MODEL OF AI INTERACTION WITH IOT DEVICES AT THE SOFTWARE UPDATE LEVEL
DOI 10.31673/2412-4338.2025.024431
Abstract
Abstract: Modern IoT systems consist of millions of heterogeneous devices that require regular software updates to maintain functionality and security. Traditional methods of deploying updates are often insufficiently flexible and efficient, especially in dynamically changing network environments. This paper proposes an innovative model of interaction between artificial intelligence (AI) and IoT devices at the software update level that combines the advantages of canary releases with intelligent optimisation algorithms. The study focuses on the development of a mathematical model for intelligent update deployment that takes into account the following key aspects: phased implementation of changes (canary releases), automated monitoring of system stability, and adaptive decision-making based on machine learning algorithms. The proposed model uses Reinforcement Learning methods to dynamically select the optimal deployment strategy, which minimises the risk of failures and optimises the use of network resources.
Particular attention is paid to the formalisation of the deployment process using a mathematical apparatus, including: the definition of criteria for successful updates, cost functions for assessing the quality of deployment, and real-time decision-making algorithms. The results of the study demonstrate that the integration of AI into the process of updating IoT devices can significantly improve system stability and reduce the number of failures during large-scale deployments. The article also discusses promising areas for further research, including the introduction of federated learning for decentralised data analysis, integration of blockchain technologies to improve update security, and development of adaptive algorithms for heterogeneous IoT networks. The proposed approach opens up new opportunities for the creation of intelligent, self-managed IoT systems capable of operating effectively in a dynamically changing environment.
Keywords: artificial intelligence, IoT, information system, software updates, canary releases, machine learning, update deployment, network optimization.
