Greenhouse monitoring system integrating NB-IOT technology and a cloud service framework

Abstract

The strong support for the rural revitalization strategy has gradually made greenhouse monitoring systems an important component of modern agriculture and the planting industry in China. To efficiently and intelligently monitor and regulate the greenhouse environment, a greenhouse monitoring system based on narrowband Internet of Things and a cloud service framework was proposed. The experiment introduced particle swarm optimization and genetic algorithms to improve the parameter optimization of this system, ultimately achieving intelligent regulation of the greenhouse environment. When the system iterated to the 49th and 78th iterations on the training and testing sets, respectively, the constructed method had the optimal fitness value, with values as high as 97.58 and 96.27. Comparing the packet loss rates, the communication success rate of the monitoring system was over 99% when the constructed method was running. Upon comparing the relative errors, under the operation of the constructed method, the average relative measurement errors of particulate matter, hydrogen sulfide, and ammonia were ±2.58 μg/m3, ±0.216 × 10−6, and ±0.175 × 10−6, respectively, all within a reasonable range. In addition, the constructed method was closer to the actual control values for temperature, humidity, light, and carbon dioxide. In summary, the greenhouse monitoring system constructed by this method has lower energy consumption and can reduce manual intervention, providing new ideas for achieving precision agriculture and sustainable development.

Keywords

• nb-iot technology
• cloud services
• greenhouse monitoring
• genetic algorithm
• pid control
• intelligent agriculture