The rapid advancement and incorporation of Artificial Intelligence (AI) and the Internet of Things (IoT) have created exceptional opportunities to revolutionize healthcare and treatment methods and offer significant potential for broader industrial information integration. Nevertheless, the growth of intelligent healthcare systems faces challenges such as data confidentiality concerns and the safety of AI algorithms. The need for local datasets is the main problem in applying traditional AI to the development of a personalized model for health care. Thus, to tackle these issues, a novel healthcare system based on blockchain powered by federated matrix meta-learning supported by IoT. In this system, IoT devices function as light nodes, uploading local, shareable information to an edge server for model training, while non-tampered models downloaded through smart contracts handle local private data. This framework comprises four key modules: a hierarchical feature extraction module, a graph topology formulation unit, a dynamic prototype optimization algorithm, and a predictive query integration system. Blockchain technology ensures the healthcare model remains consistent and protects private data from leaks. Also, it has offered a federated matrix meta-learning model known as the federated Matrix-prototype Graph Network (MGN) to handle heterogeneous healthcare data efficiently. This model, based on metrics and graph networks, excels at capturing data distributions even with limited labeled data. To validate the efficacy of the proposed framework, we conducted extensive evaluations using two widely recognized datasets: CheXpert only for medical imaging and CIFAR 100 for general image classification. These experiments increased the performance of up to 85 percent of existing healthcare systems, demonstrating the potential of the proposed integrated approach to solve the industry’s main problems. Thus, this study advances the current discourses on the development of strong, privacy-oriented, and context-aware AI solutions for health systems, which, together with intelligent health technology, will help to raise the efficiency and effectiveness of patient care in the future.

This research in industrial engineering emphasizes data security and confidential capacity. It involves a careful assessment of mutual information, using professional terminology to enhance communication resilience. The study employs deep learning techniques to increase secret capacity during communication, comparing the calculated transmit power with a set threshold for maximization. The master node arranges node pairs based on power requirements, facilitating cluster formation through logical operations. This method optimizes power usage, ensuring dynamic cluster arrangement based on node pair outputs. The system's confidential capacity is evaluated and enhanced systematically. Mutual information between primary and eavesdropping channels aids in calculating confidential capacity. The research focuses on optimizing transmit power using advanced methodologies, aiming to increase secret capacity within power constraints. At decision points, the research checks if the derived transmit power maximizes confidential capacity. If so, the master node organizes nodes in ascending order based on power demands, establishing node pairs and using an OR gate to determine logical values. Nodes with the same logical value form distinct clusters, demonstrating a systematic process for enhancing confidential capacity. This professional approach contributes to the system's robustness and security, aligning with best practices in confidential information management.

Smart cities require effective and sustainable intelligent solutions in transport, economy, fuel, and government affairs to keep up with the fast rise of urbanization. Smart city infrastructure is one of the most successful options; it blends the Internet of Things (IoT), large-scale data, and the green internet. It has several issues, including unstable IoT security, apparatus preservation, safety difficulties, excessive production charges of massive data center building projects, bad impact confrontation, struggle to create green internet users' confidence, personal space easily leaked, and so on. The blockchain is a circulated peer-to-peer (P2P) system and standard intelligence secretarial know-how. This work presents a blockchain-based infrastructure for the sustainable Internet of Everything (IoE)-enabled distribution economy in super smart cities that sustenance safety and secrecy-oriented spatial-temporal decentralized secure services. The infrastructure uses cognitive fog nodes. It uses artificial intelligence (AI) to develop and quote important factual information, produces semantic analytics, and protects results in blockchain and decentralized sources to simplify distribution economy facilities. The proposed model provides a long-term incentive tool that might support secure smart city facilities, including a distribution economy, smart connections, and cyber-physical communication using blockchain and IoE.

Blockchain technology can potentially revolutionize several industries, including agriculture, by addressing agri-product deception, accountability, price tampering, and low consumer trust. Several significant challenges arise due to active human involvement in the agricultural supply chain, including monetary losses, food contamination, spoilage, lack of transparency, delays, poor traceability, security issues, and data vulnerability. The decentralised computing architecture and secure distributed public ledger technology of blockchain make it a suitable substitute to address these problems and attain profitability and confidence for all parties involved. By reviewing previous research and examining case studies of blockchain start-up businesses, this article seeks to illustrate the diverse ways in which blockchain technology can be applied in the agriculture sector, additionally, it will resolve current problems. Blockchain technology presents a viable means of promoting a more reliable, superior, safer, and environmentally sustainable agri-food system in the future. Agri-Chain aims to connect different stakeholders while addressing challenges prevalent in the agriculture sector through the use of Internet of Things (IoT) devices and by implementing Ethereum smart contracts. Although blockchain use in agriculture is currently in its initial stages and faces numerous challenges, including installation costs, privacy concerns, security concerns, scalability difficulties, performance issues, and immaturity, it can revolutionize the industry.