We have developed a system which integrates IoT data market with Blockchain. The system allows IoT data producers to sell their IoT data such as pressure and light sensor data from Android devices in the Blockchain network and ML service providers will be able to access the IoT data in a decentralized way. We have used solidity language for our my smart contract and React for the development of front-end service.
Cellular automata (CA) consists of a simple and well-formalized model of massively parallel computing, known to be capable of universal computing. CA has rich information processing capabilities because of their parallel behaviour; however, defining their power limitations is not easy. It is a useful approach to classifying the computational capacity of CA to examine their complexity classes.
Building models that can generalize and reproduce desired tasks will enable the robots to learn and do more, which will make our lives easier. The aim of this project is to build such a model, able to learn and reproduce different tasks. We chose Learning from Demonstration as the way of teaching and we used Hidden Markov Models (HMM) with a modified version of Gaussian Mixture Regression (GMR) in order to teach a robot multiple types of trajectories together, with a small number of demonstrations for each.
