A System for Vertical Farming Data Collection and Analysis

Abstract

Presently, agriculture is one of humanity’s most deleterious activities as it results in harmful environmental effects. As technologies in robotics and machine learning advance, people are developing new agricultural methods to help assuage the ecological risks associated with conventional growing methods. Whether these methods are sustainable and efficient are an important questions in light of possible climate, population, and food crises projections. This thesis project consists of the design and partial implementation of a hardware-software system that can be used to automate data collection and model training in order optimize yield as well as to determine the feasibility of vertical farming as a sustainable solution.