Circadian Lighting Control for Indoor Plant Yield
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Solution Overview
Problem
Indoor plant growing environments face high costs due to lighting and energy expenses, with existing systems lacking efficiency in mimicking natural circadian rhythms and adapting to specific plant needs.
Innovation Solution
An advanced plant production system that includes a lighting system with controllable output intensity, a driver to mimic and modify circadian rhythms based on prior harvest results, and a sensor hub for monitoring environmental factors, along with methods for optimizing light fixture placement and verification, to enhance plant growth efficiency and yield.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If lighting systems operate continuously at high intensity to maximize plant growth, then plant yield improves, but energy costs increase significantly
Solution Approach 1:
The lighting system implements circadian rhythm cycles with periodic variations in intensity and spectrum, switching between different lighting phases (daylight simulation, dusk, night, dawn) to provide optimal light only when biologically necessary for plant growth, reducing overall energy consumption while maintaining productivity
Solution Approach 2:
The system dynamically adjusts lighting intensity and spectral composition based on the circadian phase and plant response feedback, transitioning from static high-intensity lighting to adaptive variable lighting that optimizes energy use at different growth stages
2Adaptability or versatility
If lighting controls are manually adjusted to emulate daylight cycles, then circadian rhythm simulation improves, but operational complexity increases
Solution Approach 1:
The system automatically adjusts lighting parameters based on pre-programmed circadian rhythms and real-time plant response data without requiring manual intervention, with the controller autonomously managing intensity, spectrum, and timing adjustments
Solution Approach 2:
The system incorporates feedback mechanisms that monitor plant responses to lighting and automatically adjust subsequent lighting cycles, creating a closed-loop control system that refines circadian rhythm simulation based on actual plant performance
3Productivity
If harvest results are used to modify subsequent lighting schedules, then plant growth efficiency improves, but system adaptability requirements increase
Solution Approach 1:
The system uses harvest results as feedback to automatically modify subsequent lighting schedules, creating a learning system that adapts lighting parameters based on historical performance data to optimize future growth efficiency
Solution Approach 2:
The system pre-adjusts lighting schedules based on anticipated plant needs derived from harvest patterns, proactively optimizing conditions before new growth cycles begin rather than reacting after problems occur
Data Source
AI summary
An advanced plant production system comprises a robust and efficient network of lighting, instrumentation and control and data acquisition systems, which are integrated together to maximize plant health, crop production, while conserving resources. The system provides an advanced user interface that can be accessed both locally and remotely. In some embodiments, the lighting can be controlled to mimic the circadian rhythm of the crops or the Sun, and can be matched to a particular type and/or maturity of plant. A sensor node which can be used in the plant production system comprises internal sensors, and can also be connected to other external sensors, to provide detailed environmental information. Several methods are described that can optimize the efficiency of the system, and can be used to improve the yield, value, and/or quality of crops.