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Green, T.R., Salas, J.D., Martinez, A. and Erskine, R.H. (2007) Relating Crop Yield to Topographic Attributes Using Spatial Analysis Neural Networks and Regression. Geoderma, 139, 23-37.
https://doi.org/10.1016/j.geoderma.2006.12.004

has been cited by the following article:

• TITLE: Smart Agriculture with an Automated IoT-Based Greenhouse System for Local Communities

  AUTHORS: Nianpu Li, Yimeng Xiao, Lei Shen, Zhuoyue Xu, Botao Li, Chongxuan Yin

  KEYWORDS: Internet of Things, Hydroponics, ZigBee, Sensor Network, Automated Agriculture, Cloud

  JOURNAL NAME: Advances in Internet of Things, Vol.9 No.2, April 29, 2019

  ABSTRACT: Nowadays, smart agriculture using wireless communication is replacing the wired system which was difficult to install and manage. Then, this paper introduces a new design for IoT application on the greenhouse, which utilizes different technologies to present a new model for practical implementation in the IoT concept. This design can settle a new method to solve problems in Market Demand, Precision in Operation and supervision. Furthermore, this design can be used in many cases and assist farmers, cropper and planted people to develop their business.