We have developed a comprehensive computer system to assist farmers who
practice traditional farming methods and have limited access to agricultural
experts for addressing crop diseases. Our system utilizes artificial
intelligence (AI) to identify and provide remedies for vegetable diseases. To
ensure ease of use, we have created a mobile application that offers a
user-friendly interface, allowing farmers to inquire about vegetable diseases
and receive suitable solutions in their local language. The developed system
can be utilized by any farmer with a basic understanding of a smartphone.
Specifically, we have designed an AI-enabled mobile application for identifying
and suggesting remedies for vegetable diseases, focusing on tomato diseases to
benefit the local farming community in Nepal. Our system employs
state-of-the-art object detection methodology, namely You Only Look Once
(YOLO), to detect tomato diseases. The detected information is then relayed to
the mobile application, which provides remedy suggestions guided by domain
experts. In order to train our system effectively, we curated a dataset
consisting of ten classes of tomato diseases. We utilized various data
augmentation methods to address overfitting and trained a YOLOv5 object
detector. The proposed method achieved a mean average precision of 0.76 and
offers an efficient mobile interface for interacting with the AI system. While
our system is currently in the development phase, we are actively working
towards enhancing its robustness and real-time usability by accumulating more
training samples.

我们开发了一种全面的计算机系统，用于辅助采用传统农耕方式且无法很好获得农业专家帮助的农民处理农作物病害问题。我们的系统利用人工智能技术来识别和提供蔬菜病害的解决方法，并创建了一款手机应用程序，提供用户友好的界面，允许农民用本地语言查询蔬菜病害并获得适当的解决方案。该系统可被任何具备基本智能手机操作理解能力的农民使用，重点关注西红柿病害以惠及尼泊尔当地的农业社区。