Skip to main content

Green Energy-Based Efficient IoT Sensor Network for Small Farms

  • 98 Accesses

Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 436)

Abstract

The recent advancement in the Internet of Things (IoT) makes crop management much smarter and helps optimize resource consumption in the agriculture industry. However, due to the high deployment and operational cost of IoT-based infrastructure, it becomes pretty expansive to be afforded by small farm holders. In this paper, an energy-efficient, low-cost, in-house wireless sensor network has been developed and established for collecting important field parameters directly from small household farms. The sensor nodes equipped with in-situ sensors were placed in the test field. The parameters such as atmospheric temperature, humidity, and soil moisture are measured through various sensors. Consequently, the sensors’ data is transferred from the sensor nodes to the Gateway via Long-range (LoRA) communication. The Gateway is designed to push the sensor data to the application server (ThingSpeak) through the Long-range wide-area network (LoRAWAN) protocol. The performance of the proposed LoRaWAN based WSN was tested over the 868 MHz unlicensed ISM indoor network setup for an entire season of rice crop and found satisfactory even in the harsh propagation environment.

Keywords

  • Sensor network
  • Sensor node
  • Gateway
  • LoRAWAN

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-031-01984-5_2
  • Chapter length: 13 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   64.99
Price excludes VAT (USA)
  • ISBN: 978-3-031-01984-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   84.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.
Fig. 10.

References

  1. Rayhana, R., Xiao, G., Liu, Z.: Internet of things empowered smart greenhouse farming. IEEE J. Radio Freq. Identif. 4(3), 195–211 (2020)

    CrossRef  Google Scholar 

  2. Anand, T., Sinha, S., Mandal, M., Chamola, V., Yu, F.R.: AgriSegNet: deep aerial semantic segmentation framework for IoT-assisted precision agriculture. IEEE Sens. J. 21(16), 17581–17590 (2021)

    CrossRef  Google Scholar 

  3. Boursianis, D., et al.: Smart irrigation system for precision agriculture-the AREThOU5A IoT platform. IEEE Sens. J. 21(16), 17539–17547 (2021)

    CrossRef  Google Scholar 

  4. Yang, X., et al.: A survey on smart agriculture: development modes, technologies, and security and privacy challenges. IEEE/CAA J. Autom. Sin. 8(2), 273–302 (2021)

    CrossRef  Google Scholar 

  5. Jinya, S., et al.: Aerial visual perception in smart farming: field study of wheat yellow rust monitoring. IEEE Trans. Industr. Inf. 17(3), 2242–2249 (2021)

    CrossRef  Google Scholar 

  6. Fishman, R., et al.: Digital villages: a data-driven approach to precision agriculture in small farms. In: 9th International Conference on Sensor Network (SENSORNETS), pp. 1–6. Valletta, Malta (2020)

    Google Scholar 

  7. Jamroen, C., Komkum, P., Fongkerd, C., Krongpha, W.: An intelligent irrigation scheduling system using low-cost wireless sensor network toward sustainable and precision agriculture. IEEE Access 8, 172756–172769 (2001)

    CrossRef  Google Scholar 

  8. Ojha, T., Misra, S., Raghuwanshi, N.S.: Internet of things for agricultural applications: the state of the art. IEEE Internet Things J. 8(14), 10973–10997 (2021)

    CrossRef  Google Scholar 

  9. Kour, V.P., Arora, S.: Recent developments of the internet of things in agriculture: a survey. IEEE Internet Things J. 8, 129924–129957 (2020)

    Google Scholar 

  10. Raza, U., Kulkarni, P., Sooriyabandara, M.: Low power wide area networks: an overview. IEEE Commun. Surv. Tutor. 19(2), 855–873 (2017)

    CrossRef  Google Scholar 

  11. LoRa Alliance Homepage. https://www.lora-alliance.org. Accessed 2015

  12. Sigfox Homepage. https://www.sigfox.com. Accessed 2010

  13. Ingenue RPMA Homepage. https://www.ingenu.com/technology/rpma. Accessed 2008

  14. Telensa Homepage. http://www.telensa.com. Accessed 2005

  15. Weightless Homepage. http://www.weightless.org. Accessed 2016

  16. Nokia: LTE M2M-optimizing LTE for the Internet of Things’ Homepage. https://gsacom.com/paper/nokia-lte-m2m-optimizing-lte-for-the-internet-of-things/. Accessed 2017

  17. Neumann, P., Montavont, J., Nol, T.: Indoor deployment of low-power wide-area networks (LPWAN): A LoRaWAN case study. In: 2016 IEEE 12th Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 1–8. IEEE, New York, USA (2016)

    Google Scholar 

  18. Centenaro, M., Vangelista, L., Zanella, A., Zorzi, M.: Long-range communications in unlicensed bands: the rising stars in the IoT and smart city scenarios. IEEE Wirel. Commun. 23(5), 60–67 (2016)

    CrossRef  Google Scholar 

  19. Wen-Liang, C., et al.: AgriTalk: IoT for precision soil farming of turmeric cultivation. IEEE Internet Things J. 6(3), 5209–5223 (2019)

    CrossRef  Google Scholar 

  20. Petäjäjärvi, J., Mikhaylov, K., Pettissalo, M., Janhunen, J., Iinatti, J.: Performance of a low-power wide area network based on LoRa technology: doppler robustness, scalability, and coverage. J. Distrib. Sensor Netw. 13(3), 1–16 (2017)

    Google Scholar 

  21. Petäjäjärvi, J., Mikhaylov, K., Roivainen, A., and Hanninen, T.: On the coverage of LPWANs: Range evaluation and channel attenuation model for LoRa technology. In Proc.14th International Conference on ITS Telecommunications, pp. 55–59, (2015)

    Google Scholar 

  22. Goswami, V., Singh, P., Dwivedi, P., Chauhan, S.: Soil health monitoring system. Int. J. Res. Appl. Sci. Eng. Technol. 8(5), 1536–1540 (2020)

    CrossRef  Google Scholar 

  23. Salam, A.: Internet of things in agricultural innovation and security. In: Salam, A. (eds.) Internet of Things for Sustainable Community Development, pp. 71-112. Springer, Cham (2020).https://doi.org/10.1007/978-3-030-35291-2_3

  24. CartaSense Ltd. Homepage. https://cartasense-coldchain.com/products/m-sensor-ms/. Accessed 2007

  25. Libelium Homepage. https://www.libelium.com/iot-products/plug-sense/. Accessed 2006

Download references

Acknowledgements

This work is fully funded and supported by the project 'Digital Village: A Data-Driven Approach to Precision Agriculture in Small Farms,' under the TIET-TAU center of excellence for food security (T2CEFS) in Thapar Institute of Engineering and Technology (A central university), Patiala, Punjab, India. I thank all the co-authors for their expertise and assistance throughout our study and help in writing the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Amit Mishra .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Mishra, A., Singh, S., Verma, K., Bhatia, P., Ghosh, M., Shacham-Diamand, Y. (2022). Green Energy-Based Efficient IoT Sensor Network for Small Farms. In: Seyman, M.N. (eds) Electrical and Computer Engineering. ICECENG 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 436. Springer, Cham. https://doi.org/10.1007/978-3-031-01984-5_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-01984-5_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-01983-8

  • Online ISBN: 978-3-031-01984-5

  • eBook Packages: Computer ScienceComputer Science (R0)