Skip to main content

Telemetry System for Smart Agriculture

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 373))

Abstract

The use of telemetry systems in SMART agriculture is an innovative approach which consists in the implementation of an information system able to provide data on irrigation parameters throughout a year, also taking into consideration other meteorological parameters. The need for a telemetry system for irrigation is emphasized by the market’s interest in having access to fully automated monitoring and automation solutions for energy efficient and cost-effective agricultural crops. This paper aims to present a telemetry system for monitoring crops with an improved architecture from the point of view of very low energy consumption, low management costs, scalability, forecasting functions, and diagnosis. IoT devices are needed in the agriculture sector to monitor plant growth. This paper also brings to attention an analysis performed with an embedded implemented system. Measured data (collected using ADCON station) include air temperatures; relative humidity and soil temperature. These data are visualized and accessed on the IoT platform using an Internet connection. The ADCON station transmits data from the crop area where it is installed.

Measurements are performed considering energy efficiency criteria and the technologies available on the market. Enlargement facilities lead to an important technical impact and a high potential for marketing.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   99.99
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

Learn about institutional subscriptions

References

  1. Nelson, M.C., et al.: Climate challenges, vulnerabilities, and food security. Proc. Natl. Acad. Sci. U.S.A. 113(2), 298–303 (2016). https://doi.org/10.1073/pnas.1506494113

    Article  MathSciNet  Google Scholar 

  2. Rossati, A.: Global warming and its health impact. Int. J. Occup. Environ. Med. 8(1), 7–20 (2017). https://doi.org/10.15171/ijoem.2017.963

    Article  Google Scholar 

  3. Klomp, J., Hoogezand, B.: Natural disasters and agricultural protection: a panel data analysis. World Dev. 104, 404–417 (2018)

    Article  Google Scholar 

  4. Shelia, V., et al.: A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies. Environ. Model Softw. 115, 144–154 (2019). https://doi.org/10.1016/j.envsoft.2019.02.006

    Article  Google Scholar 

  5. Suciu, G., Bezdedeanu, L., Vasilescu, A., Suciu, V.: Unified intelligent water management using cyberinfrastructures based on cloud computing and IoT. In: 21st International Conference on Control Systems and Computer Science (CSCS), pp. 606–611, Romania (2017). https://doi.org/10.1109/cscs.2017.92

  6. Kamienski, C., et al.: Smart water management platform: IoT-based precision irrigation for agriculture. Sensors 19(2), 276 (2019)

    Article  Google Scholar 

  7. Kapoor, A., Bhat, S.I., Shidnal, S., Mehra, A.: Implementation of IoT (Internet of Things) and image processing in smart agriculture. In: 1st IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS), WOS: 000390719100005, India, pp. 21–26 (2016)

    Google Scholar 

  8. Jianbang, L., Shuxue, Z., Aihua, L., Ye, Y.: Application of Internet of Things in weather modification service in Anhui Province. Meteorol. Sci. Technol. 42, 1143–1146 (2014)

    Google Scholar 

  9. India set to become water scarce by 2025: report, Mumbai. http://www.thehindu.com/. Accessed 9 Apr 2019

  10. Roopaei, M., Rad, P., Choo, K.-K.R.: Cloud of things in smart agriculture: intelligent irrigation monitoring by thermal imaging. IEEE Cloud Comput. 4(1), 10–15 (2017)

    Article  Google Scholar 

  11. Chaudhry, S., Garg, S.: Smart irrigation techniques for water resource management. In: Smart Farming Technologies for Sustainable Agricultural Development. Advances in Environmental Engineering and Green Technologies, WOS: 000461277400011, pp. 196–219 (2019)

    Google Scholar 

  12. Prathibha, S.R., Hongal, A., Jyothi, M.P.: IoT based monitoring system in smart agriculture. In: 1st IEEE International Conference on Recent Advances in Electronics and Communication Technology (ICRAECT), pp. 81–84, India (2017)

    Google Scholar 

  13. Rajalakshmi, P., Mahalakshmi, S.D.: IoT based crop-field monitoring and irrigation automation. In: 10th International Conference on Intelligent Systems and Control (ISCO), India, WOS: 000387435600028 (2016)

    Google Scholar 

  14. Pernapati, K.: IoT based low cost smart irrigation system. In: International Conference on Inventive Communication and Computational Technologies (ICICCT), WOS: 000456251700265, pp. 1312–1315, India (2018)

