Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Input-State-Output Representations of Concatenated 2D Convolutional Codes Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Automation and Control in Greenhouses: State-of-the-Art and Future Trends

Authors : Josenalde Oliveira, José Boaventura-Cunha, Paulo Moura Oliveira

Published in: CONTROLO 2016

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This paper presents the state-of-the-art in terms of automation and control for protected cultivation in greenhouses. Aspects such as modeling, instrumentation, energy optimization and applied robotics are considered, aiming at not only to identify latest research topics, but also to foster continuous improvement in key cutting-edge problems.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
previous chapter Milling Parameters Optimization for Surface Quality
next chapter A New Plant Growth System Rig Based on Thermodynamic Solar Energy: A Study for Energy Efficiency Assessment
Footnotes
1
for example, IFAC Agricontrol, EFITA WCCA-CIGR.
 
8
Last report on horticulture, flowers and other crops date from 2007: http://​www.​gpp.​pt/​pbl/​diagnosticos/​SubFileiras/​Horticultura.​pdf.
 
Literature
1.
2.
Bozchalui, M.C., Cañizares, C.A., Battacharya, K.: Optimal energy management of greenhouses in smart grids. IEEE Trans. Smart Grid 6(2), 827–835 (2015)CrossRef
3.
Hashimoto, Y. (ed.): The Computerized Greenhouse: Automatic Control Application in Plant Production. Academic Press (1993)
4.
Hemming, S.: Innovations in greenhouse systems—energy conservation by system design, sensors and decision support systems (invited speaker). In: Greensys 2015: International Symposium on New Technologies and Management for Greenhouses, Évora, Portugal. http://​www.​greensys2015.​uevora.​pt/​ (2015)
5.
Gat, G., Gan-Mor, S., Degani, A.: Stable and robust vehicle steering control using an overhead guide in greenhouse tasks. Comput. Electron. Agric. 121, 234–244 (2016)CrossRef
6.
7.
van Straten, G., van Willigenburg, G., van Henten, E., van Ooteghem, R.: Optimal Control of Greenhouse Cultivation. CRC Press (2010)
8.
Castilla, N.: Greenhouse Technology and Management, 2nd edn. Cabi (2012)
9.
10.
Mhenni, Z., Abbes, M., Mami, A.: Fractional order model of a greenhouse. In: 6th International Renewable Energy Congress, pp. 1–5 (2015)
11.
Xiu-hua, W., Lei, Z.: Simulation on temperature and humidity nonlinear controller for greenhouses. In: 4th International Conference on Intelligent Computation Technology and Automation, pp. 500–503 (2011)
12.
Gao, Y., Song, X., Liu, C., He, S.: Feedback feed-forward linearization and decoupling for greenhouse environment control. In: International Conference on Mechatronics and Control, pp. 179–183 (2014)
13.
Pérez-González, A., Begovich, O., Ruiz-Léon, J.: Modeling of a greenhouse prototype using PSO algorithm based on a LabView\(^{TM}\) application. In: 11th International Conference on Electrical Engineering, Computing Science and Automatic Control, pp. 1–6 (2014)
14.
Rashedi, E., Nezamadi-Pour, H., Saryazdi, S.: GSA: a gravitational search algorithm. Inf. Sci. 179, 2232–2248 (2009)CrossRefMATH
15.
Mirjalili, S., Mirjalili, S.M., Lewis, A.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46–61 (2014)CrossRef
16.
17.
Guoqi, M., Linlin, Q., Xinghua, L., Gang, W.: Modeling and predictive control of greenhouse temperature-humidity system based on MLD and time-series. In: 34th Chinese Control Conference, pp. 2234–2239 (2015)
18.
19.
Márquez-Vera, M.A., Ramos-Fernández, J.C., Cerecero-Natale, L.F., Lafont, F., Balmat, J.-F., Esparza-Villanueva, J.I.: Temperature control in a MISO greenhouse by inverting its fuzzy model. Comput. Electron. Agric. 124, 168–174 (2016)
20.
Qhan, V.M., Gupta, G.S., Mukhopadhyay, S.: Review of sensors for greenhouse climate monitoring. In: 2011 IEEE Sensors Applications Symposium, pp. 112–118 (2011)
21.
Al-aubidy, K.M., Ali, M.M., Derbas, A.M., Al-mutairi, A.W.: Real-time monitoring and intelligent control for greenhouses based on wireless sensor network. In: 11th Multi-conference on Systems, Signals and Devices, pp. 1–7 (2014)
22.
Kuroda, M., Ibayashi, H., Mineno, H.: Affordable 400 MHz Long-haul sensor network for greenhouse horticulture. In: IEEE International Conference on Information Networking, pp. 19–24 (2015)
