With the proven effectiveness that both offer when used individually, the combination of the two has a host of advantages that go beyond data security and transparency. With both blockchain and ML merged to work together, data scientists or company administrators can make better or more informed decisions based on the predictability of the latter. Let’s talk about Surprising use cases of machine learning blockchain.

Machine learning blockchain advantages

Enhanced security & transparency

Surprising use cases of machine learning in blockchain

The data is stored in blocks and sealed using cryptographic encryption which makes it impossible to manipulate. In fact, adding data to a block that follows a consensus model is very difficult to boycott. Besides this security advantage, the stored data is easily visible to anyone with access (depending on the type of blockchain), bringing a high level of transparency to data systems.

Lower maintenance costs

Startups or companies that incur frequent maintenance costs can find solace in blockchain technology and machine learning. Maintenance schedules can be registered on the blockchain to allow everyone responsible for a specific task to track when they might need to act. ML can help predict the right time frame to be made, based on the collected data.

Combining the qualities of both blockchain and machine learning, every personnel or service provider will be updated when they need it and the exact time when maintenance is carried out. This information can help prevent system failures and directly help reduce costs.

General Data Management

Having established that blockchains are digital ledgers that store information and ML as a tool for predicting actions, the combination of the two can help improve data management. System data will not only be stored securely, other functions of checking, sharing and manipulating data can be performed easily.

Surprising use cases of machine learning in blockchain

Supply chain & logistics

Surprising use cases of machine learning in blockchain

The Logistics and supply chain industry use a lot of data, which if not handled properly can complicate operations. Blockchain technology can be used for efficient commodity record keeping as well as product tracking through its open source framework.


Blockchain technology can help automate various aspects of a typical production outfit. With blockchain, the stock of resources can be stored transparently, and it also enhances production, maintains database security, ensures quality control, and supports compliance checks. . With ML integration, maintenance schedules can be well tracked and predictable, all working in tandem to avoid component failures and overall costs. Prediction algorithms are used.

Surprising use cases of machine learning in blockchain

Energy & utilities

One of the most widespread uses of machine learning blockchain is gaining traction for use in energy exchanges. More and more startups are using blockchain to improve energy consumption. While IOTA is one of the companies that has introduced blockchain-powered energy production and consumption in a peer-to-peer manner, the Sun exchange in South Africa has built a network of distribution and payments using blockchain. solar energy using blockchain ledger technology.

Surprising use cases of machine learning in blockchain


Health records are now stored on the blockchain for enhanced data security and easy sharing among trusted employees. While blockchain has advantages in performing these prominent roles, merging with ML will make the technology even more fruitful. Machine Learning algorithms can help predict prescriptions for a specific disease and aid decision-making in a number of data-driven medical diagnoses.

Blockchain technology and machine learning are two unique data-centric innovations that are changing our world today. Although both are said to be revolutionary, they are, in every way, futuristic. Hope that these Surprising use cases of machine learning blockchain help you come up with good ideas for your own company.

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