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Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama ve Gübreleme Sistemi

Year 2022, Volume: 15 Issue: 1, 14 - 23, 27.06.2022

Muhammed Akif Yenikaya Erdal Güvenoğlu Süleyman Kondakcı

https://doi.org/10.54525/tbbmd.1028785
Cited By: 1

Abstract

Bu çalışmada, tarımda kullanılan otomatik sulama ve gübreleme sistemlerinde verimliliğin artırılması için IoT tabanlı akıllı toprak bakım sisteminin geliştirilmesi ve uygulanması amaçlanmaktadır. Geliştirmeyi hedeflediğimiz sistem, sulama ve gübreleme işlemlerini otomatik olarak en düşük maliyetle gerçekleştirmektedir. Tarla ve seralarda toprak değerleri kontrol edilerek ve kontrol merkezi ile internet üzerinden haberleşerek gübreleme ve sulama yapılabilmektedir. Kontrol merkezi, sensörler ile toprak değerlerini sürekli gözlemleyerek ihtiyacı olan çalışma ile toprağı otomatik olarak optimum düzeyde beslemektedir. Bu amaçla kullanılan yazılım ve donanımları içeren bir sistem, internet üzerinden yönetilebilecek şekilde tasarlanmıştır.

Keywords

Nesnelerin İnterneti Akıllı Sulama Akıllı Gübreleme Arduino NodeMCU

References

  • Gubbi, J., Buyya R., Marusic, S., Palaniswami, M., Internet of Things (IoT): A vision, architectural elements, and future directions. Future generation computer systems, 29(7), 2013, 1645 1660.
  • Yenikaya, M. A., Internet-aided Smart Irrigation and Fertilization System. MSc Thesis, Izmir University of Economics, The Gradute School of Natural and Applied Sciences, İzmir, 2017.
  • Ciğer, M., Computer Controlled, Internet-Aided Greenhouse Automation. MSc Thesis, Çukurova University, The Gradute School of Natural and Applied Sciences, Adana, 2010.
  • Çoruh, B., A system calibrates to the parameters of pressure, temperature and humidity. MSc Thesis, Başkent University, The Gradute School of Natural and Applied Sciences, Ankara, 2008.
  • Dukes, D. M., Simonne, H. E., Davis, E.W., Studstill, W. R., Hochmuth, Effect of Sensor-Based High Frequency Irrigation on Bell Pepper Yield and Water Use. Proceedings 2nd International Conference on Irrigation and Drainage, Phoenix, AZ, May 12-15, 2003, 665-674.
  • Kırnak, H., Automatic Irrigation Based on Soil Moisture for Nursery Crops. GAP V. Engineering Congress, Harran University. Engineering Department, 26-28 April, Şanlurfa, 2006, 1540-1547.
  • Millaa, K., Kishb, S., A Low-cost Microprocessor and Infrared Sensor System for Automating Water In lnfiltration Measurements. Computers and Electronics in Agriculture, 53, 2006, 122-129.
  • Inan, S. A., Meyve Fidanı Çoğaltılmasında Kullanılan Köklendirme Seralarının Otomasyonu. MSc Thesis, SDU, The Gradute School of Natural and Applied Sciences, Isparta, 2002.
  • Shivaprasad, B., Ravishankara, M., Shoba, B. N., Design and Implementation of Seeding and Fertilizing Agriculture Robot. International Journal of Application or Innovation in Engineering and Management, Volume 3, Issue 6, 2014.
  • Taştan, M., Nesnelerin İnterneti Tabanlı Akıllı Sulama ve Uzaktan İzleme Sistemi. Avrupa Bilim ve Teknoloji Dergisi , (15), 2019, 229 236.
  • Xiao, K., Xiao, D., Luo, X., Smart water saving irrigation system in precision agriculture based on wireless sensor network. Transactions of the Chinese Society of Agricultural Engineering, 26(11), 2010, 170 175.
  • Majsztrik, J. C., Price, E. W., King, D. M., Environmental benefits of wireless sensor based irrigation networks: Case study projections and potential adoption rates. HortTechnology, 23(6), 2013, 783 793.
  • Parameswaran, G., Sivaprasath,K., Arduino Based Smart Drip Irrigation System Using Internet of Things. Int. J. Eng. Sci, 5518, 2016.
  • Ishak, A., Hajjaj, S., Gsangaya, K., Hameed Sultan, M. T., Mail, M., Lee, S. H., Autonomous fertilizer mixer through the Internet of Things (IoT). Materials Today: Proceedings. 10.1016/j.matpr.2021.03.194, 2021.
