Skip to main content

A Survey on Wireless Sensor Networks and Instrumentation Techniques for Smart Agriculture

  • Conference paper
  • First Online:
Mobile Computing and Sustainable Informatics

Abstract

Agriculture is the primary source for the development of our country’s economy. It involves production, processing, marketing, and distribution of agricultural produce. Smart agriculture is one of the modern farming practices that increase the agricultural production in a most efficient manner. Smart agriculture involves wireless sensor networks (WSN) for various operations. Wide variety of sensors are used in WSN that assists farmers to know the statistical details of their field which helps them to take accurate decisions and provides instantaneous feedback for various agricultural parameters. Numerous researchers and manufacturers aim to develop real-time sensors based on different approaches, namely electromagnetic, electric, optical, mechanistic, acoustic, or electrochemical, which calculates the physical and chemical properties of soil in agricultural fields. The main objective of this study is to review the application of wireless sensors used in agriculture, the principle and various instrumentation techniques in measuring different parameters in agriculture.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. A.Z. Aqueel-ur-Rehman, N.I. Abbasi, Z.A. Shaikh, A review of wireless sensors and networks’ applications in agriculture. Comput. Stand. Interf. 36, 263–270 (2014)

    Article  Google Scholar 

  2. R.K. Kodali, N. Rawat, L. Boppana, WSN sensors for precision agriculture, in IEEE Region 10 Symposium, 2014, pp. 651–656

    Google Scholar 

  3. V.I. Adamchuk, J.W. Hummel, M.T. Morgan, S.K. Upadhyaya, On-the-go soil sensors for precision agriculture. Comput. Electron. Agric. 44, 71–91 (2004)

    Article  Google Scholar 

  4. S. Veena, M. Rajesh, K. Mahesh, S. Salmon, Survey on smart agriculture using IoT. Int. J. Innov. Res. Eng. Manage. 5, 63–66 (2018)

    Google Scholar 

  5. M.S. Mekala, V. Perumal, A survey: smart agriculture IoT with cloud computing, in International Conference on Microelectronic Devices, Circuits and Systems (IEEE, Vellore, India, 2017), pp. 1–7

    Google Scholar 

  6. R. Madhumathi, Elucidating farmers towards smart agricultural farm building through cloud model, in 10th International Conference on Computing Communication and Networking Technologies (IEEE, Kanpur, 2019), pp. 1–4

    Google Scholar 

  7. A. Rezaee, Design, construction and evaluation of a digital hand-pushed penetrometer. Int. J. Adv. Smart Sensor Netw. Syst. (IJASSN) 7, 1–10 (2017)

    Google Scholar 

  8. Y. Tekin, B. Kul, R. Okursoy, Sensing and 3D mapping of soil compaction. Sensors 8, 3447–3459 (2008)

    Article  Google Scholar 

  9. T.B. Randrup, J.M. Lichter, Measuring soil compaction on construction sites: a review of surface nuclear gauges and penetrometers. J. Arboricult. 27, 109–117 (2001)

    Google Scholar 

  10. V.I. Adamchuk, P. José, Molin: instrumented shanks for soil mechanical resistance measurements. Engenharia Agrícola 26, 161–169 (2006)

    Article  Google Scholar 

  11. M. Futagawa, H. Takao, M. Ishida, K. Sawada, Fabrication of a multi-modal sensor with pH, EC and temperature sensing areas for agriculture application, in IEEE Sensors (New Zealand, 2009), pp. 2013–2016

    Google Scholar 

  12. S.M. Lesch, D.L. Corwin, D.A. Robinson, Apparent soil electrical conductivity mapping as an agricultural management tool in arid zone soils. Comput. Electron. Agricult. 46, 351–378 (2005)

    Article  Google Scholar 

  13. C.M. Anderson-Cook, M.M. Alley, J.K.F. Roygard, R. Khosla, R.B. Noble, J.A. Doolittle, Differentiating soil types using electromagnetic conductivity and crop yield maps. Soil Sci. Soc. Am. J. 66, 1562–1570 (2002)

    Article  Google Scholar 

  14. D.L. Corwin, E. Scudiero, Field-scale apparent soil electrical conductivity, in Methods of Soil Analysis, vol. 1, ed. by S. Logsdon (Soil Science Society of America, Madison, WI, 2016), pp. 1–29

