Abstract
This project focuses on lighting control in greenhouse production to achieve optimal
plant growth. The concept can be applied to other environmental variables such as
temperature, humidity, and CO2. We propose a system comprised of an intelligent
sensor network, distributed control nodes, and LED grow lights with the following
characteristics:
1. To reduce the supplemental lighting energy consumption by optimizing
LED grow-light intensity through advanced controls
2. To improve crop productivity by using the spectrum modification capabilities of
LED technology to manipulate the light quality within a greenhouse environment.
.
Background
System Design
References
1. Massa GD, Kim HH, Wheeler RM & Mitchell CA. Plant productivity in response to LED lighting. HortScience.
2008;43:1951–1956.
2. Vänninen I, Pinto DM, Nissinen AI, Johansen NS & Shipp L. In the light of new greenhouse technologies: Plant-
mediates effects of artificial lighting on arthropods and tritrophic interactions. Ann Appl Biol. 2010;157:393–414.
3. Chen P. Chlorophyll and other photosentives. In: LED grow lights, absorption spectrum for plant photosensitive
pigments. http://www.ledgrowlightshq.co.uk/chlorophyll-plant-pigments/.Accessed 12 March 2014.
Acknowledgments
This research has been supported by the Pacific Institute
of Climate Solutions and the School of Mechatronic
Systems Engineering at Simon Fraser University
Intelligent Control Systems for Energy-efficient Lighting in Greenhouses
Alex Jun Jiang (PhD Student), Mehrdad Moallem (Professor)
School of Mechatronic Systems Engineering
Hardware Set Up Data Insights
Control Factors
1. Photoperiod Control
Control the flowering period
2. Photomorphogenesis Control
Control the seed germination, seedling development,
and the switch time from vegetative to the flowering stage
Affects disease resistance, taste, and nutritional levels
The above can be achieved by customizing red and
blue light ratio for making optimal light recipe for growing
various crops
3. Illuminance Control
Control supplemental light intensity in the presence of
natural light for photosynthesis during the winter season or
overcast days.
Light Duration
Energy
saving at
least
• 70%
Crop yield all year
around
•365
days
Increase the crop
quality control
precision
•40%
Reduce
cultivation time
•30%
Light quality
Light intensity
 Absorption spectrum in
photosynthesis process of
plant
 Mainly blue light and red light
Cloud Server
Light Fixtures
Gateway
Internet
Ethernet
Router
Wireless
Distributed lighting system with
multiple LED-luminaries where
each fixture is:
•Wireless enabled to exchange
information with other luminaries
and a local control unit
•Ambient light sensor to detect
light level
•Continuous dimming capability
Energy-efficient Lighting
- Power Drives for HB LED
 Small capacitors for increased
lifetime
- Low-cost Single Stage Power
Driver
- Distributed lighting control with
daylighting strategies
LED Grow Light
Control modules inside LED lights
TI MCU
User Interface
Sensors (Temp,
Humidity, CO2,
quantum

Alex_v6_CleanTech_Surrey_City_Hall_ORG

  • 1.
    Abstract This project focuseson lighting control in greenhouse production to achieve optimal plant growth. The concept can be applied to other environmental variables such as temperature, humidity, and CO2. We propose a system comprised of an intelligent sensor network, distributed control nodes, and LED grow lights with the following characteristics: 1. To reduce the supplemental lighting energy consumption by optimizing LED grow-light intensity through advanced controls 2. To improve crop productivity by using the spectrum modification capabilities of LED technology to manipulate the light quality within a greenhouse environment. . Background System Design References 1. Massa GD, Kim HH, Wheeler RM & Mitchell CA. Plant productivity in response to LED lighting. HortScience. 2008;43:1951–1956. 2. Vänninen I, Pinto DM, Nissinen AI, Johansen NS & Shipp L. In the light of new greenhouse technologies: Plant- mediates effects of artificial lighting on arthropods and tritrophic interactions. Ann Appl Biol. 2010;157:393–414. 3. Chen P. Chlorophyll and other photosentives. In: LED grow lights, absorption spectrum for plant photosensitive pigments. http://www.ledgrowlightshq.co.uk/chlorophyll-plant-pigments/.Accessed 12 March 2014. Acknowledgments This research has been supported by the Pacific Institute of Climate Solutions and the School of Mechatronic Systems Engineering at Simon Fraser University Intelligent Control Systems for Energy-efficient Lighting in Greenhouses Alex Jun Jiang (PhD Student), Mehrdad Moallem (Professor) School of Mechatronic Systems Engineering Hardware Set Up Data Insights Control Factors 1. Photoperiod Control Control the flowering period 2. Photomorphogenesis Control Control the seed germination, seedling development, and the switch time from vegetative to the flowering stage Affects disease resistance, taste, and nutritional levels The above can be achieved by customizing red and blue light ratio for making optimal light recipe for growing various crops 3. Illuminance Control Control supplemental light intensity in the presence of natural light for photosynthesis during the winter season or overcast days. Light Duration Energy saving at least • 70% Crop yield all year around •365 days Increase the crop quality control precision •40% Reduce cultivation time •30% Light quality Light intensity  Absorption spectrum in photosynthesis process of plant  Mainly blue light and red light Cloud Server Light Fixtures Gateway Internet Ethernet Router Wireless Distributed lighting system with multiple LED-luminaries where each fixture is: •Wireless enabled to exchange information with other luminaries and a local control unit •Ambient light sensor to detect light level •Continuous dimming capability Energy-efficient Lighting - Power Drives for HB LED  Small capacitors for increased lifetime - Low-cost Single Stage Power Driver - Distributed lighting control with daylighting strategies LED Grow Light Control modules inside LED lights TI MCU User Interface Sensors (Temp, Humidity, CO2, quantum