There is a massive transformation in the traditional healthcare system from the specialist-centric approach to the patient-centric approach by adopting modern and intelligent healthcare solutions to build a smart healthcare system. It permits patients to directly share their medical data with the specialist for remote diagnosis without any human intervention. Furthermore, the remote monitoring of patients utilizing wearable sensors, Internet of Things (IoT) technologies, and artificial intelligence (AI) has made the treatment readily accessible and affordable. However, the advancement also brings several security and privacy concerns that poorly maneuvered the effective performance of the smart healthcare system. An attacker can exploit the IoT infrastructure, perform an adversarial attack on AI models, and proliferate resource starvation attacks in smart healthcare system. To overcome the aforementioned issues, in this survey, we extensively reviewed and created a comprehensive taxonomy of various smart healthcare technologies such as wearable devices, digital healthcare, and body area networks (BANs), along with their security aspects and solutions for the smart healthcare system. Moreover, we propose an AI-based architecture with the 6G network interface to secure the data exchange between patients and medical practitioners. We have examined our proposed architecture with the case study based on the COVID-19 pandemic by adopting unmanned aerial vehicles (UAVs) for data exchange. The performance of the proposed architecture is evaluated using various machine learning (ML) classification algorithms such as random forest (RF), naive Bayes (NB), logistic regression (LR), linear discriminant analysis (LDA), and perceptron. The RF classification algorithm outperforms the conventional algorithms in terms of accuracy, i.e., 98%. Finally, we present open issues and research challenges associated with smart healthcare technologies.

This article proposes a blockchain and coalition game theory-based secure and reliable optimal data pricing scheme for ride sharing. It mainly focuses on securing data sharing between vehicle owners and customers. It employs beyond fifth-generation (5G) as a communication network that facilitates vehicle owners and customers with low latency, high throughput, and high availability for communication. We also formulate a coalition game-theory approach to optimize the payoff of vehicle owners and customers by forming coalitions. The performance of the proposed system beyond 5G is estimated by comparing it with 5G and LTE-A networks. The various performance parameters considered are network latency, throughput, and profit for vehicle owners. The performance results show that the proposed system is efficient and beneficial for both vehicle owners and customers in terms of low latency, high throughput, and profit.

The gradual transition from a traditional transportation system to an intelligent transportation system (ITS) has paved the way to preserve green environments in metro cities. Moreover, electric vehicles (EVs) seem to be beneficial choices for traveling purposes due to their low charging costs, low energy consumption, and reduced greenhouse gas emission. However, a single failure in an EV’s intrinsic components can worsen travel experiences due to poor charging infrastructure. As a result, we propose a deep learning and blockchain-based EV fault detection framework to identify various types of faults, such as air tire pressure, temperature, and battery faults in vehicles. Furthermore, we employed a 5G wireless network with an interplanetary file system (IPFS) protocol to execute the fault detection data transactions with high scalability and reliability for EVs. Initially, we utilized a convolutional neural network (CNN) and a long-short term memory (LSTM) model to deal with air tire pressure fault, anomaly detection for temperature fault, and battery fault detection for EVs to predict the presence of faulty data, which ensure safer journeys for users. Furthermore, the incorporated IPFS and blockchain network ensure highly secure, cost-efficient, and reliable EV fault detection. Finally, the performance evaluation for EV fault detection has been simulated, considering several performance metrics, such as accuracy, loss, and the state-of-health (SoH) prediction curve for various types of identified faults. The simulation results of EV fault detection have been estimated at an accuracy of 70% for air tire pressure fault, anomaly detection of the temperature fault, and battery fault detection, with R² scores of 0.874 and 0.9375.

