Lightweight Proof of Game (LPoG): A Proof of Work (PoW)'s Extended Lightweight Consensus Algorithm for Wearable...

Area of Science:

• Health Informatics
• Biomedical Engineering
• Computer Science

Background:

• Current healthcare systems struggle with interoperability across departments and specializations, hindering efficient patient data management.
• A patient-centric approach is crucial for automated medication and enhanced patient satisfaction, but faces challenges in security, governance, and integration.
• Existing systems lack robust data collection, retrieval, storage, and exchange capabilities for complex medical needs.

Purpose of the Study:

• To explore the integration feasibility of resource-constrained wearable kidney systems within the Industry 4.0 network.
• To propose a Healthcare 4.0 model for wearable kidney systems leveraging blockchain technology.
• To develop game theory-based consensus algorithms for secure data management in these systems.

Main Methods:

• Integration of wearable kidney devices with Industry 4.0 network infrastructure.
• Implementation of blockchain technology for secure and transparent data handling.
• Application of game theory-based consensus algorithms for resource-constrained devices.

Main Results:

• Achieved hash rates ranging from 0.10 to 0.18 million GH/s, indicating robust performance.
• Demonstrated minimal chances of majority attacks, ensuring high security.
• Reported Average Packet Delivery Rate (ADPR) between 95%-97% (without outliers) and Average Throughput (AT) between 120-250 Kbps.

Conclusions:

• The proposed system facilitates a transition from departmental-centric to data- and patient-centric healthcare models.
• Blockchain and game theory enhance transparency, trust, and healthy practices in healthcare.
• The system effectively manages data from wearable kidney devices, improving overall healthcare processes.