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Smart plant factories incorporate sensing technology, actuators and controlalgorithms to automate processes, reducing the cost of production whileimproving crop yield many times over that of traditional farms. This paperinvestigates the growth of lettuce (Lactuca Sativa) in a smart farming setupwhen exposed to red and blue light-emitting diode (LED) horticulture lighting.An image segmentation method based on K-means clustering is used to identifythe size of the plant at each stage of growth, and the growth of the plantmodelled in a feed forward network. Finally, an optimization algorithm based onthe plant growth model is proposed to find the optimal lighting schedule forgrowing lettuce with respect to dynamic electricity pricing. Genetic algorithmwas utilized to find solutions to the optimization problem. When compared to abaseline in a simulation setting, the schedules proposed by the geneticalgorithm can achieved between 40-52% savings in energy costs, and up to a 6%increase in leaf area.

Minimizing Electricity Cost through Smart Lighting Control for Indoor Plant Factories