In the current era, the skyrocketing demand for energy necessitates a powerful mechanism to mitigate the supply–demand gap in intelligent energy infrastructure, i.e., the smart grid. To handle this issue, an intelligent and secure energy management system (EMS) could benefit end-consumers participating in the Demand–Response (DR) program. Therefore, in this paper, we proposed a real-time and secure incentive-based EMS for smart grid, i.e., RI-EMS approach using Reinforcement Learning (RL) and blockchain technology. In the RI-EMS approach, we proposed a novel reward mechanism for better convergence of the RL-based model using a Q-learning approach based on the greedy policy that guides the RL-agent for faster convergence. Then, the proposed RI-EMS approach designed a real-time incentive mechanism to minimize energy consumption in peak hours and reduce end-consumers’ energy bills to provide incentives to the end-consumers. Experimental results show that the proposed RI-EMS approach induces end-consumer participation and increases customer profitabilities compared to existing approaches considering the different performance evaluation metrics such as energy consumption for end-consumers, energy consumption reduction, and total cost comparison to end-consumers. Furthermore, blockchain-based results are simulated and analyzed with the help of deployed smart contracts in a Remix Integrated Development Environment (IDE) with the parameters such as transaction efficiency and data storage cost.

The emerging demand for electric vehicles in urban cities leads to the need to install a huge number of charging stations. With this requirement, electric vehicle coordination and scheduling at charging stations in real-time becomes highly tedious. Thus, there is a need for an efficient scheduling mechanism for electric vehicle charging at charging stations. This paper proposes a novel blockchain and Internet of Things-based consensus mechanism called COME for secure and trustable electric vehicle scheduling at charging stations. The proposed mechanism is intending to resolve conflicts at charging stations. The integrated InterPlanetary File System protocol facilitates a cost-efficient mechanism with minimized bandwidth for electric vehicle scheduling. The proposed mechanism ensures that there is no loss for either the electric vehicle or the charging station. We formulate different scenarios for electric vehicle charging and apply different scheduling algorithms, including first-come first-served, longest remaining time first, and coalition game theory. The performance of the proposed COME consensus mechanism is estimated by comparing it with the practical Byzantine Fault Tolerance consensus protocol and traditional systems based on the charging demand, wait time, conflict resolution, scalability, and InterPlanetary File System bandwidth parameters. The performance results show that the proposed COME consensus mechanism ensures that electric vehicles can have their vehicle charged without any conflict and that the charging station can be satisfied in terms of profit. Moreover, the proposed COME consensus mechanism outperforms the both practical Byzantine Fault Tolerance consensus protocol and the traditional system in terms of scalability and conflict resolution along with additional parameters such as wait time, charging demand, and bandwidth analysis.

Purpose: With the advancement and modernization of Information and Communication Technology, electronic voting (e-voting) has been adopted across the globe for conducting a secure and efficient voting procedure. However, e-voting can be easily exposed to various malicious attacks such as denial-of-service, malware, insider, compromised credentials, etc., that can risk the voter’s privacy and affect the final voting results. Thus, we have considered the decentralized and immutable blockchain technology for completing the voting procedure securely. Nevertheless, many researchers have considered blockchain to mitigate the security and privacy issues of the voting procedure, but they ignored the aspect of cost-efficiency, latency, and response time while voting. Method: The idea of the proposed mechanism is to deploy and implement the smart contract in the Remix Integrated Development Environment (IDE) involving number of voters electing the candidate with various functionalities. Moreover, we considered the amalgamation of blockchain and IPFS to overcome the data storage cost issues of blockchain for voters and candidates communicating through 5G wireless network. The 5G network, with its low latency, high availability, and high reliability facilitates high data rate and reliable communication between voters and candidates to complete the voting procedure efficiently. Results: The deployed smart contract of the proposed voting mechanism highlight various functionalities required for electing the candidate by the voters. Moreover, the deployed smart contract is evaluated and analyzed considering various performance metrics such as gas consumption analysis for smart contract functions and number of voters, cost analysis for smart contract functions, bit error rate, and storage cost comparison with the traditional scheme. We have also verified the security of the proposed voting mechanism using Echidna security tool which shows the election of candidate without any threat. Conclusion: Finally, we have presented a blockchain-based voting mechanism in which IPFS and 5G is employed to avail the cost-efficient, reliable, and secure candidate election by the voters. Moreover, the voters and candidates can communicate with lower response time and high reliability using 5G network so that smart contract consisting of all the functionalities related to the candidate election can be executed efficiently in the Remix IDE.