  • Adeloye, A. J., Rustum, R., & Kariyama, I. D. Neural computing modeling of the reference crop evapotranspiration. Environmental Modelling & Software, 29(1), 2012, 61-73.
  • Kamienski, C., Soininen, J. P., Taumberger, M., Dantas, R., Toscano, A., Salmon Cinotti, T., ... & Torre Neto, A. Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture. Sensors, 19(2), 2019, 276.
  • Lichtenberg, E., Majsztrik, J., & Saavoss, M. Profitability of sensor-based irrigation in greenhouse and nursery crops. HortTechnology, 23(6), 2013, 770-774.
  • Soulis, K. X., Elmaloglou, S., & Dercas, N. Investigating the effects of soil moisture sensors positioning and accuracy on soil moisture based drip irrigation scheduling systems. Agricultural Water Management, 148, 2015, 258-268.
  • Mesas-Carrascosa, F.,Verdu, D., Merono, J.,Sanchez de la Orden, M., A. 2015 Biosystems Engineering. http://www.sciencedirect.com/science/article/pii/S1537511015001208, Erişim tarihi: 12 Kasım 2021.
  • Arduino UNO R3 Datasheet. https://docs.arduino.cc/static/dd40bcbb5f5ac04b6315a92e4e45d0f0/A000066-datasheet.pdf, Erişim tarihi: 12 Kasım 2021.
  • Arduino WiFi Shield Datasheet. https://docs.arduino.cc/retired/shields/arduino-wifi-shield, Erişim tarihi: 12 Kasım 2021.
  • LM35 Sıcaklık sensörü, https://www.direnc.net/lm35dz-hassas-sicaklik-sensoru-entegresi-to-92, Son erişim tarihi: 12 Kasım 2021.
  • LM393 Yangın algılama kartı, https://www.sunrom.com/p/fire-flame-sensor-module, Erişim tarihi: 12 Kasım 2021.
  • Barman, G., Görme Engellilere Yardımcı Ultrasonik Cihaz. Karadeniz Teknik Üniversitesi Mühendislik Fakültesi Tasarım Projesi, 2014.
  • Çamoğlu, G., Kızıl, Ü., Demirel, K., Aksu, S., Nar, H. & Genç, L., Bazı Ekonomik Toprak Nem Sensörlerinin Hassasiyetlerinin Belirlenmesi. Uluslararası Tarım ve Yaban Hayatı Bilimleri Dergisi, 7 (2), 2021, 247-254. DOI: 10.24180/ijaws.846464
  • Heaney, M. B. "Electrical Conductivity and Resistivity." Electrical Measurement, Signal Processing, and Displays. Ed. John G. Webster. CRC Press, 2003. 7-1.
  • Atlas Scientific: Environmental Robotics. EZO-EC. Revised: 9/2020, https://atlas-scientific.com/files/EC_EZO_Datasheet.pdf Erişim tarihi: 12 Kasım 2021.
  • Londo, J., Kushla, D., Carter, C., Soil pH and Tree Species Suitability in the South Andrew, Jacksonville State University, 2010.
  • Atlas Scientific: Environmental Robotics. EZO-pH. Revised: 1/2021, https://www.atlas-scientific.com/files/pH_EZO_Datasheet.pdf Erişim tarihi: 12 Kasım 2021.
  • South Dakota Soil Health Coalition. Soil Electrical Conductivity. https://www.sdsoilhealthcoalition.org/technical-resources/chemical-properties/soil-electrical-conductivity, Erişim tarihi: 12 Kasım 2021.

Internet of Things (IoT) Based Smart Irrigation and Fertilization System

Year 2022, Volume: 15 Issue: 1, 14 - 23, 27.06.2022

Muhammed Akif Yenikaya Erdal Güvenoğlu Süleyman Kondakcı

https://doi.org/10.54525/tbbmd.1028785
Cited By: 1

Abstract

In this study, it has been aimed to develop and apply an IoT based smart soil maintenance system in order to increase productivity in automated irrigation and fertilization systems used in agriculture. The system we aim to develop performs irrigation and fertilization processes automatically with the lowest expenditure. Fertilization and irrigation can be done by controlling values of the soil in felds and greenhouses, and communicating with the control centre via the Internet. The control centre nourishes the soil automatically on an optimal level with the study it needs by observing the soil values constantly with sensors. A system containing software and hardware used for this purpose has been designed to be manageable via the internet.

