Secure sharing and monitoring of patient data through a blockchain-based iot healthcare platform

This thesis presents the design and implementation of a comprehensive decentralized healthcare platform that leverages blockchain technology and IoT infrastructure to enable secure sharing, real-time monitoring, and controlled access to patient data. Unlike traditional healthcare information systems that rely heavily on centralized servers and third-party intermediaries, the proposed platform introduces a blockchain-based IoT architecture that ensures data integrity, patient privacy, and robust security against unauthorized access and manipulation. With the exponential growth of digital healthcare systems, data breaches and cyberattacks targeting hospitals and medical institutions have increased dramatically, creating a critical need for innovative technological solutions that emphasize decentralization, transparency, and patient-driven data ownership. The developed platform addresses these challenges by integrating low-cost IoT hardware with a blockchain-backed access control system that allows patients to decide who can view and use their medical information. The platform is built on three main layers: IoT Data Acquisition Layer: Raspberry Pi devices, equipped with medical sensors (such as temperature, heart rate, and blood pressure modules), continuously collect patient health metrics. These readings are securely encrypted and transmitted to the blockchain network. Blockchain Security and Access Management Layer: Custom-developed smart contracts deployed on an Ethereum-based blockchain ensure immutability and tamper-proof data storage. A role-based access control (RBAC) mechanism is implemented within these smart contracts, enabling patients to grant or revoke data-sharing permissions to specific doctors, family members, or healthcare providers. Web-Based Healthcare Platform: A user-friendly front-end application offers dedicated panels for both patients and doctors. Patients can monitor their own health data in near real-time, manage data-sharing permissions, and review historical medical records. Doctors, on the other hand, gain authorized access to patients' health metrics, allowing them to provide timely medical interventions and consultations. A key feature of this platform is its secure sharing mechanism. Unlike centralized systems where hospital administrators or external entities control access, the proposed blockchain-based model enforces patient sovereignty over personal health data. Access permissions are cryptographically recorded on the blockchain, making them transparent, auditable, and resistant to tampering. Only verified Ethereum addresses belonging to authorized doctors can modify or update patient records, while patients retain the ability to instantly revoke access at any time. This fine-grained permission control significantly reduces privacy risks and enhances trust between patients and healthcare professionals. The back-end of the system is implemented using Python and Flask, enabling the Raspberry Pi to send continuous health data updates to the blockchain every 10 seconds. This real-time data acquisition simulates a live medical monitoring scenario, demonstrating the platform's ability to handle frequent sensor inputs without performance degradation. The front-end is developed using HTML, CSS, and JavaScript, with Web3.js and Ethers.js libraries facilitating secure interaction with the blockchain. User identities and transaction signing are handled through the MetaMask browser extension, ensuring private keys remain protected during medical record updates and access operations. Extensive experimental evaluations were carried out to validate the platform's performance, scalability, and security. In a simulated hospital environment, Raspberry Pi devices generated mock medical data that was continuously transmitted to the blockchain. Performance metrics such as latency, transaction confirmation speed, access permission enforcement, and system responsiveness under varying data loads were thoroughly analyzed. Results indicated that the average latency between data generation and visibility on the web interface was 2.1 seconds, with a minimum of 1.5 seconds and a maximum of 3.8 seconds. Access control tests confirmed that unauthorized users were completely blocked from viewing or modifying patient data, while authorized doctors received immediate access following patient approval. These findings demonstrate that the proposed platform is highly suitable for real-time patient monitoring and secure healthcare data sharing. The system architecture provides strong guarantees of data integrity and auditability. Once health records are written to the blockchain, they become immutable, preserving historical accuracy—a critical factor for medical decision-making. The blockchain-enforced RBAC model eliminates dependence on traditional centralized authentication servers, reducing vulnerability to single points of failure and cyberattacks. Additionally, the distributed nature of blockchain enhances resilience against data loss and malicious tampering, ensuring that patient information remains reliable and trustworthy. From a broader perspective, this research contributes significantly to the field of blockchain-based health informatics. It demonstrates that low-cost IoT devices, when combined with decentralized blockchain technology, can form the foundation of a scalable, secure, and patient-centered healthcare ecosystem. The platform not only facilitates efficient medical data collection but also empowers patients with unprecedented control over their health information—an essential step toward next-generation digital healthcare systems. Looking ahead, several enhancements are proposed to further improve and scale the platform: Integration with IPFS or decentralized storage: Enabling storage of large medical datasets (diagnostic images, laboratory reports) while keeping blockchain transactions lightweight by storing only secure references on-chain. Advanced encryption and privacy-preserving techniques: Implementing end-to-end encryption on the IoT devices to ensure that sensitive data is protected even before reaching the blockchain. Future research may explore advanced cryptographic methods such as homomorphic encryption and zero-knowledge proofs for secure multi-party medical data analysis. Deployment on public or Layer-2 blockchains: Migrating the prototype from the Ganache test network to public Ethereum or high-throughput Layer-2 solutions to evaluate real-world scalability and cross-institutional data sharing. AI-powered analytics: Leveraging artificial intelligence and machine learning models to analyze blockchain-stored medical data for predictive healthcare insights, early disease detection, and automated medical alerts. In conclusion, this thesis provides a holistic approach to decentralized healthcare platforms, combining IoT-based medical data acquisition with blockchain-enabled secure sharing and monitoring mechanisms. The developed prototype demonstrates the feasibility of delivering transparent, traceable, and tamper-proof patient data management without relying on centralized servers. It is particularly suited for hospitals, home-care setups, rural clinics, and resource-limited healthcare environments where trust, security, and accessibility are paramount. By offering a robust foundation for future innovations, this work paves the way for a global shift toward secure, patient-controlled, and decentralized digital health infrastructures, setting new standards in healthcare data management and resilience.