Research on ecosystem detection based on wireless communication network


  • Muzi Tang
  • Yitong Liu
  • Tingyu Shen



wireless communication network, ecological monitoring, smart city, data processing and acquisition, reliability of ecological monitoring system.


Ecosystem monitoring is of great significance in environmental protection and sustainable development. Wireless communication networks provide a broad application prospect for ecosystem monitoring, but there is a lack of further research on the strengths and weaknesses of the existing research results and specific application scenarios, as well as on the reliability of data processing. This paper aims to explore the theoretical basis of the reliability of wireless communication networks in ecosystem monitoring. Firstly, the current status, characteristics and challenges of wireless communication networks in ecosystem monitoring are reviewed, the key elements in ecosystem monitoring and the requirements for data integrity and accuracy are analyzed in detail, and the reliability problems of signal interference, node failure and data loss in data transmission are discussed. Secondly, methods and strategies to improve the reliability of ecosystem monitoring based on wireless communication networks are explored. By reviewing and analyzing the existing research results, the advantages and disadvantages of different methods as well as the applicable scenarios are elaborated. Finally, the paper proposes directions and challenges for future research. The exploration of emerging technologies is emphasized. At the same time, issues that need to be addressed, network security, energy efficiency and cost feasibility are pointed out. The significance of this paper in academic and industry practice can further deepen the exploration of the theoretical basis of reliability and combine it with practical application scenarios for verification and optimization.


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How to Cite

Tang, M., Liu, Y., & Shen, T. (2024). Research on ecosystem detection based on wireless communication network. Highlights in Science, Engineering and Technology, 82, 43-50.