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Development of an IoT-Based (LoRaWAN) Tractor Tracking System

Yıl 2022, Cilt: 28 Sayı: 3, 438 - 448, 05.09.2022
https://doi.org/10.15832/ankutbd.769200

Öz

The use of new technologies and precision agriculture (PA) in farms has become more important due to the need for enough agricultural production for increasing world population opposed to decreasing farm areas. PA covers wide range of technologies like sensors, microcontroller-based devices, machine to machine communication technologies, global positioning systems but, the investment costs of these devices are literally expensive which become a constraint for farmers especially in developing countries. Internet of things (IoT) technology is a new era that agricultural production will be the one area mostly affected by. LoRaWAN is one of the new communication technologies for IoT which enables almost everything on the planet to be connected to internet and deliver high amount of data with no expense. In this research by using the advantages of LoRaWAN, a new IoT-based tractor tracking system including a LoRaWAN module and a web-based software was developed, and the test results were evaluated. As a result, it was found that the developed system was capable of measuring and sending tractor sensor data along with geospatial position of the tractor and serving the data on the web-based user interface.

Destekleyen Kurum

TÜBİTAK

Proje Numarası

2170351

Teşekkür

This study was financially supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK) under the Project number 2170351.

Kaynakça

  • Aqeel-Ur-Rehman Abbasi A Z, Islam N & Shaikh Z A (2014). A review of wireless sensors and networks’ applications in agriculture. Computer Standards and Interfaces, 36(2), 263-270. https://doi.org/10.1016/j.csi.2011.03.004
  • Barman A, Neogi B & Pal S (2020). Solar-Powered Automated IoT-Based Drip Irrigation System. IoT and Analytics for Agriculture, Studies in Big Data, 63, 27-49. https://doi.org/10.1007/978-981-13-9177-4_2
  • Bhatnagar V & Chandra R (2020). IoT-Based Soil Health Monitoring and Recommendation System. IoT and Analytics for Agriculture, Vol. 2, Studies in Big Data, 67, 1-21. https://doi.org/10.1007/978-981-15-0663-5_1https://doi.org/10.1007/978-981-15-0663-5_1
  • Civelek Ç (2020). Evaluation of Internet of Things (IoT) Technology to be Used as a Precision Agriculture Solution for Turkey’s Agriculture. Fresenius Environmental Bulletin, 29(07-A), 5689-5695
  • Das V J, Sharma S & Kaushik A (2019). Views of Irish farmers on smart farming technologies: an observational study. AgriEngineering, 1(2), 164-187. https://doi.org/10.3390/agriengineering1020013
  • Dasig Jr D D & Mendez J M (2020). An IoT and Wireless Sensor Network-Based Technology for a Low-Cost Precision Apiculture. IoT and Analytics for Agriculture, Vol. 2, Studies in Big Data, 67, 23-44. https://doi.org/10.1007/978-981-15-0663-5_4
