IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i12p3427-d188601.html
   My bibliography  Save this article

Design and Implementation of an IoT System for Smart Energy Consumption and Smart Irrigation in Tunnel Farming

Author

Listed:
  • M. Safdar Munir

    (Department of Computer Science & IT, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan)

  • Imran Sarwar Bajwa

    (Department of Computer Science & IT, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan)

  • M. Asif Naeem

    (School of Computer and Mathematical Sciences, Auckland University of Technology, Auckland 92006, New Zealand)

  • Bushra Ramzan

    (Department of Computer Science & IT, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan)

Abstract

Efficient and cost effective ways of irrigation have emerged as the need of the hour due to limited sweet water resources, especially the countries that are seriously hit by a lack of sweet water reservoirs. The majority of the water is wasted due to inefficient ways of watering plants. In this paper, we propose an intelligent approach for efficient plant irrigation that has a database of daily water needs of a type of plant and decides the amount of water for a plant type on the basis of the current moisture in soil, humidity, and time of the day. This approach not only saves sweet water by efficient utilization, but also supports smart consumption of energy. Our approach employs IoT and a set of sensors to efficiently record plant data and their watering needs and the approach is implemented with a mobile phone application interface that is used to continuously monitor and control the efficient watering system. The results of this study are easy to reproduce as the sensors used are cheap and easy to access. The study discusses in this paper is experimented on small area (such as tunnel farm) but the results of the experiments show that the used approach can be generalized and can be used for large size fields for efficient irrigation. The results of the experiments also outperform the manual approach and the similar approaches for sensor based irrigation systems.

