  Smart plant factories incorporate sensing technology, actuators and control
algorithms to automate processes, reducing the cost of production while
improving crop yield many times over that of traditional farms. This paper
investigates the growth of lettuce (Lactuca Sativa) in a smart farming setup
when exposed to red and blue light-emitting diode (LED) horticulture lighting.
An image segmentation method based on K-means clustering is used to identify
the size of the plant at each stage of growth, and the growth of the plant
modelled in a feed forward network. Finally, an optimization algorithm based on
the plant growth model is proposed to find the optimal lighting schedule for
growing lettuce with respect to dynamic electricity pricing. Genetic algorithm
was utilized to find solutions to the optimization problem. When compared to a
baseline in a simulation setting, the schedules proposed by the genetic
algorithm can achieved between 40-52% savings in energy costs, and up to a 6%
increase in leaf area.
