Trees play essential roles in environmental protection, soil erosion prevention, air purification, urban aesthetics, etc. The hazards of no trees, such as soil erosion and climate warming, bring huge damage to human lives. Thus, to implement effective tree healthcare is vital. In previous works, we have proposed Internet of Things (IoT) based tree healthcare monitoring methods. In this article, we further study this topic on data collection and data analysis methods. We study the influence of various sensor deployment schemes. Besides, we adopted a new loT network, LoRaWAN, in this work. Comparing to other loT networks, LoRaWAN owns advantages on large coverage, low power consumption. Besides, it is more convenient to implement the LoRaWAN network since it uses capable gateways. Furthermore, we apply a new artificial intelligence method, gate recurrent unit (GRU). It is a category of Recurrent Neural Network, which focuses on the contribution of data within a period. A tree health monitoring system is established and the accuracy of this system could achieve 90.6%.