Annual energy consumption and carbon footprints are compared in simulation for two controlled environments: plant factory and traditional greenhouse. Energy consumed for heating, ventilating, and air conditioning (HVAC) as well as supplemental lighting are included in the models. In the greenhouse case, supplemental lighting is controlled to a consistent daily light integral (DLI) of Photosynthetically Active Radiation (PAR) using Light and Shade System Implementation (LASSI). In the plant factory model, lighting power is sized according to photoperiod and DLI requirements. Building HVAC loads and system responses are computed using the ASHRAE heat balance method with a one hour time-step. Both environments are simulated in four different climates using Typical Meteorological Year (TMY) data sets. In each simulation, energy consumption and carbon footprints are shown to be significantly higher in the plant factory environment compared to the greenhouse.

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This paper proposes a technique for planar trajectory following for an autonomous aerial robot. A trajectory is modeled as a planar spline. A behavior-based control system which stabilizes the robot and enforces trajectory following, has been implemented and tested on an autonomous helicopter. Results from two flight experiments are presented. The trajectory tracking error is on the order of the size of the robot (1.8m). Given the inherent error in GPS positioning, and environmental disturbances (wind), this is quite reasonable.

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Lighting is a major component of energy consumption in controlled environment agriculture (CEA) operations. Skyscraper farms (multilevel production in buildings with transparent glazing) have been proposed as alternatives to greenhouse or plant factories (opaque warehouses) to increase space-use efficiency while accessing some natural light. However, there are no previous models on natural light availability and distribution in skyscraper farms. This study employed climate-based daylight modeling software and the Typical Meteorological Year (TMY) dataset to investigate the effects of building geometry and context shading on the availability and spatial distribution of natural light in skyscraper farms in Los Angeles (LA) and New York City (NYC). Electric energy consumption for supplemental lighting in 20-storey skyscraper farms to reach a daily light integral target was calculated using simulation results. Natural lighting in our baseline skyscraper farms without surrounding buildings provides 13% and 15% of the light required to meet a target of 17 mol·m−2·day−1. More elongated buildings may meet up to 27% of the lighting requirements with natural light. However, shading from surrounding buildings can reduce available natural light considerably; in the worst case, natural light only supplies 5% of the lighting requirements. Overall, skyscraper farms require between 4 to 11 times more input for lighting than greenhouses per crop canopy area in the same location. We conclude that the accessibility of natural light in skyscraper farms in dense urban settings provides little advantage over plant factories.