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Blockchain and AI-based Solutions to Combat Coronavirus (COVID-19)-like Epidemics: A Survey (2106.14631v1)

Published 28 Jun 2021 in cs.CR and eess.SP

Abstract: The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems in timely handling public health emergencies. In such contexts, innovative technologies such as blockchain and AI have emerged as promising solutions for fighting coronavirus epidemic. In particular, blockchain can combat pandemics by enabling early detection of outbreaks, ensuring the ordering of medical data, and ensuring reliable medical supply chain during the outbreak tracing. Moreover, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Therefore, we present an extensive survey on the use of blockchain and AI for combating COVID-19 epidemics. First, we introduce a new conceptual architecture which integrates blockchain and AI for fighting COVID-19. Then, we survey the latest research efforts on the use of blockchain and AI for fighting COVID-19 in various applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. A case study is also provided using federated AI for COVID-19 detection. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.

Blockchain and AI-Based Solutions for Coronavirus Epidemics: A Survey

The paper "Blockchain and AI-based Solutions to Combat Coronavirus (COVID-19)-like Epidemics: A Survey" undertakes a comprehensive exploration of technological interventions with a focus on blockchain and AI in the context of managing coronavirus epidemics. The authors aim to present a detailed survey of the application spectrum and effectiveness of these technologies in combating virus outbreaks akin to COVID-19.

Conceptual Integration of Blockchain and AI

The paper introduces a conceptual architecture integrating blockchain and AI as overarching frameworks to streamline health crisis management. Blockchain enhances the reliability and security of data exchange critical to early outbreak detection, real-time epidemic monitoring, and efficient medical supply chains. AI complements these capacities by offering predictive analytics for outbreak trends, facilitating diagnostic processes, and supporting drug discovery.

Blockchain Applications in Epidemics

The authors segregate the blockchain applications into different functional areas:

  • Outbreak Monitoring: Blockchain's capability to record real-time data securely fosters a transparent and immutable record of outbreaks, which is crucial for tracking and mitigating the spread.
  • Safe Operations and Economic Continuity: Facilitating remote, decentralized transactions assures continued economic activities while minimizing physical interaction, thus reducing contagion risk.
  • Medical Supply Chains: Blockchain's tracking features ensure transparency and security in logistics, thereby fortifying supply lines of medical provisions.
  • Donation Tracing: The paper highlights blockchain's role in ensuring trust and transparency in donations, critical for managing supply to affected populations effectively.

AI Solutions for Epidemic Management

AI's role emerges primarily in diagnostic and predictive contexts:

  • Outbreak Prediction: Machine learning models can analyze vast datasets to predict future outbreak patterns, offering essential foresight for preparedness.
  • Diagnostic Support: Deep learning applications leverage medical imaging for precise, rapid diagnosis of virus infections, enhancing clinical response and treatment accuracy.
  • Treatment and Vaccine Development: AI aids in identifying potential antiviral compounds and structure prediction for vaccine targets, crucial for therapeutic advancements against emerging strains.

Efficacy and Future Directions

Numerical results and case studies illustrate substantial improvements in performance and reliability through combined blockchain and AI applications. The paper proposes federated learning as a pathway to optimize AI capabilities while safeguarding sensitive health data—a crucial aspect given privacy concerns in sharing medical data.

Challenges and Opportunities

Despite demonstrated capabilities, the deployment of these technologies faces challenges such as regulatory compliance, data privacy, security vulnerabilities, and the need for interoperable datasets across platforms. Advances in blockchain scalability, AI model precision, and integration with other technologies like IoT and 5G could pave the way for robust epidemic management systems.

Conclusion

The synthesis of blockchain and AI represents a promising frontier for epidemic preparedness and response. This survey not only identifies the current capabilities but also steers the discussion toward addressing inherent challenges and harnessing future technological opportunities. The work underscores the critical role these technologies play in evolving health strategies that efficiently handle public health emergencies akin to COVID-19.

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Authors (4)
  1. Dinh C. Nguyen (43 papers)
  2. Ming Ding (219 papers)
  3. Pubudu N. Pathirana (35 papers)
  4. Aruna Seneviratne (43 papers)
Citations (168)