Abstract: A method (100) for performing event detection on a data stream is disclosed, the data stream comprising data from a plurality of devices connected by a communications network. The method comprises using an autoencoder to concentrate information in the data stream, wherein the autoencoder is configured according to at least one hyperparameter (110) and detecting an event from the concentrated information (120). The method further comprises generating an evaluation of the detected event on the basis of logical compatibility between the detected event and a knowledge base (130), and using a Reinforcement Learning (RL) algorithm to refine the at least one hyperparameter of the autoencoder, wherein a reward function of the RL algorithm is calculated on the basis of the generated evaluation (140). Also disclosed are a system (900) for performing event detection, and a method (1100) and node (1200) for managing an event detection process.

Abstract: A method and a system for reducing the size of a blockchain. The blockchain includes a first set of two or more blocks including an initial genesis block. A new genesis block for the blockchain is generated. The first hash value resulting from hashing the new genesis block matches a second hash value resulting from hashing a last block from the first set of blocks, and the difficulty of determining the first hash value is computationally greater than the cumulative difficulty of determining hash values of all blocks in the first set of blocks. The new genesis block is transmitted to one or more blockchain nodes of a blockchain network, and the first set of blocks is replaced with the new genesis block.