Automated IoT-Based Monitoring of Industrial Hemp in Greenhouses Using Open-Source Systems and Computer Vision

Repository of data related to the paper: "Automated IoT-Based Monitoring of Industrial Hemp in Greenhouses Using Open-Source Systems and Computer Vision". The "Hemp_growth" folder contains hourly images of the monitored plants (C1, C2, C3, C4, and C5) from transplanting until 20 days after transplanting. The "Hemp_water_stress" folder contains the train and test data and the trained model for water stress detection. The dataset was organised into four classes corresponding to different levels of water stress: healthy plants (no stress); plants with three days without irrigation; plants with six days without irrigation; and plants with nine days without irrigation. Training and test sets were prepared for each class with the following distributions (approx. 80% for training and 20% for test): • 81 images of healthy plants for training and 20 for test; • 90 images corresponding to 3 days of stress for training and 20 images for test; • 70 images with 6 days of stress for training and 17 for test; • 64 images of plants with 9 days of stress for training and 16 for test.本数据集为关联论文《基于开源系统与计算机视觉的温室工业大麻物联网自动化监测》（Automated IoT-Based Monitoring of Industrial Hemp in Greenhouses Using Open-Source Systems and Computer Vision）的数据仓库。 「Hemp_growth」文件夹包含了自移栽至移栽后20天期间，供监测植株（C1、C2、C3、C4及C5）的每小时采集图像。 「Hemp_water_stress」文件夹包含了用于水分胁迫检测的训练数据、测试数据与训练完成的模型。本数据集被划分为四个类别，分别对应不同程度的水分胁迫：健康植株（无胁迫）、停灌3天的植株、停灌6天的植株以及停灌9天的植株。已针对每个类别按约80%训练集、20%测试集的比例划分训练与测试集，具体分布如下： • 健康植株：训练集含81张图像，测试集含20张图像； • 停灌3天胁迫组：训练集含90张图像，测试集含20张图像； • 停灌6天胁迫组：训练集含70张图像，测试集含17张图像； • 停灌9天胁迫组：训练集含64张图像，测试集含16张图像。