EconPapers    
Economics at your fingertips  
 

Model Predictive Control of Smart Greenhouses as the Path towards Near Zero Energy Consumption

Chiara Bersani, Ahmed Ouammi, Roberto Sacile and Enrico Zero
Additional contact information
Chiara Bersani: DIBRIS—Department on Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genova, Italy
Ahmed Ouammi: Centre for Sustainable Development, Qatar University, Doha 2713, Qatar
Roberto Sacile: DIBRIS—Department on Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genova, Italy
Enrico Zero: DIBRIS—Department on Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genova, Italy

Energies, 2020, vol. 13, issue 14, 1-17

Abstract: Modern agriculture represents an economic sector that can mainly benefit from technology innovation according to the principles suggested by Industry 4.0 for smart farming systems. Greenhouse industry is significantly becoming more and more technological and automatized to improve the quality and efficiency of crop production. Smart greenhouses are equipped with forefront IoT- and ICT-based monitoring and control systems. New remote sensors, devices, networking communication, and control strategies can make available real-time information about crop health, soil, temperature, humidity, and other indoor parameters. Energy efficiency plays a key role in this context, as a fundamental path towards sustainability of the production. This paper is a review of the precision and sustainable agriculture approaches focusing on the current advance technological solution to monitor, track, and control greenhouse systems to enhance production in a more sustainable way. Thus, we compared and analyzed traditional versus model predictive control methods with the aim to enhance indoor microclimate condition management under an energy-saving approach. We also reviewed applications of sustainable approaches to reach nearly zero energy consumption, while achieving nearly zero water and pesticide use.

Keywords: model predictive control; precision agriculture; greenhouse; control strategies; energy saving; sustainability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/14/3647/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/14/3647/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:14:p:3647-:d:384787

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3647-:d:384787