Global demand for fresh water continues to grow and the experience of repeated drought years and climatic conditions calls for a revolution in more efficient irrigation management in agriculture. Traditional forms of irrigation have come under widespread condemnation all over the world for wastage of valuable water and leading to long-term sustainability of agriculture being compromised. To meet these challenges, the combination of new technologies such as machine learning (ML) and the Internet of Things (IoT) is essential for optimizing irrigation processes. This paper presents a systematic evaluation of smart irrigation technologies, integrating IoT and ML, based on a comparative analysis of peer-reviewed literature spanning 2019 to 2025. The paper highlights how IoT facilitates wireless data transmission to centralized systems, enhancing resource efficiency and reducing labor demands. It further explores the augmentation of IoT with ML algorithms, which analyze sensor data alongside weather predictions to optimize irrigation schedules and volumes, thereby minimizing water use while maximizing crop productivity. Finally, this study provides an in-depth analysis of IoT's impact on precision agriculture, highlighting how interconnected sensors gather essential environmental data, such as soil moisture, air temperature, and humidity to enable real-time, adaptive irrigation adjustments.