This paper presents the health monitoring system and early detection of disease in black pepper plants by integrating an IoT-enabled smart sensor system with a transfer learning based Convolutional Neural Network (CNN) model. The system is designed to continuously monitor essential parameters influencing plant growth, such as temperature, humidity, soil nutrients, and moisture levels, while simultaneously detecting infectious diseases. Utilizing the pre-trained VGG16 architecture, the CNN model is fine-tuned to classify diseases based on leaf images. Experimental findings demonstrate that the transfer learning model surpasses conventional CNNs, exhibiting superior accuracy across training, testing, and validation datasets. The proposed system serves as a valuable tool for farmers, empowering them to make informed decisions and implement timely interventions, thereby enhancing crop health and yields in black pepper cultivation.