crops using the United Nations Food and Agriculture Organization’s software CROPWAT 8.0 and converts the water requirement into energy demand to design the water pumping system. The energy requirement water pumping system is used to design a hybrid energy system using HOMER PRO 3.14.4 that can reliably meet the energy demand. The results suggests that, contrary to the common consideration in Saudi Arabia, a hybrid of wind and solar energy proves to be more cost effective and yields a higher amount of energy. The results suggest that a significant reduction in cost can be achieved with a hybrid energy system as compared to a solar PV system only.