Araştırma Makalesi
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A Novel Agriculture Tracking System Using Data Mining Approaches

Yıl 2020, Ejosat Özel Sayı 2020 (ISMSIT), 313 - 322, 30.11.2020
https://doi.org/10.31590/ejosat.818934

Öz

Agriculture has been one of our most important needs in the world since the first ages. Nowadays, human knowledge and experience, especially in agriculture, are still lacking in achieving the most productivity. For a plant to grow close to 100% yield, multiple variables must be in optimal condition. In the Agriculture Tracking System, people are able to control the environment required for growing plants, i.e. optimal levels of their variables. Therefore, in this study, we have designed a hardware system with an Internet of Things (IoT) device and 2 sensors. The solar energy to power this hardware system has been used. Also, these sensors are a digital humidity and temperature sensor (DHT11) and Soil Moisture Sensors. Values of incoming from sensors are read with an IP Address. Moreover, these values are written to SQLite database and displayed last 5 records with bar charts. The users can save plants with optimal values. With these values, can make predictions. We have studied the effect of the sun angle on temperature and humidity in the last 5 years with months. We have compared this data with the plants added by the user and presented the most appropriate and closest months as a warning to the user. Another prediction is possible with instant records. When we researched, we saw that the condition of the plant can be categorized according to temperature and humidity. By checking the instant data, a warning message to the user according to these rates is sent by using the K-Nearest Neighbour classification algorithm. As a result, in the tests, the results have shown that this approach can increase productivity.

Teşekkür

4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) 2020' de 332 ID li bildiriyi değerlendiren hakemlere ve semposyum yetkililerine teşekkür ederiz.

Kaynakça

  • Attia, H. A., Getu, B. N., Ghadban, H., & Mustafa, A. K. A. (2014). Portable solar charger with controlled charging current for mobile phone devices. Int. J. of Thermal & Environmental Engineering, 7(1), 17-24.
  • Barış A., Halil K. (2017). Solar Tracking System. Thesis of Karabük University.
  • Baysal, K., Özcan, M. O., Özdüven, F. F., & Beynek, B. Nesnelerin İnterneti Tabanlı Bir Sera Takip Sistemi. Ejovoc (Electronic Journal of Vocational Colleges), 8(2), 49-56.
  • Gondchawar, N., & Kawitkar, R. S. (2016). Internet of Things based smart agriculture. International Journal of advanced research in Computer and Communication Engineering, 5(6), 838-842.
  • Handayani, T. P., Hulukati, S. A., Jaya, R., Tiandho, Y., & Abdullah, R. (2019). The prototype of solar-powered building lighting Internet of Things. In IOP Conference Series: Materials Science and Engineering (Vol. 486, No. 1, p. 012079).
  • Hanschke, L., Heitmann, J., & Renner, C. (2016). Challenges of Wi-Fi-enabled and solar-powered sensors for smart ports. In Proceedings of the 4th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems (pp. 13-18). ACM.
  • Hill, C. A., Such, M. C., Chen, D., Gonzalez, J., & Grady, W. M. (2012). Battery energy storage for enabling integration of distributed solar power generation. IEEE Transactions on smart grid, 3(2), 850-857.
  • Kaur, T., Gambhir, J., & Kumar, S. (2016). Arduino based solar powered battery charging system for rural SHS. In 2016 7th India International Conference on Power Electronics (IICPE) (pp. 1-5). IEEE.
  • Khanna, A., & Ranjan, P. (2015). Solar-powered android-based speed control of DC motor via secure bluetooth. In 2015 Fifth International Conference on Communication Systems and Network Technologies (pp. 1244-1249). IEEE.
  • Lee, M., Hwang, J., & Yoe, H. (2013). Agricultural production system based on Internet of Things. IEEE 16th International Conference on Computational Science and Engineering (pp. 833-837). IEEE.
  • Suma, N., Samson, S. R., Saranya, S., Shanmugapriya, G., & Subhashri, R. (2017). Internet of Things based smart agriculture monitoring system. International Journal on Recent and Innovation Trends in computing and communication, 5(2), 177-181.
  • Taştan, M. (2019). Nesnelerin İnterneti Tabanlı Akıllı Sulama ve Uzaktan İzleme Sistemi. Avrupa Bilim ve Teknoloji Dergisi, (15), 229-236.
  • TongKe, F. (2013). Smart agriculture based on cloud computing and Internet of Things. Journal of Convergence Information Technology, 8(2).
  • Yücel, M., Kılıçarslan, Y., & Yıldırım, M. (2018). Güneş Takip Sistemiyle Çalışan Güneş Panellerin Sulama Uygulamasında Verimlilik Düzeyleri. ÇOMÜ Ziraat Fakültesi Dergisi, 6, 123-130.
  • Zhao, J. C., Zhang, J. F., Feng, Y., & Guo, J. X. (2010). The study and application of the Internet of Things technology in agriculture. In 2010 3rd International Conference on Computer Science and Information Technology (Vol. 2, pp. 462-465). IEEE.

