The use of blockchain to support distributed AI implementation in IoT systems

This paper presents a distributed and decentralized architecture for the implementation of Distributed Artificial Intelligence (DAI) using hardware platforms provided by the Internet of Things (IoT). A trained DAI system has been implemented over the IoT, where each IoT device acts as one or more of the neurons within the DAI layers. This is accomplished through the utilization of decentralized, self-managed blockchain technologies that allow trusted interactions and information to be exchanged between distributed neurons. The platform was built and customized to be used within the IoT system, and it is capable of handling DAI-related tasks. A new consensus mechanism based on Proof of Authority (PoA) and Proof of Work (PoW) has been designed and implemented, along with bespoke block and transaction formats. The proposed architecture was analyzed, implemented, and tested using a dedicated testbed with low-cost IoT devices. A quantitative measurement and performance evaluation of the system based on a real-world IoT application was conducted. The implemented DAI is found to have an accuracy of 92%-98%, with an energy cost of 0.12 joules (J) when utilizing a Raspberry Pi to run one neuron. The measured hash per joule (h/J) when using a Raspberry Pi for mining is 13.8Kh/J compared to 54Kh/J using an ESP32. The results showed that it is feasible to implement a DAI system utilizing the IoT hardware platform while maintaining the system’s accuracy. The integration of the blockchain has added an element of security and trust to the data and the interaction between system components.