In India, major portion of popularity depends on farming. Due to seasonal disbalance of weather, crop diseases are now becoming a major concern for farmers. This research paper mainly focuses on smart agricultural disease detection using the Internet of Things (IoT) and forecasting suitable weather to safeguard our precise resources of daily living using several Machine Learning (ML) and Deep Learning (DL) models. IoT technology integrates various types of input data, viz. Visual images, moisture level, humidity level, and temperature from that area. YOLOv8 is the latest version of the You Only Look Once family that is a pre-trained model as well as it gives high accuracy in the detection process. This model captures the visual characteristics of images in a numerical form i.e. Convolutional Neural Network (CNN). The performance of our ML model named YOLO-new effectively detects the plant’s disease and provides an overall accuracy gives 98% accuracy and F1 score is 96% in all classes. This fusion allows for a comprehensive analysis and insights across different fields, enhancing our understanding and application of technology in areas such as healthcare, agriculture, and environmental monitoring.