Keywords

Internet of Things Smart Irrigation Smart Fertilization Arduino NodeMCU

References

  • Gubbi, J., Buyya R., Marusic, S., Palaniswami, M., Internet of Things (IoT): A vision, architectural elements, and future directions. Future generation computer systems, 29(7), 2013, 1645 1660.
  • Yenikaya, M. A., Internet-aided Smart Irrigation and Fertilization System. MSc Thesis, Izmir University of Economics, The Gradute School of Natural and Applied Sciences, İzmir, 2017.
  • Ciğer, M., Computer Controlled, Internet-Aided Greenhouse Automation. MSc Thesis, Çukurova University, The Gradute School of Natural and Applied Sciences, Adana, 2010.
  • Çoruh, B., A system calibrates to the parameters of pressure, temperature and humidity. MSc Thesis, Başkent University, The Gradute School of Natural and Applied Sciences, Ankara, 2008.
  • Dukes, D. M., Simonne, H. E., Davis, E.W., Studstill, W. R., Hochmuth, Effect of Sensor-Based High Frequency Irrigation on Bell Pepper Yield and Water Use. Proceedings 2nd International Conference on Irrigation and Drainage, Phoenix, AZ, May 12-15, 2003, 665-674.
  • Kırnak, H., Automatic Irrigation Based on Soil Moisture for Nursery Crops. GAP V. Engineering Congress, Harran University. Engineering Department, 26-28 April, Şanlurfa, 2006, 1540-1547.
  • Millaa, K., Kishb, S., A Low-cost Microprocessor and Infrared Sensor System for Automating Water In lnfiltration Measurements. Computers and Electronics in Agriculture, 53, 2006, 122-129.
  • Inan, S. A., Meyve Fidanı Çoğaltılmasında Kullanılan Köklendirme Seralarının Otomasyonu. MSc Thesis, SDU, The Gradute School of Natural and Applied Sciences, Isparta, 2002.
  • Shivaprasad, B., Ravishankara, M., Shoba, B. N., Design and Implementation of Seeding and Fertilizing Agriculture Robot. International Journal of Application or Innovation in Engineering and Management, Volume 3, Issue 6, 2014.
  • Taştan, M., Nesnelerin İnterneti Tabanlı Akıllı Sulama ve Uzaktan İzleme Sistemi. Avrupa Bilim ve Teknoloji Dergisi , (15), 2019, 229 236.
  • Xiao, K., Xiao, D., Luo, X., Smart water saving irrigation system in precision agriculture based on wireless sensor network. Transactions of the Chinese Society of Agricultural Engineering, 26(11), 2010, 170 175.
  • Majsztrik, J. C., Price, E. W., King, D. M., Environmental benefits of wireless sensor based irrigation networks: Case study projections and potential adoption rates. HortTechnology, 23(6), 2013, 783 793.
  • Parameswaran, G., Sivaprasath,K., Arduino Based Smart Drip Irrigation System Using Internet of Things. Int. J. Eng. Sci, 5518, 2016.
  • Ishak, A., Hajjaj, S., Gsangaya, K., Hameed Sultan, M. T., Mail, M., Lee, S. H., Autonomous fertilizer mixer through the Internet of Things (IoT). Materials Today: Proceedings. 10.1016/j.matpr.2021.03.194, 2021.
  • Adeloye, A. J., Rustum, R., & Kariyama, I. D. Neural computing modeling of the reference crop evapotranspiration. Environmental Modelling & Software, 29(1), 2012, 61-73.
  • Kamienski, C., Soininen, J. P., Taumberger, M., Dantas, R., Toscano, A., Salmon Cinotti, T., ... & Torre Neto, A. Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture. Sensors, 19(2), 2019, 276.
  • Lichtenberg, E., Majsztrik, J., & Saavoss, M. Profitability of sensor-based irrigation in greenhouse and nursery crops. HortTechnology, 23(6), 2013, 770-774.
  • Soulis, K. X., Elmaloglou, S., & Dercas, N. Investigating the effects of soil moisture sensors positioning and accuracy on soil moisture based drip irrigation scheduling systems. Agricultural Water Management, 148, 2015, 258-268.
  • Mesas-Carrascosa, F.,Verdu, D., Merono, J.,Sanchez de la Orden, M., A. 2015 Biosystems Engineering. http://www.sciencedirect.com/science/article/pii/S1537511015001208, Erişim tarihi: 12 Kasım 2021.
  • Arduino UNO R3 Datasheet. https://docs.arduino.cc/static/dd40bcbb5f5ac04b6315a92e4e45d0f0/A000066-datasheet.pdf, Erişim tarihi: 12 Kasım 2021.
  • Arduino WiFi Shield Datasheet. https://docs.arduino.cc/retired/shields/arduino-wifi-shield, Erişim tarihi: 12 Kasım 2021.
  • LM35 Sıcaklık sensörü, https://www.direnc.net/lm35dz-hassas-sicaklik-sensoru-entegresi-to-92, Son erişim tarihi: 12 Kasım 2021.
  • LM393 Yangın algılama kartı, https://www.sunrom.com/p/fire-flame-sensor-module, Erişim tarihi: 12 Kasım 2021.
  • Barman, G., Görme Engellilere Yardımcı Ultrasonik Cihaz. Karadeniz Teknik Üniversitesi Mühendislik Fakültesi Tasarım Projesi, 2014.
  • Çamoğlu, G., Kızıl, Ü., Demirel, K., Aksu, S., Nar, H. & Genç, L., Bazı Ekonomik Toprak Nem Sensörlerinin Hassasiyetlerinin Belirlenmesi. Uluslararası Tarım ve Yaban Hayatı Bilimleri Dergisi, 7 (2), 2021, 247-254. DOI: 10.24180/ijaws.846464
  • Heaney, M. B. "Electrical Conductivity and Resistivity." Electrical Measurement, Signal Processing, and Displays. Ed. John G. Webster. CRC Press, 2003. 7-1.
  • Atlas Scientific: Environmental Robotics. EZO-EC. Revised: 9/2020, https://atlas-scientific.com/files/EC_EZO_Datasheet.pdf Erişim tarihi: 12 Kasım 2021.
  • Londo, J., Kushla, D., Carter, C., Soil pH and Tree Species Suitability in the South Andrew, Jacksonville State University, 2010.
  • Atlas Scientific: Environmental Robotics. EZO-pH. Revised: 1/2021, https://www.atlas-scientific.com/files/pH_EZO_Datasheet.pdf Erişim tarihi: 12 Kasım 2021.
  • South Dakota Soil Health Coalition. Soil Electrical Conductivity. https://www.sdsoilhealthcoalition.org/technical-resources/chemical-properties/soil-electrical-conductivity, Erişim tarihi: 12 Kasım 2021.
There are 30 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Makaleler(Araştırma)
Authors

