Plant Growth Prediction through Intelligent Embedded Sensing

摘要: Precision agriculture is a research domain aimed at securing the food production for growing Earth population and urbanization. In this paper, we report on monitoring system that provides robust prediction of plant growth dynamics. Based knowledge about plants growth, propose solution consists two data analysis stages. The first image preprocessing using filters time series pruning applying statistical methods. On second stage make predictions with superficial machine learning algorithms. proposed can run embedded devices locally. computation low-power allows us to reduce transmission ensure ‘distributed intelligence’. As dataset, collected top-down view sequences images. We achieved 5% relative error four days predictions. experimental results modelling demonstrate high potential precision industry, being crucial part development control system.