Convergence of blockchain with IoT has been discussed at length in , Scalability and Other Challenges.
Briefly, it can be said that due to the authenticity, integrity, privacy, and shared nature of blockchains, IoT networks will benefit greatly from blockchain technology.
A Complete Guide to Understanding This Blockchain Concept
This can be realized in the form of an IoT network that runs on a blockchain and makes use of a decentralized mesh network for communication to facilitate Machine-to-Machine (M2M) communication in real time.
All this data which is generated as a result of M2M communication can be used in the machine learning process to augment the functionality of Artificially Intelligent DAOs or simple AAs.
AAs can act as agents in a Distributed Artificial Intelligence (DAI) environment provided by a blockchain and can learn over time using machine learning processes.
AI is a field of computer science that endeavors to build intelligent agents that can make rational decisions based on the scenarios and environment that they observe around them.
Machine learning plays a vital role in AI by making use of raw data as a learning resource.
A key requirement in AI-based systems is the availability of authentic data that can be used for machine learning and model building.
Why This Matters for Blockchain Technology
The explosion of data coming out IoT devices, smartphone’s, and other data acquisition means that AI and machine learning is becoming more and more powerful.
Once consumers, producers, and other entities are on a blockchain, the data that is generated as a result of interaction between these entities can be readily used as an input to machine learning engines with a guarantee of authenticity.
It could be argued that if an IoT device is hacked, it can send malformed data to the blockchain.
This issue is mitigated because an IoT device is part of the blockchain (as a node) and has all security properties applied to it as a standard node in the blockchain network.
Key Points to Remember
- Convergence with other industries Convergence of blockchain with IoT has been discussed at length in , Scalability and Other Challenges.
- Briefly, it can be said that due to the authenticity, integrity, privacy, and shared nature of blockchains, IoT networks will benefit greatly from blockchain technology.
- This can be realized in the form of an IoT network that runs on a blockchain and makes use of a decentralized mesh network for communication to facilitate Machine-to-Machine (M2M) communication in real time.
- All this data which is generated as a result of M2M communication can be used in the machine learning process to augment the functionality of Artificially Intelligent DAOs or simple AAs.
Going Deeper: Advanced Concepts
These properties include incentivization of good behavior, rejection of malformed transactions, and strict verification of transactions and various other checks that are part of blockchain protocol.
Therefore, even if an IoT device is somehow hacked, it would be treated as a Byzantine node by the blockchain network and would not cause any adverse impact on the network.
Moreover, the possibility of combining intelligent Oracles, intelligent, smart contracts, and AAs will give rise to Artificially Intelligent Decentralized Autonomous Organizations (AIDAOs) that can act on behalf of humans to run entire organizations on their own.
This is another side of AI that can become norm in the future.
Conclusion
Convergence with other industries represents one of the many innovative layers that make blockchain technology so powerful and transformative. As distributed systems continue to evolve, a solid understanding of these core concepts becomes increasingly valuable — not just for developers, but for anyone building, investing in, or working alongside blockchain-powered systems.
Whether you are just starting your blockchain journey or deepening existing expertise, mastering these fundamentals gives you the tools to think clearly about decentralized systems and make smarter decisions in this rapidly evolving space.