  • Davcev D, Mitreski K, Trajkovic S, Nikolovski V & Koteli N (2018). IoT Agriculture System Based on LoRaWAN. 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS), Imperia, Italy, 13-15 June 2018 Erickson B, Lowenberg-De Boer J & Bradford J (2017). 2017 Precision Agriculture Dealership Survey. Departments of Agricultural Economics and Agronomy, Purdue University
  • European Commission (2017). Industry 4.0 in Agriculture: Focus on IoT Aspects. https://ec.europa.eu/growth/tools-databases/dem/monitor/sites/default/files/DTM_Agriculture%204.0%20IoT%20v1.pdf. Last accessed 4 February 2020
  • Keskin M, Say S M & Görücü Keskin S. (2018). Farmers’ experiences with GNSS-based tractor auto guidance in Adana province of Turkey. Journal of Agricultural Faculty of Gaziosmanpasa University, 35 (2), 172-181
  • Keskin M & Sekerli Y E (2016). Awareness and adoption of precision agriculture in the Cukurova region of Turkey. Agronomy Research, 14(4), 1307-1320
  • Mendez J M & Dasig D D (2020). Frost Prediction in Highland Crops Management Using IoT-Enabled System and Multiple Regression. IoT and Analytics for Agriculture, Vol. 2, Studies in Big Data, 67, 261-288. https://doi.org/10.1007/978-981-15-0663-5_13
  • Meola A. Why IoT, Big Data & Smart Farming Are the Future of Agriculture. Business Insider (2017). Available online: http://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10 (accessed 10 December 2017)
  • Onwunde D I, Chen G, Hashim N, Esdaile J R, Gomes C, Khaled A Y, Alonge A F & Ikrang E (2018). Mechanization of Agricultural Production in Developing Countries. Advances in Agricultural Machinery and Technologies. Taylor and Francis Group, Boca Raton, Florida, USA. 472 pp. ISBN: 978-1-4987-5412-5
  • Pierce F J & Nowak P (1999). Aspects of precision agriculture. Advances in Agronomy, 67, 1-85. https://doi.org/10.1016/S0065-2113(08)60513-1
  • Saygılı F, Kaya A, Çalışkan E T & Kozal E (2019). Türk Tarımının Global Entegrasyonu Ve Tarım 4.0. İzmir Ticaret Borsası No: 98: 100 pp. https://itb.org.tr/img/userfiles/files/ITB%20TARIM.pdf?v=1550751511711. Last accessed 19 May 2020
  • Shabandri B & Madara S R (2020). IoT-Based Smart Tree Management Solution for Green Cities. IoT and Analytics for Agriculture, Vol. 2, Studies in Big Data, 67, 181-199. https://doi.org/10.1007/978-981-15-0663-5_9
  • Turkish Statistical Institute (TÜİK) (2019a). Number of Road Motor Vehicles by Model Years. http://www.tuik.gov.tr/PreIstatistikTablo.do?istab_id=355. Last accessed 2 August 2019
  • Turkish Statistical Institute (TÜİK) (2019b). Number of Road Motor Vehicles by Model Years. Number of Main Agricultural Machinery and Equipment by Size of Holdings and Forms of Ownership. http://www.tuik.gov.tr/PreIstatistikTablo.do?istab_id=298. Last accessed 2 August 2019
Yıl 2022, Cilt: 28 Sayı: 3, 438 - 448, 05.09.2022
https://doi.org/10.15832/ankutbd.769200

