Intelligent Vineyard Multimodal Dataset

The current agricultural industry faces challenges such as low production efficiency and severe resource waste. Traditional agricultural management lacks data support, resulting in inaccurate decisions. Existing solutions focus mostly on single data sources, lacking comprehensive analysis of multimodal data. This dataset aims to provide comprehensive data support by integrating vineyard images, sensor data, and management records, helping agricultural practitioners make more scientific decisions. Data is collected using high-resolution cameras and various sensors under different times and climatic conditions to ensure data diversity and representativeness. In terms of quality control, the data undergoes multiple rounds of annotation and consistency checks and is reviewed by agricultural experts. Data storage uses JPEG format for images and JSON format for sensor and management records, facilitating rapid reading and analysis. The core advantage of this dataset is its high data quality, with annotation precision exceeding 95%, good consistency, and high completeness. By introducing new data augmentation technologies and quality assessment methods, the application value of the dataset is significantly enhanced, effectively improving the accuracy of object detection and increasing decision-making efficiency in agricultural management, with an expected increase in crop yield of up to 10%.