基于LoRa无线传感网络的农业温室大棚环境测控系统设计

Design of Agricultural Greenhouse Environment Measurement and Control System Based on LoRa Wireless Sensor Network

摘要:

温室大棚是种植反季农作物的重要环境,棚内环境参数直接决定了农作物的生产质量和数量。然而,现有的测控系统由于受天气条件等因素的影响,导致环境温湿度测试存在一定的误差。为了满足农作物的生长需求,并提高精确度,本文进行了基于LoRa无线传感网络的农业温室大棚环境测控系统的优化设计。首先,对空气温湿度、光照度、二氧化碳浓度等传感器设备进行了改装,使其成为LoRa无线传感网络的终端节点。其次,对数据处理器和控制器的内部结构进行了调整,在系统数据库中根据大棚环境测试数据内容及数据之间的逻辑关系进行了构建。在硬件系统和数据库的支持下,在农业温室大棚环境中组建了LoRa无线传感网络,并实时采集大棚的环境数据。通过LoRa无线传感网络将采集到的数据传输到系统终端。测量了大棚的温度、湿度、光照度、二氧化碳浓度等环境指标,并结合农作物生长对环境的要求,确定了环境控制目标。通过计算调整控制量,实现了系统对农业温室大棚环境的测控功能。通过对实验结果的分析,发现与传统测控系统相比,优化设计的系统在环境温湿度测试方面的误差分别降低了3.65℃和3.75%。这表明,在优化设计的系统下,大棚环境温湿度的控制误差显著降低。

Abstract:

Greenhouses are an important environment for planting off-season crops, and the environmental parameters inside the greenhouse directly determine the production quality and quantity of crops. However, the existing measurement and control systems have certain errors in environmental temperature and humidity testing due to factors such as weather conditions. In order to meet the growth needs of crops and improve accuracy, this paper optimizes the design of an agricultural greenhouse environment measurement and control system based on LoRa wireless sensor network. Firstly, sensor devices such as air temperature and humidity, light intensity, and carbon dioxide concentration were modified to become the terminal nodes of the LoRa wireless sensor network. Secondly, the internal structure of the data processor and controller has been adjusted, and the system database has been constructed based on the content of greenhouse environment testing data and the logical relationships between the data. With the support of hardware systems and databases, a LoRa wireless sensor network was established in the agricultural greenhouse environment, and real-time environmental data of the greenhouse was collected. The collected data is transmitted to the system terminal through the LoRa wireless sensor network. We measured environmental indicators such as temperature, humidity, light intensity, and carbon dioxide concentration in the greenhouse, and determined environmental control objectives based on the environmental requirements of crop growth. By calculating and adjusting the control variables, the system has achieved the measurement and control function of the agricultural greenhouse environment. Through the analysis of experimental results, it was found that compared with traditional measurement and control systems, the optimized system reduced errors in environmental temperature and humidity testing by 3.65 ℃ and 3.75%, respectively. This indicates that under the optimized design system, the control error of temperature and humidity in the greenhouse environment is significantly reduced.