    Google Scholar 

  15. M. Yokota, T. Okada, I. Yamaguchi, An optical sensor for analysis of soil nutrients by using LED light sources. Measur. Sci. Technol. 18, 2197–2201 (2007)

    Google Scholar 

  16. A. Erler, D. Riebe, T. Beitz, H.-G. Lohmannsroben, R. Gebbers, Soil nutrient detection for precision agriculture using handheld laser-induced breakdown spectroscopy (LIBS) and multivariate regression methods (PLSR, Lasso and GPR). Sensors 20, 1–17 (2020)

    Article  Google Scholar 

  17. A.-M. Fortuna, P.J. Patrick, A.M. Nelson, J.L. Steiner, Prediction of soil carbon fractions using a field spectroradiometer equipped with an illuminating contact probe. Soil Syst. 3 (2019)

    Google Scholar 

  18. M. Singh, R. Kumar, A. Sharma, B. Singh, S.K. Thind, Calibration and algorithm development for estimation of nitrogen in wheat crop using tractor mounted N-sensor. Sci. World J. 2015 (2015)

    Google Scholar 

  19. Y. He, X. Liu, Y. Lv, F. Liu, J. Peng, T. Shen, Y. Zhao, Y. Tang, S. Luo, Quantitative analysis of nutrient elements in soil using single and double pulse laser-induced breakdown spectroscopy. Sensors 18 (2018)

    Google Scholar 

  20. M. Naderi-Boldaji, M.Z. Tekeste, RA. Nordstorm, D.J. Bernard, S.J. Birrell, A mechanical-dielectric-high frequency acoustic sensor fusion for soil physical characterization. Comput. Electron. Agric. 156, 10–23 (2019)

    Google Scholar 

  21. F. Adamo, G. Andria, F. Attivissimo, N. Giaquinto, An acoustic method for soil moisture measurement. IEEE Trans. Instrument. Measur. 53, 891–898 (2004)

    Google Scholar 

  22. A. Moallemi-Oreh, S. Minaei, A. Sharifi-Malvajerdi, A.M. Borghaee, Multiprobe soil compaction sensor: an acoustical approach. J. Food Agric. Environ 8, 747–750 (2010)

    Google Scholar 

  23. S. Huang, D.G. Fredlund, S.L. Barbour, Measurement of the coefficient of permeability for a deformable unsaturated soil using a triaxial permeameter. Canadian Geotechn. J. 35, 436–432 (1998)

    Google Scholar 

  24. V.I. Adamchuk, E.D. Lund, B. Sethuramasamyraja, B., M.T. Morgan, A. Dobermann, D.B. Marx, Direct measurement of soil chemical properties on-the-go using ion-selective electrodes. Comput. Electron. Agricult. 48, 272–294 (2005)

    Google Scholar 

  25. A. Al-Busaidi, P. Cookson, T. Yamamoto, Methods of pH determination in calcareous soils: use of electrolytes and suspension effect. Aust. J. Soil Res. 43, 541–545 (2005)

    Article  Google Scholar 

  26. M. Schirrmann, R. Gebbers, E. Kramer, J. Seidel, Soil pH mapping with an on-the-go sensor. Sensors 11, 573–598 (2011)

    Article  Google Scholar 

  27. S. Bhandari, U. Singh, S. Kumbhat, Nafion-modified carbon-based sensor for soil potassium detection. Electroanalysis 31, 1–8 (2019)

    Article  Google Scholar 

Download references

Acknowledgements

The authors sincerely thank the Science and Engineering Research Board (SERB) of DST for the financial support and the Director, ICAR-SBI, Coimbatore, and the Management and Principal of Sri Ramakrishna Engineering College, Coimbatore, for extending the required facilities.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R. Madhumathi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Madhumathi, R., Arumuganathan, T., Shruthi, R. (2022). A Survey on Wireless Sensor Networks and Instrumentation Techniques for Smart Agriculture. In: Shakya, S., Bestak, R., Palanisamy, R., Kamel, K.A. (eds) Mobile Computing and Sustainable Informatics. Lecture Notes on Data Engineering and Communications Technologies, vol 68. Springer, Singapore. https://doi.org/10.1007/978-981-16-1866-6_33

Download citation

Publish with us

Policies and ethics