Title: Machine Learning with IoT: Leveraging AI to Enhance IoT Systems and Applications

Abstract By facilitating intelligent, data-driven decision-making, the combination of machine learning (ML) and the internet of things (IoT) is transforming a number of industries. When paired with machine learning algorithms, the Internet of Things (IoT), which links devices and sensors to gather and share data, makes it easier to create intelligent systems that can analyse enormous amounts of data in real time. The synergy between ML and IoT is examined in this study, with an emphasis on how this combination might improve the performance of IoT systems in industries including smart cities, healthcare, and agriculture. Important machine learning methods used with IoT systems are covered, including deep learning, reinforcement learning, and supervised and unsupervised learning. The difficulties are also discussed, such as computing constraints, data privacy, and security. This study highlights how machine learning may solve the complexities of IoT networks, increase automation, and optimize decision-making processes. It does this by doing a thorough assessment of recent studies and identifying the potential benefits, impacts, and future directions of ML in IoT applications.