Waterberry Farms benchmark (WBF)

Waterberry Farms benchmark (WBF) 是一个针对精确农业应用的基准数据集，由北佛罗里达大学创建。该数据集模拟了佛罗里达州一个种植多种作物类型的农场环境，重点关注植物疾病的动态传播和土壤湿度的变化。WBF数据集包含约90000000条数据，涵盖了多种环境变量和时间序列数据，旨在通过模拟真实农业环境，评估和推动路径规划及估计算法的发展。数据集通过GitHub平台公开，支持开放源代码MIT许可，适用于多机器人信息收集和路径规划算法的测试与研究。

Waterberry Farms benchmark (WBF) is a benchmark dataset designed for precision agriculture applications, developed by the University of North Florida. This dataset simulates a multi-crop farm environment located in Florida, with a core focus on the dynamic spread of plant diseases and variations in soil moisture. The WBF dataset contains approximately 90,000,000 data entries, covering diverse environmental variables and time-series data. Its primary objective is to evaluate and facilitate the advancement of path planning and estimation algorithms by replicating real-world agricultural scenarios. The dataset is publicly hosted on GitHub under the open-source MIT License, and is applicable for testing and conducting research on multi-robot information collection and path planning algorithms.