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We propose a decentralized medical trust management system using blockchain-based federated learning for large-scale Internet of Things (IoT) systems. The proposed system enables health institutions to share data without revealing the privacy of data owners. Health institutions form coalitions and the leader of each coalition is elected based on the proposed proof-of-trust collaboration (PoTC) consensus protocol. The PoTC consensus protocol is based on a weight difference game where trust scores, trust consistency value, and trust deviation are factors used for evaluating nodes in the blockchain. The trust of a node is obtained either through direct trust or recommended trust evaluations. Each leader elects an aggregator who has the most credibility to manage the proposed federated learning system. The leaders become the federated clients as well as validators while the aggregator is the federated server. To ensure the decentralization of nodes, a consortium blockchain is employed. Extensive simulations are performed, which show that the proposed system not only demonstrates scalability and credibility without compromising the accuracy, convergence, and resilience properties against malicious attackers but also outperforms existing trust management systems. A security analysis is also conducted, which shows that the proposed system is robust against trust-related attacks.

The recent innovation in mechanical farming techniques has provided a rapid advancement in farming occupations and has increased both efficiency and productivity in the sector. This review work has investigated the current status of mechanized farming; farm machinery, the domestic factories of the farm implements and their importations, as well as the challenges confronting agricultural mechanization in Nigeria. The paper also discussed and provided the insightful information about the environmental considerations in agricultural mechanization practices.

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Background: Proper biodiversity conservation and strategies for sustainability in environmental and public health are essential measures for addressing the problems of water-related and zoonotic-caused pandemics. It is generally assumed that a resurgence in an epidemic disease is directly linked to negligence in environmental protection policies, but there are sparse scientific publications supporting the claim. Methods: To address this issue, we collected data on the global pre- and post- industrialization scenarios and subjected it to multivariate analyses to investigate the relationship between the lack of proper environmental protection and the emergence of new diseases. Result: Our investigations found a statistically significant association between the loss of wildlife habitat and the emergence of novel diseases. The study also revealed that wildlife-related zoonotic disorders caused more than 220 million deaths amongst global pandemics. More than 30 million deaths were attributed to waterborne diseases due to improper waste management and wastewater treatment. Thus, it is recommended that other environmental parameters (e.g., pollution phase) need to be investigated to fully understand the complex relationship between environmental protection and emergence of new zoonotic diseases.