Affiliation: | 1. LRSD Laboratory, Ferhat Abbas University of Setif1, Setif, Algeria;2. LRSD Laboratory, Ferhat Abbas University of Setif1, Setif, Algeria
Computer Science Dept, Mohamed El-Bachir El-Ibrahimi University, BBA, El Anceur, Algeria;3. LRSD Laboratory, Ferhat Abbas University of Setif1, Setif, Algeria
Arabic Literature and Language Department, Mouhamed Lamine Debaghine University of Setif2, Setif, Algeria |
Abstract: | The Internet of Things (IoT) is a network of interconnected smart objects having capabilities that collectively form an ecosystem and enable the delivery of smart services to users. The IoT is providing several benefits into people's lives through the environment. The various applications that are run in the IoT environment offer facilities and services. The most crucial services provided by IoT applications are quick decision for efficient management. Recently, machine learning (ML) techniques have been successfully used to maximize the potential of IoT systems. This paper presents a systematic review of the literature on the integration of ML methods in the IoT. The challenges of IoT systems are split into two categories: fundamental operation and performance. We also look at how ML is assisting in the resolution of fundamental system operation challenges such as security, big data, clustering, routing, and data aggregation. |