Earth Science Frontiers ›› 2024, Vol. 31 ›› Issue (4): 165-182.DOI: 10.13745/j.esf.sf.2024.5.12

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IoT monitoring and visualization of urban soil pollution based on microservice architecture

WANG Hanyu1,2,3(), ZHOU Yongzhang1,2,3,*(), XU Yating1,2,3, WANG Weixi1,2,3, CAO Wei1,2,3,*(), LIU Yongqiang1,2,3, HE Juxiang1,2,3, LU Kefei2   

  1. 1. School of Earth Sciences & Engineering, Sun Yat-sen University, Zhuhai 519000, China
    2. Center of Earth Environment & Resources, Sun Yat-sen University, Zhuhai 519000, China
    3. Guangdong Provincial Key Lab of Geological Process and Mineral Resource Survey, Zhuhai 519000, China
  • Received:2023-09-03 Revised:2024-03-14 Online:2024-07-25 Published:2024-07-10

Abstract:

The nature of soil pollution—cumulative, hidden, latent, irreversible—makes it essential that urban soil pollution should be closely monitored and prevented. However, traditional monitoring methods cannot perform real-time pollution monitoring and have limited data processing capabilities. To address this issue, we aim to develop a pollution prediction and early warning system capable of real-time online monitoring, processing, and analyzing urban soil pollution data. In this paper we report the development of a monitoring and data visualization system based on microservice framework Spring Cloud Alibaba, whereby integrating the EMQX platform soil data are successfully collected and stored. Additionally, we develop a WebGIS module that interfaces with Geoserver—this module utilizes OpenLayers to render maps and soil element concentration charts, enabling the monitoring and visual analysis of soil conditions. We believe with breakthroughs in sensor technologies relating to chemical monitoring, real-time online monitoring, processing, and analysis of soil pollution data through Internet of Things (IoT) can be achieved. The IoT monitoring and visualization system has been tested and its effectiveness in identifying pollution changes, predicting trends, and devising effective prevention and control measures are demonstrated. Most importantly, practical applications confirm the system's notable advantages in enhancing the timeliness of soil pollution prediction and early warning.

Key words: urban soil pollution, Internet of Things, microservice architecture, Spring Cloud Alibaba, Docker, visualization system, big data

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