Use of Machine Vision and Intelligent Data Processing Algorithms to Monitor and Predict Crop Growth in Vertical Farms

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Recommended citation: Bewley, Tom. "Use of Machine Vision and Intelligent Data Processing Algorithms to Monitor and Predict Crop Growth in Vertical Farms." BEng Thesis, University of Bristol, 2018. [PDF]

An individual research and design project, culminating in the development of a Python-based computer vision and machine learning system, capable of quantifying and predicting growth progression for microgreens in a vertical farm. I employ techniques including edge detection and colour analysis for low-level image processing, a Gaussian process for time series regression, and a Kalman filter for aggregation of noisy predictions over time.