    Google Scholar 

  15. Difallah, W., Benahmed, K., Draoui, B., Bounaama, F.: Linear optimization model for efficient use of irrigation water. Int. J. Agron. 1–8 (2017). Article number: 5353648 https://doi.org/10.1155/2017/5353648

  16. Gangadharan, A., et al.: Solar powered smart irrigation system. Int. J. Comput. Sci. Inf. Technol. Secur. 102–106 (2016)

    Google Scholar 

  17. Patil, S., Rudresh, S.M., Kallendrachari, K.M., Kiran, K., Vani, H.V.: Solar powered irrigation system with automatic control of pump and SMS alert. Int. J. Eng. Technol. Manag. Res. 3(1), 90–94 (2015)

    Google Scholar 

  18. Nikesh, G., Kawitkar, R.S.: Smart agriculture using IoT and WSN based modern technologies. Int. J. Innov. Res. Comput. Commun. Eng. 4(6), 12070–12076 (2016)

    Google Scholar 

  19. Ibrahim, M., Rawidean, M., Kassim, M., Harun, A.N.: IoT in precision agriculture applications using wireless moisture sensor network. In: IEEE Conference on Open Systems, WOS: 000411226100005, pp. 24–29, Langkawi, Malaysia (2016)

    Google Scholar 

  20. Rasul, G., Chaudhry, Q.Z., Mahmood, A., Hyder, K.W.: Effect of temperature rise on crop growth and productivity. Pak. J. Meteorol. 8(15), 53–62 (2011)

    Google Scholar 

  21. Bellingham, K.: The role of soil moisture on our climate. http://www.soilsensor.com/climatech. Accessed 10 Apr 2019

  22. Mareels, I., Weyer, E., Ooi, S.K., Cantoni, M., Li, Y., Nair, G.: Systems engineering for irrigation systems: success and challenges. Annu. Rev. Control 29(2), 191–204 (2005). https://doi.org/10.1016/j.arcontrol.2005.08.001

    Article  Google Scholar 

  23. Ahmad, L., Habib Kanth, R., Parvaze, S., Sheraz Mahdi, S.: Measurement of humidity. Experimental Agrometeorology: A Practical Manual, pp. 23–27. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69185-5_4

    Chapter  Google Scholar 

  24. Sawant, S., Durbha, S.S., Adinarayana, J.: Interoperable agro-meteorological observation and analysis platform for precision agriculture: a case study in citrus crop water requirement estimation. Comput. Electron. Agric. 138, 175–187 (2017). https://doi.org/10.1016/j.compag.2017.04.019

    Article  Google Scholar 

  25. Davis, S.L., Dukes, M.D.: Landscape irrigation with evapotranspiration controllers in a humid climate. Trans. ASABE 55(2), 571–580 (2012)

    Article  Google Scholar 

  26. Prichard, T.: Vineyard irrigation systems. Raisin Production Manual University of California Agricultural and Natural Resources Publication, vol. 3393, pp. 57–63, Oakland (2000)

    Google Scholar 

  27. Jensen, M.E., Allen, R.G.: Evaporation, evapotranspiration and irrigation water requirements. ASCE Manuals and Reports on Engineering, no. 70 (2016)

    Google Scholar 

  28. Nabil, M.: Interaction of advanced scientific irrigation management with I-Scada system for efficient and sustainable production of fiber on 10,360 hectares. Resource Magazine, pp. 203–212 (2010)

    Google Scholar 

  29. OTT Hydromet. http://m.ott.com/index.php?id=93&L=2. Accessed 10 Apr 2019

  30. Addvantage Pro. https://www.ADCON.com/products/software-285/ADCON-addvantage-6x-1485/. Accessed 12 Apr 2019

Download references

Acknowledgment

The work presented in this paper has been funded by the SmartAgro project subsidiary contract no. 8592/08.05.2018, from the NETIO project ID: P_40_270, MySmis Code: 105976.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to C. M. Balaceanu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Balaceanu, C.M., Marcu, I., Suciu, G. (2019). Telemetry System for Smart Agriculture. In: Abramowicz, W., Corchuelo, R. (eds) Business Information Systems Workshops. BIS 2019. Lecture Notes in Business Information Processing, vol 373. Springer, Cham. https://doi.org/10.1007/978-3-030-36691-9_48

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-36691-9_48

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36690-2

  • Online ISBN: 978-3-030-36691-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics