Abstract
This study is dedicated to the development of an Internet of Things (IoT)-based water-fertilizer coupling optimization model for landscape plant cultivation using big data analysis technology to solve the problems of resource wastage and unstable plant growth quality in traditional water-fertilizer management. Through real-time monitoring of soil, climate and plant physiological indicators, combined with autoregressive moving average model and other prediction means, to achieve accurate prediction of plant water and fertilizer demand and dynamic coupling management. The model is able to customize personalized water and fertilizer supply strategies according to plant species, growth stages and environmental conditions, thus enhancing the efficiency of water and fertilizer utilization, promoting healthy plant growth, and enhancing the effect of urban greening.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
