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IoT-Based Automatic Irrigation Control

  • Akkenaguntla Karthik
  • Anumula Amarnath
  • T. M. Manohar Reddy
  • Veldhanda Tulasi Krishna
  • A. V. Pavan KumarEmail author
Conference paper
  • 11 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 665)

Abstract

Modern world is facing problems to secure the basic needs such as food, water, shelter, and electricity for people. Among these, the most focused need is water as the need of water is increasing immensely. Agriculture sector plays a vital role in the economic development of any country. It is also a major source of raw materials to industries like cotton, tobacco, sugar, etc. Currently, the agriculture sector is said to be facing water problem because of water scarcity. So, a need has raised to use water carefully without wasting it. Human cannot monitor the water availability in fields throughout the day. The cons of manual monitoring can be reduced by using this technology. This paper presents a method to monitor the water level in fields using soil moisture sensor. The proposed method is integrated with GSM and IoT technology for getting the status of pump and operating them from anywhere in the world. The electricity required for the operation of components is less. The water consumed by plants and soil is continuously monitored by using soil moisture sensor; based on the moisture, the motor is automatically controlled to feed water. The operational status of the entire system is communicated through SMS.

Keywords

GSM IoT technology Soil moisture sensor 

References

  1. 1.
    Liu, J., Chai, Y., Xiang, Y., Zhang, X., Gou, S., Liu, Y.: Clean energy consumption of power systems towards smart agriculture: roadmap, bottlenecks and technologies. CSEE J. Power Energy Syst. 4(3), 273–282 (2018).  https://doi.org/10.17775/cseejpes.2017.01290
  2. 2.
    Daskalakis, S.N., Goussetis, G., Assimonis, S.D., Tentzeris, M.M., Georgiadis, A.: A uW backscatter-morse-leaf sensor for low-power agricultural wireless sensor networks. IEEE Sens. J. 18(19), 7889–7898 (2018).  https://doi.org/10.1109/JSEN.2018.2861431CrossRefGoogle Scholar
  3. 3.
    Lucas Gomes Salmento, M., Camponogara, A., Manhaes de Andrade Filho, L., Vidal Ribeiro, M.: A novel synchronization scheme for impulsive UWB-based PLC systems. IEEE Lat. Am. Trans. 15(11), 2050–2058 (2017).  https://doi.org/10.1109/tla.2017.8070407
  4. 4.
    Czajkowski, K., Fitzgerald, S., Foster, I., Kesselman, C.: Grid information services for distributed resource sharing. In: 10th IEEE International Symposium on High Performance Distributed Computing, pp. 181–184. IEEE Press, New York (2001).  https://doi.org/10.1109/hpdc.2001.945188
  5. 5.
    Viani, F., Bertolli, M., Salucci, M., Polo, A.: Low-cost wireless monitoring and decision support for water saving in agriculture. IEEE Sens. J. 17(13), 4299–4309 (2017).  https://doi.org/10.1109/jsen.2017.2705043
  6. 6.
    Jagüey, J.G., Villa-Medina, J.F., López-Guzmán, A., Porta-Gándara, M.Á.: Smartphone irrigation sensor. IEEE Sens. J. 15(9), 5122–5127 (2015).  https://doi.org/10.1109/jsen.2015.2435516
  7. 7.
    Maheswararajah, S., Halgamuge, S.K., Dassanayake, K.B., Chapman, D.: Management of orphaned-nodes in wireless sensor networks for smart irrigation systems. IEEE Trans. Signal Process. 59(10), 4909–4922 (2011).  https://doi.org/10.1109/tsp.2011.2160258
  8. 8.
    Vaishali, S., Suraj, S., Vignesh, G., Dhivya, S., Udhayakumar, S.: Mobile integrated smart irrigation management and monitoring system using IOT. In: International Conference on Communication and Signal Processing (ICCSP), pp. 2164–2167. Chennai (2017).  https://doi.org/10.1109/iccsp.2017.8286792
  9. 9.
    Namala, K.K., Prabhu, AV, K.K., Math, A., Kumari, A., Kulkarni, S.: Smart irrigation with embedded system. In: IEEE Bombay Section Symposium (IBSS), Baramati, pp. 1–5 (2016).  https://doi.org/10.1109/ibss.2016.7940199
  10. 10.
    Ghosh, S., Sayyed, S., Wani, K., Mhatre, M., Hingoliwala, H.A.: Smart irrigation: a smart drip irrigation system using cloud, android and data mining. In: IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT), Pune, pp. 236–239 (2016).  https://doi.org/10.1109/icaecct.2016.7942589
  11. 11.
    Pernapati, K.: IoT based low cost smart irrigation system. In: Second International Conference on Inventive Communication and Computational Technologies (ICICCT), Coimbatore, pp. 1312–1315 (2018).  https://doi.org/10.1109/icicct.2018.8473292
  12. 12.
    Rau, A.J., Sankar, J., Mohan, A.R., Das Krishna, D., Mathew, J.: IoT based smart irrigation system and nutrient detection with disease analysis. In: IEEE Region 10 Symposium (TENSYMP), Cochin, pp. 1–4 (2017).  https://doi.org/10.1109/tenconspring.2017.8070100

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Akkenaguntla Karthik
    • 1
  • Anumula Amarnath
    • 1
  • T. M. Manohar Reddy
    • 1
  • Veldhanda Tulasi Krishna
    • 1
  • A. V. Pavan Kumar
    • 1
    Email author
  1. 1.Department of EEEMadanapalle Institute of Technology & ScienceMadanapalleIndia

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