Muhammed Akif Yenikaya 0000-0002-3624-722X

Erdal Güvenoğlu 0000-0003-1333-5953

Süleyman Kondakcı 0000-0001-5150-3220

Early Pub Date June 27, 2022
Publication Date June 27, 2022
Published in Issue Year 2022 Volume: 15 Issue: 1

Cite

APA Yenikaya, M. A., Güvenoğlu, E., & Kondakcı, S. (2022). Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama ve Gübreleme Sistemi. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi, 15(1), 14-23. https://doi.org/10.54525/tbbmd.1028785
AMA Yenikaya MA, Güvenoğlu E, Kondakcı S. Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama ve Gübreleme Sistemi. TBV-BBMD. June 2022;15(1):14-23. doi:10.54525/tbbmd.1028785
Chicago Yenikaya, Muhammed Akif, Erdal Güvenoğlu, and Süleyman Kondakcı. “Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama Ve Gübreleme Sistemi”. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi 15, no. 1 (June 2022): 14-23. https://doi.org/10.54525/tbbmd.1028785.
EndNote Yenikaya MA, Güvenoğlu E, Kondakcı S (June 1, 2022) Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama ve Gübreleme Sistemi. Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi 15 1 14–23.
IEEE M. A. Yenikaya, E. Güvenoğlu, and S. Kondakcı, “Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama ve Gübreleme Sistemi”, TBV-BBMD, vol. 15, no. 1, pp. 14–23, 2022, doi: 10.54525/tbbmd.1028785.
ISNAD Yenikaya, Muhammed Akif et al. “Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama Ve Gübreleme Sistemi”. Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi 15/1 (June 2022), 14-23. https://doi.org/10.54525/tbbmd.1028785.
JAMA Yenikaya MA, Güvenoğlu E, Kondakcı S. Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama ve Gübreleme Sistemi. TBV-BBMD. 2022;15:14–23.
MLA Yenikaya, Muhammed Akif et al. “Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama Ve Gübreleme Sistemi”. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi, vol. 15, no. 1, 2022, pp. 14-23, doi:10.54525/tbbmd.1028785.
Vancouver Yenikaya MA, Güvenoğlu E, Kondakcı S. Nesnelerin İnterneti (IoT) Tabanlı Akıllı Sulama ve Gübreleme Sistemi. TBV-BBMD. 2022;15(1):14-23.

Cited By

IoT-based smart agriculture: an exhaustive study
Wireless Networks
https://doi.org/10.1007/s11276-023-03315-7
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