A Blockchain-based Fog-IoT Platform for Improving Wearable IoT Applications in Healthcare

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University of Guelph
Abstract

Health-based conditions are growing exponentially, and healthcare resources are getting limited. In response, the health industry must adapt. Wearable IoT devices introduce a convenient way to collect patient data wirelessly and deploy services remotely. Wearables are portable technologies worn for monitoring patient data. However, although it can improve healthcare services, it can also introduce many challenges. The issues addressed by this thesis are patient privacy, data flow, server interactability, device standardization, and scalability.

This thesis proposes a platform design to address these challenges. It incorporates a Fog-based IoT network architecture for managing the data within the healthcare network, providing an organized means of improving data flow and scalability. The platform adds wireless architectures such as WBANs and REST APIs to address server interactability and device standardization issues. Next, it incorporates blockchain technology to manage security. Also, the platform adds techniques such as Smart contracts and Federated learning to reinforce privacy.

The thesis presents implementations of these technologies and strategies and their ability to address these challenges. These implementations are from past research that became academic articles either published or under review. Presenting these works also includes the testbeds and analyses used to evaluate the feasibility of their highlighted approach or technology incorporated into the platform. The testbeds evaluated the Fog-IoT architecture and showed its feasibility in improving the data flow and scalability of the healthcare network. Also, the testbeds that specifically implemented the supporting architectures of WBANs and RESTAPIs showed their ability to reinforce data and device manageability within the Fog-IoT network by showing improvements to the platform through experiments measuring latency and throughput. Next, the testbeds that evaluated the private blockchain showed its advantages over its public variants by yielding results proving its efficiency in processing time.

Furthermore, Smart contracts contributed to reducing the server response time through automation. Also, Federated learning proved its ability to ensure service integrity and preserve privacy by keeping the health-based predictive learning service accurate while adding privacy-preserving functionality. Overall, each solution and approach combines into a proposed blockchain-based Fog-IoT platform that shows overwhelming promise in improving wearable IoT in healthcare.

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Keywords
Internet of Things, Blockchain, Fog computing, Wearable IoT, Healthcare, Network Security
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