A Review of Machine Learning and Deep Learning Applications in the Internet of Things (IoT)

The Internet of Things (IoT) is made up of devices and sensors that are connected to each other and can communicate with each other in order to share and process data. All the IoT capabilities are greatly improved by the implementation of Machine Learning (ML) and Deep Learning (DL), giving rise to automation and supporting decision-making. This review paper highlights that ML and DL were implemented in different areas of IoT, namely data analytics, security, smart environments, energy optimization, and predictive maintenance. Besides, it points out the challenges, trends such as federated learning and edge DL, and presents a structured taxonomy of applications, comparative analysis, and future research directions for intelligent IoT systems.

کلیدواژه ها:

Internet of Things ، Machine Learning ، Deep Learning ، Edge Computing ، Smart Applications ، Security ، Scalability