Veri Madenciliği Yaklaşımlarını Kullanan Yeni Bir Tarım Takip Sistemi

Yıl 2020, Ejosat Özel Sayı 2020 (ISMSIT), 313 - 322, 30.11.2020
https://doi.org/10.31590/ejosat.818934

Öz

Tarım, ilk çağlardan beri dünyadaki en önemli ihtiyaçlarımızdan biri olmuştur. Günümüzde, özellikle tarımda insan bilgisi ve deneyimi yine de en verimliliğe ulaşma konusunda eksiktir. Bir bitkinin %100 verime yakın büyümesi için, birden çok değişkenin optimum durumda olması gerekir. Tarım Takip Sisteminde insanlar bitki yetiştirmek için gerekli ortamı, yani değişkenlerinin optimum seviyelerini kontrol edebilmektedir. Bu nedenle, bu çalışmada Nesnelerin Interneti (IoT) cihazı ve 2 sensör içeren bir donanım sistemi tasarladık. Bu donanım sistemine güç sağlamak için güneş enerjisi kullanılmıştır. Ayrıca, bu sensörler Dijial Nem ve Sıcakık (DHT11) ile Toprak Nemi sensörleridir. Sensörlerden gelen değerler bir IP Adresi ile okunur. Bu değerler SQLite veritabanına yazılır ve son 5 kayıt çubuk grafiklerle görüntülenir. Kullanıcılar bitkileri optimum değerlerle kaydedebilirler. Bu değerler ile tahminlerde bulunabilir. Bununla beraber, son 5 yılda güneş açısının sıcaklık ve nem üzerindeki etkisini aylarla birlikte inceledik. Bu verileri kullanıcı tarafından eklenen bitkilerle karşılaştırarak en uygun ve en yakın ayları kullanıcıya uyarı olarak sunduk. Anlık kayıtlarla başka bir tahmin mümkündür. Araştırdığımızda bitkinin durumunun sıcaklık ve neme göre kategorize edilebileceğini gördük. Anlık veriler kontrol edilerek K-En Yakın Komşu sınıflandırma algoritması kullanılarak bu oranlara göre kullanıcıya uyarı mesajı gönderilir. Sonuç olarak testlerde elde edilen sonuçlar, bu yaklaşımın verimliliği artırabileceğini göstermiştir.

Kaynakça

  • Attia, H. A., Getu, B. N., Ghadban, H., & Mustafa, A. K. A. (2014). Portable solar charger with controlled charging current for mobile phone devices. Int. J. of Thermal & Environmental Engineering, 7(1), 17-24.
  • Barış A., Halil K. (2017). Solar Tracking System. Thesis of Karabük University.
  • Baysal, K., Özcan, M. O., Özdüven, F. F., & Beynek, B. Nesnelerin İnterneti Tabanlı Bir Sera Takip Sistemi. Ejovoc (Electronic Journal of Vocational Colleges), 8(2), 49-56.
  • Gondchawar, N., & Kawitkar, R. S. (2016). Internet of Things based smart agriculture. International Journal of advanced research in Computer and Communication Engineering, 5(6), 838-842.
  • Handayani, T. P., Hulukati, S. A., Jaya, R., Tiandho, Y., & Abdullah, R. (2019). The prototype of solar-powered building lighting Internet of Things. In IOP Conference Series: Materials Science and Engineering (Vol. 486, No. 1, p. 012079).
  • Hanschke, L., Heitmann, J., & Renner, C. (2016). Challenges of Wi-Fi-enabled and solar-powered sensors for smart ports. In Proceedings of the 4th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems (pp. 13-18). ACM.
  • Hill, C. A., Such, M. C., Chen, D., Gonzalez, J., & Grady, W. M. (2012). Battery energy storage for enabling integration of distributed solar power generation. IEEE Transactions on smart grid, 3(2), 850-857.
  • Kaur, T., Gambhir, J., & Kumar, S. (2016). Arduino based solar powered battery charging system for rural SHS. In 2016 7th India International Conference on Power Electronics (IICPE) (pp. 1-5). IEEE.
  • Khanna, A., & Ranjan, P. (2015). Solar-powered android-based speed control of DC motor via secure bluetooth. In 2015 Fifth International Conference on Communication Systems and Network Technologies (pp. 1244-1249). IEEE.
  • Lee, M., Hwang, J., & Yoe, H. (2013). Agricultural production system based on Internet of Things. IEEE 16th International Conference on Computational Science and Engineering (pp. 833-837). IEEE.
  • Suma, N., Samson, S. R., Saranya, S., Shanmugapriya, G., & Subhashri, R. (2017). Internet of Things based smart agriculture monitoring system. International Journal on Recent and Innovation Trends in computing and communication, 5(2), 177-181.
  • Taştan, M. (2019). Nesnelerin İnterneti Tabanlı Akıllı Sulama ve Uzaktan İzleme Sistemi. Avrupa Bilim ve Teknoloji Dergisi, (15), 229-236.
  • TongKe, F. (2013). Smart agriculture based on cloud computing and Internet of Things. Journal of Convergence Information Technology, 8(2).
  • Yücel, M., Kılıçarslan, Y., & Yıldırım, M. (2018). Güneş Takip Sistemiyle Çalışan Güneş Panellerin Sulama Uygulamasında Verimlilik Düzeyleri. ÇOMÜ Ziraat Fakültesi Dergisi, 6, 123-130.
  • Zhao, J. C., Zhang, J. F., Feng, Y., & Guo, J. X. (2010). The study and application of the Internet of Things technology in agriculture. In 2010 3rd International Conference on Computer Science and Information Technology (Vol. 2, pp. 462-465). IEEE.
Toplam 15 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Asena Gökçe Albay 0000-0001-5193-9112

Yunus Doğan 0000-0002-0353-5014

Yayımlanma Tarihi 30 Kasım 2020
Yayımlandığı Sayı Yıl 2020 Ejosat Özel Sayı 2020 (ISMSIT)

Kaynak Göster

APA Albay, A. G., & Doğan, Y. (2020). A Novel Agriculture Tracking System Using Data Mining Approaches. Avrupa Bilim Ve Teknoloji Dergisi313-322. https://doi.org/10.31590/ejosat.818934