Öz

Proje Numarası

2170351

Kaynakça

  • Aqeel-Ur-Rehman Abbasi A Z, Islam N & Shaikh Z A (2014). A review of wireless sensors and networks’ applications in agriculture. Computer Standards and Interfaces, 36(2), 263-270. https://doi.org/10.1016/j.csi.2011.03.004
  • Barman A, Neogi B & Pal S (2020). Solar-Powered Automated IoT-Based Drip Irrigation System. IoT and Analytics for Agriculture, Studies in Big Data, 63, 27-49. https://doi.org/10.1007/978-981-13-9177-4_2
  • Bhatnagar V & Chandra R (2020). IoT-Based Soil Health Monitoring and Recommendation System. IoT and Analytics for Agriculture, Vol. 2, Studies in Big Data, 67, 1-21. https://doi.org/10.1007/978-981-15-0663-5_1https://doi.org/10.1007/978-981-15-0663-5_1
  • Civelek Ç (2020). Evaluation of Internet of Things (IoT) Technology to be Used as a Precision Agriculture Solution for Turkey’s Agriculture. Fresenius Environmental Bulletin, 29(07-A), 5689-5695
  • Das V J, Sharma S & Kaushik A (2019). Views of Irish farmers on smart farming technologies: an observational study. AgriEngineering, 1(2), 164-187. https://doi.org/10.3390/agriengineering1020013
  • Dasig Jr D D & Mendez J M (2020). An IoT and Wireless Sensor Network-Based Technology for a Low-Cost Precision Apiculture. IoT and Analytics for Agriculture, Vol. 2, Studies in Big Data, 67, 23-44. https://doi.org/10.1007/978-981-15-0663-5_4
  • Davcev D, Mitreski K, Trajkovic S, Nikolovski V & Koteli N (2018). IoT Agriculture System Based on LoRaWAN. 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS), Imperia, Italy, 13-15 June 2018 Erickson B, Lowenberg-De Boer J & Bradford J (2017). 2017 Precision Agriculture Dealership Survey. Departments of Agricultural Economics and Agronomy, Purdue University
  • European Commission (2017). Industry 4.0 in Agriculture: Focus on IoT Aspects. https://ec.europa.eu/growth/tools-databases/dem/monitor/sites/default/files/DTM_Agriculture%204.0%20IoT%20v1.pdf. Last accessed 4 February 2020
  • Keskin M, Say S M & Görücü Keskin S. (2018). Farmers’ experiences with GNSS-based tractor auto guidance in Adana province of Turkey. Journal of Agricultural Faculty of Gaziosmanpasa University, 35 (2), 172-181
  • Keskin M & Sekerli Y E (2016). Awareness and adoption of precision agriculture in the Cukurova region of Turkey. Agronomy Research, 14(4), 1307-1320
  • Mendez J M & Dasig D D (2020). Frost Prediction in Highland Crops Management Using IoT-Enabled System and Multiple Regression. IoT and Analytics for Agriculture, Vol. 2, Studies in Big Data, 67, 261-288. https://doi.org/10.1007/978-981-15-0663-5_13
  • Meola A. Why IoT, Big Data & Smart Farming Are the Future of Agriculture. Business Insider (2017). Available online: http://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10 (accessed 10 December 2017)
  • Onwunde D I, Chen G, Hashim N, Esdaile J R, Gomes C, Khaled A Y, Alonge A F & Ikrang E (2018). Mechanization of Agricultural Production in Developing Countries. Advances in Agricultural Machinery and Technologies. Taylor and Francis Group, Boca Raton, Florida, USA. 472 pp. ISBN: 978-1-4987-5412-5
  • Pierce F J & Nowak P (1999). Aspects of precision agriculture. Advances in Agronomy, 67, 1-85. https://doi.org/10.1016/S0065-2113(08)60513-1
  • Saygılı F, Kaya A, Çalışkan E T & Kozal E (2019). Türk Tarımının Global Entegrasyonu Ve Tarım 4.0. İzmir Ticaret Borsası No: 98: 100 pp. https://itb.org.tr/img/userfiles/files/ITB%20TARIM.pdf?v=1550751511711. Last accessed 19 May 2020
  • Shabandri B & Madara S R (2020). IoT-Based Smart Tree Management Solution for Green Cities. IoT and Analytics for Agriculture, Vol. 2, Studies in Big Data, 67, 181-199. https://doi.org/10.1007/978-981-15-0663-5_9
  • Turkish Statistical Institute (TÜİK) (2019a). Number of Road Motor Vehicles by Model Years. http://www.tuik.gov.tr/PreIstatistikTablo.do?istab_id=355. Last accessed 2 August 2019
  • Turkish Statistical Institute (TÜİK) (2019b). Number of Road Motor Vehicles by Model Years. Number of Main Agricultural Machinery and Equipment by Size of Holdings and Forms of Ownership. http://www.tuik.gov.tr/PreIstatistikTablo.do?istab_id=298. Last accessed 2 August 2019
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Çağdaş Civelek 0000-0002-3669-488X

Proje Numarası 2170351
Yayımlanma Tarihi 5 Eylül 2022
Gönderilme Tarihi 14 Temmuz 2020
Kabul Tarihi 5 Ağustos 2021
Yayımlandığı Sayı Yıl 2022 Cilt: 28 Sayı: 3

Kaynak Göster

APA Civelek, Ç. (2022). Development of an IoT-Based (LoRaWAN) Tractor Tracking System. Journal of Agricultural Sciences, 28(3), 438-448. https://doi.org/10.15832/ankutbd.769200

Journal of Agricultural Sciences is published open access journal. All articles are published under the terms of the Creative Commons Attribution License (CC BY).