Suggested Citation

  • M. Safdar Munir & Imran Sarwar Bajwa & M. Asif Naeem & Bushra Ramzan, 2018. "Design and Implementation of an IoT System for Smart Energy Consumption and Smart Irrigation in Tunnel Farming," Energies, MDPI, vol. 11(12), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3427-:d:188601
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/12/3427/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/12/3427/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Navarro-Hellín, H. & Torres-Sánchez, R. & Soto-Valles, F. & Albaladejo-Pérez, C. & López-Riquelme, J.A. & Domingo-Miguel, R., 2015. "A wireless sensors architecture for efficient irrigation water management," Agricultural Water Management, Elsevier, vol. 151(C), pages 64-74.
    2. Soulis, Konstantinos X. & Elmaloglou, Stamatios & Dercas, Nicholas, 2015. "Investigating the effects of soil moisture sensors positioning and accuracy on soil moisture based drip irrigation scheduling systems," Agricultural Water Management, Elsevier, vol. 148(C), pages 258-268.
    3. Cancela, J.J. & Fandiño, M. & Rey, B.J. & Martínez, E.M., 2015. "Automatic irrigation system based on dual crop coefficient, soil and plant water status for Vitis vinifera (cv Godello and cv Mencía)," Agricultural Water Management, Elsevier, vol. 151(C), pages 52-63.
    4. Blonquist, J.M. Jr. & Jones, S.B. & Robinson, D.A., 2006. "Precise irrigation scheduling for turfgrass using a subsurface electromagnetic soil moisture sensor," Agricultural Water Management, Elsevier, vol. 84(1-2), pages 153-165, July.
    5. McCready, M.S. & Dukes, M.D. & Miller, G.L., 2009. "Water conservation potential of smart irrigation controllers on St. Augustinegrass," Agricultural Water Management, Elsevier, vol. 96(11), pages 1623-1632, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fernanda Moura Quintão Silva & Menaouar Berrehil El Kattel & Igor Amariz Pires & Thales Alexandre Carvalho Maia, 2022. "Development of a Supervisory System Using Open-Source for a Power Micro-Grid Composed of a Photovoltaic (PV) Plant Connected to a Battery Energy Storage System and Loads," Energies, MDPI, vol. 15(22), pages 1-22, November.
    2. Aditya Dinesh Gupta & Prerna Pandey & Andrés Feijóo & Zaher Mundher Yaseen & Neeraj Dhanraj Bokde, 2020. "Smart Water Technology for Efficient Water Resource Management: A Review," Energies, MDPI, vol. 13(23), pages 1-23, November.
    3. Leonardo D. Garcia & Camilo Lozoya & Antonio Favela-Contreras & Emanuele Giorgi, 2023. "A Comparative Analysis between Heuristic and Data-Driven Water Management Control for Precision Agriculture Irrigation," Sustainability, MDPI, vol. 15(14), pages 1-14, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Snyder, R.L. & Pedras, C. & Montazar, A. & Henry, J.M. & Ackley, D., 2015. "Advances in ET-based landscape irrigation management," Agricultural Water Management, Elsevier, vol. 147(C), pages 187-197.
    2. Singh, Amninder & Verdi, Amir & Haver, Darren & Sapkota, Anish & Iradukunda, Jean Claude, 2024. "Using a soil moisture sensor-based smart controller for autonomous irrigation management of hybrid bermudagrass with recycled water in coastal Southern California," Agricultural Water Management, Elsevier, vol. 299(C).
    3. Chen, Xiaoping & Qi, Zhiming & Gui, Dongwei & Sima, Matthew W. & Zeng, Fanjiang & Li, Lanhai & Li, Xiangyi & Gu, Zhe, 2020. "Evaluation of a new irrigation decision support system in improving cotton yield and water productivity in an arid climate," Agricultural Water Management, Elsevier, vol. 234(C).
    4. Bonfante, A. & Monaco, E. & Manna, P. & De Mascellis, R. & Basile, A. & Buonanno, M. & Cantilena, G. & Esposito, A. & Tedeschi, A. & De Michele, C. & Belfiore, O. & Catapano, I. & Ludeno, G. & Salinas, 2019. "LCIS DSS—An irrigation supporting system for water use efficiency improvement in precision agriculture: A maize case study," Agricultural Systems, Elsevier, vol. 176(C).
    5. Phogat, V. & Skewes, M.A. & McCarthy, M.G. & Cox, J.W. & Šimůnek, J. & Petrie, P.R., 2017. "Evaluation of crop coefficients, water productivity, and water balance components for wine grapes irrigated at different deficit levels by a sub-surface drip," Agricultural Water Management, Elsevier, vol. 180(PA), pages 22-34.
    6. Giulio Sperandio & Mauro Pagano & Andrea Acampora & Vincenzo Civitarese & Carla Cedrola & Paolo Mattei & Roberto Tomasone, 2022. "Deficit Irrigation for Efficiency and Water Saving in Poplar Plantations," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
    7. Marjan Aziz & Madeeha Khan & Naveeda Anjum & Muhammad Sultan & Redmond R. Shamshiri & Sobhy M. Ibrahim & Siva K. Balasundram & Muhammad Aleem, 2022. "Scientific Irrigation Scheduling for Sustainable Production in Olive Groves," Agriculture, MDPI, vol. 12(4), pages 1-14, April.
    8. Rosa, R.D. & Ramos, T.B. & Pereira, L.S., 2016. "The dual Kc approach to assess maize and sweet sorghum transpiration and soil evaporation under saline conditions: Application of the SIMDualKc model," Agricultural Water Management, Elsevier, vol. 177(C), pages 77-94.
    9. Williams, Larry E. & Levin, Alexander D. & Fidelibus, Matthew W., 2022. "Crop coefficients (Kc) developed from canopy shaded area in California vineyards," Agricultural Water Management, Elsevier, vol. 271(C).
    10. Trigo-Córdoba, Emiliano & Bouzas-Cid, Yolanda & Orriols-Fernández, Ignacio & Mirás-Avalos, José Manuel, 2015. "Effects of deficit irrigation on the performance of grapevine (Vitis vinifera L.) cv. ‘Godello’ and ‘Treixadura’ in Ribeiro, NW Spain," Agricultural Water Management, Elsevier, vol. 161(C), pages 20-30.
    11. Silva, Marcos Dornelas Freitas Machado e & Calijuri, Maria Lúcia & Sales, Francisco José Ferreira de & Souza, Mauro Henrique Batalha de & Lopes, Lucas Sampaio, 2014. "Integration of technologies and alternative sources of water and energy to promote the sustainability of urban landscapes," Resources, Conservation & Recycling, Elsevier, vol. 91(C), pages 71-81.
    12. Nolz, R. & Cepuder, P. & Balas, J. & Loiskandl, W., 2016. "Soil water monitoring in a vineyard and assessment of unsaturated hydraulic parameters as thresholds for irrigation management," Agricultural Water Management, Elsevier, vol. 164(P2), pages 235-242.
    13. França, Ana Carolina Ferreira & Coelho, Rubens Duarte & da Silva Gundim, Alice & de Oliveira Costa, Jéfferson & Quiloango-Chimarro, Carlos Alberto, 2024. "Effects of different irrigation scheduling methods on physiology, yield, and irrigation water productivity of soybean varieties," Agricultural Water Management, Elsevier, vol. 293(C).
    14. Cáceres, Rafaela & Pol, Enric & Narváez, Lola & Puerta, Anna & Marfà, Oriol, 2017. "Web app for real-time monitoring of the performance of constructed wetlands treating horticultural leachates," Agricultural Water Management, Elsevier, vol. 183(C), pages 177-185.
    15. Pereira, L.S. & Paredes, P. & Melton, F. & Johnson, L. & Mota, M. & Wang, T., 2021. "Prediction of crop coefficients from fraction of ground cover and height: Practical application to vegetable, field and fruit crops with focus on parameterization," Agricultural Water Management, Elsevier, vol. 252(C).
    16. Migliaccio, Kati W. & Schaffer, Bruce & Crane, Jonathan H. & Davies, Frederick S., 2010. "Plant response to evapotranspiration and soil water sensor irrigation scheduling methods for papaya production in south Florida," Agricultural Water Management, Elsevier, vol. 97(10), pages 1452-1460, October.
    17. Yang, Meijian & Wang, Guiling & Lazin, Rehenuma & Shen, Xinyi & Anagnostou, Emmanouil, 2021. "Impact of planting time soil moisture on cereal crop yield in the Upper Blue Nile Basin: A novel insight towards agricultural water management," Agricultural Water Management, Elsevier, vol. 243(C).
    18. Achour, Yasmine & Ouammi, Ahmed & Zejli, Driss, 2021. "Technological progresses in modern sustainable greenhouses cultivation as the path towards precision agriculture," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    19. Pisciotta, Antonino & Di Lorenzo, Rosario & Santalucia, Gioacchino & Barbagallo, Maria Gabriella, 2018. "Response of grapevine (Cabernet Sauvignon cv) to above ground and subsurface drip irrigation under arid conditions," Agricultural Water Management, Elsevier, vol. 197(C), pages 122-131.
    20. López-Riquelme, J.A. & Pavón-Pulido, N. & Navarro-Hellín, H. & Soto-Valles, F. & Torres-Sánchez, R., 2017. "A software architecture based on FIWARE cloud for Precision Agriculture," Agricultural Water Management, Elsevier, vol. 183(C), pages 123-135.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3427-:d:188601. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.