Blockchain-Internet of Things Applications: Opportunities and Challenges for Industry 4.0 and Society 5.0

Enhancing healthcare IoT systems for diabetic patient monitoring: Integration of Harris Hawks and grasshopper optimization algorithms

The integration of the Internet of Things (IoT) in healthcare, especially for people with diabetes, allows for constant health monitoring. This means that doctors can watch over patients' health more closely, making sure they catch any issues early on. With this technology, healthcare workers can be more accurate and effective when keeping an eye on how patients are doing. This not only helps in keeping track of patients' health in real-time but also makes the whole process more reliable and efficient.By implementing appropriate routing techniques, the transmission of diabetic patients' data to medical centers will facilitate real-time and timely responses from healthcare professionals. The grasshopper optimization algorithm is employed in the proposed approach to cluster network nodes, resulting in the formation of a network tree that facilitates the establishment of connections between the cluster head and the base station. After identifying the cluster head and establishing the clusters, the second stage of routing is implemented by employing the Harris Hawks optimization algorithm. This algorithm ensures that the data pertaining to diabetic patients is transmitted to the treatment centers and hospitals with minimal delay. For node routing, the optimal next step is selected based on the parameters such as the residual energy of the node, the ratio of delivered data packages, and the number of the neighbors of the node. To continue, first, the MATLAB software is utilized to simulate the proposed method, and then, it is compared with other similar methods. This comparison is conducted based on various parameters, including delay, energy consumption, network throughput, and network lifespan. Compared to other methods, the proposed method demonstrates a significant 33% improvement in the average point-to-point delay parameter in the subsequent iterations or rounds.

Traceability Management System Using Blockchain Technology and Cost Estimation in the Metrology Field

Metrological traceability is essential to ensure the reliability of calibration tests. Calibration certificates usually include information on only one upper-level reference standard. As metrological traceability is multi-layered, generally there is no method available for end users to instantly confirm the traceability from the reference standard to a primary standard. This study focuses on the Ethereum blockchain, which has both tamper resistance and high availability, as a digital data management method. To improve the transparency and reliability of calibration tests, a smart contract that traces back to the primary standard is proposed. Consequently, it is confirmed that end users can instantly obtain traceability information. In addition, the execution of smart contracts requires transaction fees. Here, the calculation of the transaction fees is organized, and the traceability management system is discussed from a cost-effective perspective in the field of metrology.