Computational Botany: A Review of Machine Learning, IoT, and Bioinformatics in Plant Sciences

The intersection of computer science and botany has catalyzed a paradigm shift in plant taxonomy, pathology, and agricultural management. This paper reviews the current literature on computational applications in plant sciences, focusing on three primary domains: Deep Learning for automated disease detection, Internet of Things (IoT) sensor networks for physiological monitoring, and high-performance computing in plant genomics. By synthesizing recent methodologies, this review identifies existing technological bottlenecks—such as dataset biases and processing latencies—and outlines future trajectories for integrating artificial intelligence into sustainable botanical research and precision agriculture.