Department of Bio-Systems Engineering, Institute of Smart Farm, Gyeongsang National University, Jinju 52828, Republic of Korea.
Ministry of Communication and Information Technology, Singhadurbar, Kathmandu 44600, Nepal.
Sensors (Basel). 2024 May 28;24(11):3468. doi: 10.3390/s24113468.
The optimal indoor environment is associated with comfortable temperatures along with favorable indoor air quality. One of the air pollutants, particulate matter (PM), is potentially harmful to animals and humans. Most farms have monitoring systems to identify other hazardous gases rather than PM due to the sensor cost. In recent decades, the application of environmental monitoring systems based on Internet of Things (IoT) devices that incorporate low-cost sensors has elevated extensively. The current study develops a low-cost air quality monitoring system for swine buildings based on Raspberry Pi single-board computers along with a sensor array. The system collects data using 11 types of environmental variables along with temperature, humidity, CO, light, pressure, and different types of gases, namely PM, PM, and PM. The system is designed with a central web server that provides real-time data visualization and data availability through the Internet. It was tested in actual pig barns to ensure stability and functionality. In addition, there was a collocation test conducted by placing the system in two different pig barns to validate the sensor data. The Wilcoxon rank sum test demonstrates that there are no significant differences between the two sensor datasets, as all variables have a p-value greater than 0.05. However, except for carbon monoxide (CO), none of the variables exhibit correlation exceeding 0.5 with PM concentrations. Overall, a scalable, portable, non-complex, low-cost air quality monitoring system was successfully developed within a cost of USD 94.
最佳室内环境与舒适的温度以及良好的室内空气质量有关。空气污染物之一的颗粒物（PM）对动物和人类都有潜在危害。由于传感器成本的原因，大多数农场都有监测系统来识别其他有害气体，而不是 PM。近几十年来，基于物联网（IoT）设备的环境监测系统的应用得到了广泛的提升，这些设备集成了低成本传感器。本研究开发了一种基于 Raspberry Pi 单板计算机和传感器阵列的低成本猪舍空气质量监测系统。该系统使用 11 种环境变量以及温度、湿度、CO、光照、压力和不同类型的气体（即 PM、PM 和 PM）收集数据。该系统设计有一个中央 Web 服务器，通过互联网提供实时数据可视化和数据可用性。它在实际的猪圈中进行了测试，以确保稳定性和功能性。此外，还进行了一次搭配测试，将系统放置在两个不同的猪圈中，以验证传感器数据。Wilcoxon 秩和检验表明，两个传感器数据集之间没有显著差异，因为所有变量的 p 值都大于 0.05。然而，除了一氧化碳（CO）之外，没有一个变量与 PM 浓度的相关性超过 0.5。总的来说，成功开发了一种可扩展、便携、不复杂、低成本的空气质量监测系统，成本为 94 美元。