23.
Gomes, T., Brito, J., Abreu, H., Gomes, H., Cabral, J.: GreenMon: an efficient wireless sensor network monitoring solution for greenhouses. In: IEEE International Conference on Industrial Technology, pp. 2192–2197 (2015)
24.
Chen, J., Yang, J., Zhao, J., Xu, F., Shen, Z., Zhang, L.: Energy demand forecasting of the greenhouses using nonlinear models based on model optimized prediction method. Neurocomputing 174, 1087–1100 (2016)CrossRef
25.
Mahdavian, M., Wattanapongsakorn, N.: Optimizing PID controller tuning for greenhouse lighting control system by varying number of objectives. In: 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, pp. 1–6 (2014)
26.
Zou, Q., Ji, J., Zhang, S., Shi, M., Luo, Y.: Model predictive control based on particle swarm optimization of greenhouse climate for saving energy consumption. In: World Automation Congress, pp. 123–128 (2010)
27.
Oliveira, J.B., Boaventura-Cunha, J., Oliveira, P.B.M.: A feasibility study of sliding mode predictive control for greenhouses. Optim. Control Appl. Methods (2015). doi:10.​1002/​oca.​2189
28.
Camacho, E.F., Gallego, A.J.: Model predictive control in solar trough plants: a review. IFAC-PapersOnline 48–23, 278–285 (2015)CrossRef
29.
Hassanien, R.H.E., Li, M., Lin, W.D.: Advanced applications of solar energy in agricultural greenhouses. Renew. Sustain. Energy Rev. 54, 989–1001 (2016)CrossRef
30.
Vadiee, A., Martin, V.: Energy management in horticultural applications through closed greenhouse concept, state of the art. Renew. Sustain. Energy Rev. 16, 5087–5100 (2012)CrossRef
31.
Komasilovs, V., Stalidzans, E., Osadcuks, V., Mednis, M.: Specification development of robotic system for pesticide spraying in greenhouse. In: 14th IEEE International Symposium on Computational Intelligence and Informatics, pp. 453–457 (2013)
32.
Bac, C.W., van Henten, E.J., Hemming, J., Edan, Y.: Harvesting robots for high-value crops: state-of-the-art review and challenges ahead. J. Field Robot. 31(6), 888–911 (2014)CrossRef
33.
Shor, N., Bechar, A., Ignat, T., Dombrovsky, A., Elad, Y., Berman, S.: Robotic disease detection in greenhouses: combined detection of powdery mildew and tomato spotted wilt virus. IEEE Robot. Autom. Lett. 1(1), 354–360 (2016)CrossRef
34.
Gao, G., Li, M.: Study on navigating path recognition for the greenhouse mobile robot based on K-means algorithm. In: IEEE 11th International Conference on Networking, Sensing and Control, pp. 451–456 (2014)
35.
Kapach, K., Barnea, E., Mairon, R., Edan, Y., Ben-Shahar, O.: Computer vision for fruit harvesting robots: state of the art and challenges ahead. Int. J. Comput. Vis. Robot. 3(1, 2), 4–34 (2012)
36.
Tarry, C., Wspanialy, P., Veres, M., Moussa, M.: An integrated bud detection and localization system for application in greenhouse automation. In: 2014 Canadian Conference on Computer and Robot Vision, pp. 344–348 (2014)
37.
38.
39.
40.
Gieling, T.H., van Straten, G., Janssen, H.J.J., Wouters, H.: ISE and Chemfet sensors in greenhouse cultivation. Sensors Actuators B 105, 74–80 (2005)CrossRef
41.
Gieling, T.H., Corver, F.J.M., Janssen, H.J.J.: Hydrion-line, towards a closed system for water and nutrients: feedback control of water and nutrients in the drain. Acta Horticulture 691, 259–266 (2005)CrossRef
42.
Manqueros-Aviles, V.E.: Mediciones Nutritivas En Un Sistema Hidropnico NFT Mediante El Uso De Sensores De Iones Selectivos Y LabVIEW. In: 1er Congreso Internacional de Ciencias de la Ingeniera, pp. 1–8 (2015)
43.
Neto, A.J.S., Zolnier, S., Lopes, D.S.: Development and evaluation of an automated system for fertigation control in soilless tomato production. Comput. Electron. Agric. 103, 17–25 (2014)CrossRef
44.
He, D., Du, W., Hu, J.: Water quality dynamics monitoring technology and application based on ion selective electrodes. In: Macas, J.P. (ed.) Recent Developments in Mobile Communications: A Multidisciplinary Approach. InTech (2011)
Metadata
Title
Automation and Control in Greenhouses: State-of-the-Art and Future Trends
Authors
Josenalde Oliveira
José Boaventura-Cunha
Paulo Moura Oliveira
Copyright Year
2017
Book
CONTROLO 2016

Print ISBN: 978-3-319-43670-8

Electronic ISBN: 978-3-319-43671-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-43671-5_50