花菇种植环境监测分析数据

采集花菇大棚的湿度、温度、菌棒湿度、菌棒温度、二氧化碳、光照强度、气流等数据，评估环境条件对花菇生长的影响，构建花菇品质与环境参数关联的深度网络模型，为基于数据驱动的环境智能调控方法提供有效的数据支持，同时可将优化经验应用于外部环境，形成花菇养植微环境的多维度细粒度感知与控制，促进花菇养植产业向科学、高效、模式可移植的方向发展。1、采用土壤温湿度传感器、空气温湿度传感器、风速传感器、光照传感器、二氧化碳传感器、物联网监测箱等物联网设备，以无线网络（5G/WiFi）+有线网络双通道的方式，构建含感知层、传输层、处理层和应用层的分层分布式系统结构，以实现温度、湿度、风速、光照、二氧化碳等多维数据的全方位感知、高可靠传输；2、利用数据清洗和数据集成技术对采集到的温度、湿度、风速、光照、二氧化碳等多维数据进行处理和合并，完成数据预处理以提高数据质量并实现多源数据融合。利用人工智能和深度学习在数据挖掘及信息特征提取上的优势，从海量实验样本数据中学习花菇生长质量与温度、湿度、风速、光照、二氧化碳等多源环境参数间的复杂高维关联，结合时间序列分析方法，构建花菇品质与环境参数关联的深度网络模型；并采用深度强化学习方法和优化控制算法在数字空间实现环境参数的控制与优化。3、为花菇培育环境提供数据支撑，增加花菇产量，实现花菇种植模式可复制。

This dataset collects data including humidity, temperature, substrate stick humidity, substrate stick temperature, carbon dioxide, light intensity and airflow in shiitake mushroom cultivation sheds, to evaluate the impact of environmental conditions on shiitake mushroom growth, construct a deep neural network model correlating shiitake mushroom quality with environmental parameters, provide effective data support for data-driven intelligent environmental regulation methods, apply optimization experience to external environments, form multi-dimensional fine-grained perception and control of the micro-environment for shiitake mushroom cultivation, and promote the development of the shiitake mushroom cultivation industry towards being scientific, efficient and with transplantable cultivation models.
1. Adopt IoT devices including soil temperature and humidity sensors, ambient air temperature and humidity sensors, anemometers, illuminance sensors, carbon dioxide sensors and IoT monitoring boxes, build a hierarchical distributed system architecture with perception layer, transmission layer, processing layer and application layer via the dual-channel mode of wireless network (5G/WiFi) + wired network, to achieve comprehensive perception and high-reliability transmission of multi-dimensional data such as temperature, humidity, wind speed, light and carbon dioxide.
2. Use data cleaning and data integration technologies to process and merge the collected multi-dimensional data including temperature, humidity, wind speed, light and carbon dioxide, complete data preprocessing to improve data quality and realize multi-source data fusion. Leveraging the advantages of artificial intelligence and deep learning in data mining and information feature extraction, learn the complex high-dimensional correlations between shiitake mushroom growth quality and multi-source environmental parameters including temperature, humidity, wind speed, light and carbon dioxide from massive experimental sample data, combine with time series analysis methods to construct a deep neural network model correlating shiitake mushroom quality with environmental parameters, and adopt deep reinforcement learning methods and optimization control algorithms to realize the control and optimization of environmental parameters in the digital space.
3. Provide data support for shiitake mushroom cultivation environments, increase shiitake mushroom yield, and realize replicable shiitake mushroom cultivation models.

搜集汇总

数据集介绍

特点

该数据集包含花菇种植环境的实时监测数据，涵盖空气和菌棒的温湿度、二氧化碳浓度、光照强度和气流等关键参数，旨在通过数据分析和模型构建优化花菇种植环境，提高产量和质量。