Convergence of blockchain, IoT, and machine learning: exploring opportunities and challenges – a systematic review

Vaccine quality

Demand forecasting

Trust among stakeholders

Predictive maintenance

Automated response

Checks whether the user initiating or requesting a transaction is a legitimate user.

- Ensures that the user has the right to request the large characters of the transaction they are carrying out.

Ledgers are only appendices. The transaction cannot be modified once it has been recorded. Details will be manually entered and human error will always be possible. Care should be taken or additional privileges should be granted to an authority.

BCT keeps a record of each transaction, including a copy of the history. The size of the database would increase, which could make it more complex to manage in the future.

Explores the synergy between blockchain and AI

Examines their applications in various industries, particularly in transportation.

Blockchain and AI technology convergence with significant advantages in the transportation industry.

Blockchain could enhance AI applications in terms of trustworthiness, decentralized computing, effectiveness, transparency, and lower entry market barriers.

The AI applications could improve the blockchain in several aspects, including energy consumption, scalability, security, privacy, efficiency, hardware, and data gates.

Storage capacity and scalability

Security and privacy

Limited data access

Domain identification

Enhances blockchain security with AI

Automates processes and reduces intermediaries

Analyzes data for insights

Improves security, automation, transparency, efficiency, and predictive maintenance

Energy consumption associated with blockchain.

Potential vulnerabilities

Data privacy concerns

Scalability

Detects and prevents food safety hazards.

Maintains track of perishable food with an immutable ledger.

Streamlines supply chain, connecting farmers directly with customers.

Enhances efficiency, transparency, and sustainability in the food chain.

Rapid and precise contamination detection.

Increased trust in the food supply chain.

Detailed bibliometric analysis and visualization.

Reliance on a single bibliometric tool limits analysis depth.

Limited applications in other smart agriculture areas.

Potential data privacy issues.

Limitations in data collection methods.

Explores how blockchain and AI can be used to improve the performance of IoT systems.

Focuses on the potential benefits, limitations, challenges, and future research directions in this emerging field.

Conducts a review of the integration of edge computing and blockchain into IoT systems, covering aspects of system architectures, categories of blockchain-based edge deployment, security requirements, and potential applications.

Discusses challenges and insights into the future directions of blockchain-based edge IoT systems.

The ability of the framework to exchange not only datasets but also the skills of data providers, using integrated operational factors.

Use of a revolutionary approach combining blockchain and crowdsensing to demonstrate relevance in the IoT context.

Lack of scalability when faced with a large number of IoT data streams.

Need for a robust solution to manage high volumes and speeds of IoT data.

System performance is subject to degradation as the number of IoT devices increases.

Power energy consumption

Huge overload of network throughput

Expandability to introduce new monitor and execution processes in the existing blockchain-based system.

Uses blockchain in verifying certificates efficiently without the participation of a third party.

Improves the scalability and security of the IoT applications by using the distributed characteristics of the chain.

Lack of a detailed examination of potential challenges related to data processing.

Insufficient exploration of how the proposed PKI manages the volume and speed, and efficiency of data processing would contribute to a more comprehensive understanding of the practical implications and potential limitations of the proposed solution.

Examines various proposed frameworks in the literature, focusing on their use of BCT to enhance IoT forensics.

Evaluates the readiness of blockchain integration in addressing challenges.

Addresses the challenges associated with data integrity, shared storage, identification, transparency, and privacy in IoT forensics.

Addresses factors when integrating BCT into IoT forensics.

Proposes a new protocol called blockchain-based IoMT.

Authenticated Key Exchange BIoMTAKE establishes a private/consortium blockchain-based distributed protocol that eliminates the need for a single trusted authority and ensures secure access to data generated by IoMT devices.

Merges blockchain and IoT in one system to lead to issues such as higher latency, centralization, and a single point of failure.

Lacks an in-depth exploration of its scalability, especially concerning the potential surge in data volume as the IoT devices generate a large amount of heterogeneous data that do not delve into potential data transmission latency issues that may arise in a blockchain-based distributed environment.

Explores the blockchain technologies’ ability to address challenges, such as digital evidence authenticity, integrity, confidentiality, and privacy, which may impact the investigation process in IoT forensics.

Proposes a holistic forensic process and identifies blockchain integration patterns to establish a secure and scalable architecture.

Lack of improvement in the quality of evidence, particularly IDS alerts, which can be addressed through the application of ML techniques or algorithms.

Development of a hybrid IDS using blockchain and Fuzzy Sets Theory, demonstrating exceptional accuracy in identifying various behaviors within the IoT for maintaining data security and IoMT functionality.

Explores the security problems related to user privacy data based on blockchain and Fuzzy Sets Theory.

Does not apply the method to mobile sensing nodes.

Absence of real-world validation or deployment of the proposed hybrid intrusion detection method.

IoMTs

The use of the technology–organization– environment theories to examine blockchain–IoT adoption enablers.

A framework based on the Graph Theory Matrix Method to measure the extent of a readiness to adopt blockchain IoT.

Complex evaluation process.

Limited expert involvement

Lack of technical performance

Analysis suggests the need for further research to conduct a comprehensive cost analysis of the technical infrastructure and evaluate the technical performance of BIoT in terms of scalability, throughput, storage, and latency on a network.

Logistics and Supply Chains Management

Industry 4.0