Blockchain and IoT are being deployed at a large scale in various fields including healthcare for applications such as secure storage, transactions, and process automation. IoT devices are resource-constrained, have no capability of security and self-protection, and can easily be hacked or compromised. Furthermore, Blockchain is an emerging technology with immutability features which provide secure management, authentication, and guaranteed access control to IoT devices. IoT is a cloud-based internet service in which processing and collection of user’s data are accomplished remotely. Smart healthcare also requires the facility to provide the diagnosis of patients located remotely. The smart health framework faces critical issues such as data security, costs, memory, scalability, trust, and transparency between different platforms. Therefore, it is important to handle data integrity and privacy as the user’s authenticity is in question due to an open internet environment. Several techniques are available that primarily focus on resolving security issues i.e., forgery, timing, denial of service and stolen smartcard attacks, etc. Blockchain technology follows the rules of absolute privacy to identify the users associated with transactions. The motivation behind the use of Blockchain in health informatics is the removal of the centralized third party, immutability, improved data sharing, enhanced security, and reduced overhead costs in distributed applications. Healthcare informatics has some specific requirements associated with the security and privacy along with the additional legal requirements. This paper presents a novel authentication and authorization framework for Blockchain-enabled IoT networks using a probabilistic model. The proposed framework makes use of random numbers in the authentication process which is further connected through joint conditional probability. Hence, it establishes a secure connection among IoT devices for further data acquisition. The proposed model is validated and evaluated through extensive simulations using the AVISPA tool and the Cooja simulator, respectively. Experimental results analyses show that the proposed framework provides robust mutual authenticity, enhanced access control, and lowers both the communication and computational overhead cost as compared to others.

In this paper, a circular intuitionistic fuzzy set is implicated, which is the extension of a fuzzy set and an intuitionistic fuzzy set. The circular intuitionistic fuzzy set includes a radius for both membership and non-membership. After this, we describe the TODIM method for decision making, which can handle both quantitative and qualitative criteria, as well as imprecise and uncertain information. TODIM takes into account the decision-maker’s subjective preferences and attitudes towards the criteria while also considering the uncertainty and imprecision in the decision-making process. We define the algorithm of C-IF-TODIM approach for decisions making problem. The proposed method takes into account both the fuzziness and circularity of the decision-making problem, which come from the fact that the decision-maker’s preferences are subjective and that the criteria depend on each other. A case study of choosing materials for a cryogenic storage tank is used to test the proposed method, and the results are compared to those from other ways of making decisions. The results show that the proposed method makes decisions that are more accurate and reliable and that it can handle the uncertainty and complexity of choosing materials for cryogenic storage tanks well. After reviewing this paper, we can help make liquid nitrogen transportation safer and more reliable, which will cut down on the chance of accidents and financial losses. The proposed method can be applied to decision-making in other domains where circular intuitionistic fuzzy information is common.

To satisfy the electricity needs of a village in Tangi, northwest Pakistan, the present research can design and evaluate the environmental and economical aspects of an optimal hybrid photovoltaic-biogas-hydropower-battery energy sustainable system (PV-BG-HP-BESS). This framework integrates various renewable energy sources, delivering a modern, efficient approach to sustainable energy solutions. The HOMER Pro software is utilized to optimize the most economical and effective hybrid energy system. The results showed that the proposed hybrid system comprising 91.4 kWp PV modules, 19.6 kW hydropower, a 50 kW biogas generator (BG), 36 batteries, and a 60.6 kW converter was the most economical choice. This system, which used the cyclic charging (CC) method, had a cost of energy (COE) of 0.0728 $/kWh and a total net present cost (NPC) of $152,242. The suggested hybrid energy system for rural areas of Pakistan includes photovoltaic (PV), biogas (BG), hydro, and battery components to provide a dependable and sustainable power supply. This system minimizes the need for expensive fossil fuels while simultaneously minimizing environmental impact by lowering pollutants and greenhouse gas emissions. The system's annual electricity production is 294,782 kWh, with PV leads at 59.4%, BG at 6.02%, and hydro at 34.6%, ensuring uninterrupted power generation even in remote areas. The unmet load, extra electricity, and capacity shortage illustrate the reliability of the system and make it possible to address rural electrification challenges while supporting sustainable development and economic growth. Moreover, the outcomes of the proposed hybrid system dominate the previous studies in multiple objectives, including cost and sensitivity analysis, when compared.

The rapid advancement of new resources of energy has been increasing in the world day by day with traditional resources of power generation. The goals of such developments are to increase both economic and environmental benefits. In the literature, there have been a lot of hybrid systems that have come into existence as a combination of different energy resources with different configurations. In this scenario, the combination of different energy resources like photovoltaic (PV), water turbine (hydro), diesel generator (D), and battery energy storage system (BESS), each with a different configuration, is taken into account, leading to a hybrid energy management system. Furthermore, the proposed system leads to a real-world optimization problem that is solved by the use of dynamic programming. For this purpose, we have taken into account the existing day-ahead data of load, electricity, and other sources for the optimal output of the proposed hybrid system. Moreover, the objective function is the minimization of cost by organizing distributed energy resources as well as the emission reduction of toxic gases. The objective function is constrained by balancing the power between the supply and load requirements and the restrictions of each distributed energy resource. A multistage decision procedure known as Dynamic programming is used in regard to state of charge (SOC), which yields the optimal cost of the system. For this purpose, we tried to make use of conventional as well as local turbines, which lead to small hydropower plants that contribute to the proposed system as a case study in the northern areas of Pakistan in order to produce low-cost electricity. The purpose of the proposed study is to develop an optimal hybrid energy management system that generates more power at a minimum cost. Moreover, the maintenance cost is reduced to a high extent as compared to the previous hybrid system in the literature. Due to the minimum use of diesel generator, the proposed hybrid system produces optimal results in terms of clean energy provision as compared to the existent techniques in the literature.

In this article, we introduce a new algorithm-based scheme titled asymptotic homotopy perturbation method (AHPM) for simulation purposes of non-linear and linear differential equations of non-integer and integer orders. AHPM is extended for numerical treatment to the approximate solution of one of the important fractional-order two-dimensional Helmholtz equations and some of its cases . For probation and illustrative purposes, we have compared the AHPM solutions to the solutions from another existing method as well as the exact solutions of the considered problems. Moreover, it is observed that the symmetry or asymmetry of the solution of considered problems is invariant under the homotopy definition. Error estimates for solutions are also provided. The approximate solutions of AHPM are tabulated and plotted, which indicates that AHPM is effective and explicit.