Research on Green City Environmental Monitoring and Landscape Design Based on Communication Technology and Internet of Things Sensing Technology
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Abstract
Rapid urbanization has created a dual challenge for green city development: environmental monitoring efficiency often lags behind ecological demand, while landscape design still relies heavily on static surveys and designer experience. Integrating communication technology with IoT sensing can address these issues by enabling continuous environmental perception and data-driven landscape optimization. This study constructs a real-time urban environmental monitoring system comprising 120 composite sensor nodes deployed across four functional zones: commercial districts, residential areas, industrial buffer zones, and urban green spaces. A dual-channel communication architecture combining NB-IoT and LoRaWAN, supported by an edge-cloud collaborative computing framework, is used to monitor atmospheric quality, thermal environment, acoustic conditions, and light environment. The wireless communication design also provides a practical reference for low-power sensor networking and propagation-aware deployment in dense urban environments. Results show that overall data integrity reached 99.1%, and edge computing reduced end-to-end response latency by 73.6%. Using multidimensional monitoring datasets as a decision basis, landscape spatial layout optimization reduced annual mean PM2.5 concentrations by 26.3% in targeted zones and lowered local urban heat island intensity by 41.7% relative to control areas. Resident satisfaction increased by 19.4 points, and AHP evaluation scores increased by 39.5%, validating a closed-loop perception-transmission-analysis-design paradigm for green urban landscape optimization.
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