Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

Smart Metering Architecture for Agriculture Applications

  • Conference paper
  • First Online:
Advanced Information Networking and Applications (AINA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 451))

Abstract

The development of technology has made agriculture more and more efficient, being more productive with less resources consumed, such as water and fertilizers. Our objective is to develop more efficient measurement systems for agricultural applications, e.g. to be more intelligent measurement and data processing and to make forecasts, helping decision-making. In this work, an architecture based on distributed edge-fog-cloud computing is presented. Through low power consumption and wide-area communications, this architecture can be used for measurement of climate, energy, and soil variables to achieve more productive crops.

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

Access this chapter

Log in via an institution

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 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
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

Abbreviations

AI:

Artificial intelligence

AMI:

Advanced measurement infrastructure

CAN:

Campus area network

DC:

Data concentrator

DL:

Data lake

DER:

Distributed energy resource

GSM:

Global system for mobile communications

IoT:

Internet of Things

LAN:

Local area network

LPWAN:

Low power wide area network

MAN:

Metropolitan area network

SBC:

Simple card computer

SM:

Smart meter

WAN:

Wide

WP:

Water pumps

WSAN:

Wireless sensor and actuator network

References

  1. Guerrero-Ibañez, J.A., et al.: SGreenH-IoT: Plataforma IoT para Agricultura de Precisión. In: CISCI 2017 - Decima Sexta Conferencia Iberoamericana en Sistemas, Cibernetica e Informatica, Decimo Cuarto Simposium Iberoamericano en Educacion, Cibernetica e Informatica, SIECI 2017 - Proceedings, pp. 315–320 (2017)

    Google Scholar 

  2. Ragab, R., Prudhomme, C.: Climate change and water resources management in arid and semi-arid regions: Prospective and challenges for the 21st century. Biosyst. Eng. 81(1), 3–34 (2002)

    Article  Google Scholar 

  3. Sales, N., Remedios, O., Arsenio, A.: Wireless sensor and actuator system for smart irrigation on the cloud. In: Proceedings of the IEEE World Forum on Internet of Things, WF-IoT 2015, pp. 693–698. Institute of Electrical and Electronics Engineers Inc. (2015)

    Google Scholar 

  4. Khriji, S., El Houssaini, D., Kammoun, I., Kanoun, O.: Precision irrigation: an IoT-enabled wireless sensor network for smart irrigation systems. In: Hamrita, T.K. (ed.) Women in Precision Agriculture. WES, pp. 107–129. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-49244-1_6

    Chapter  Google Scholar 

  5. Delegación SADER Querétaro: Convocatoria Componente Investigación, Innovación y Desarrollo Tecnológico Agrícola. Programa de Fomento a la Agricultura (2019). https://rb.gy/f6incd

  6. Srivastava, P., Bajaj, M., Rana, A.: Overview of ESP8266 Wi-Fi module based smart irrigation system using IOT. In: Proceedings of the 4th IEEE International Conference on Advances in Electrical and Electronics, Information, Communication and Bioinformatics, AEEICB 2018. Institute of Electrical and Electronics Engineers Inc. (2018)

    Google Scholar 

  7. Agrovoltaic. https://agrovoltaic.org/

  8. Tajwar, M., et al.: Design and implementation of an IoT based automated agricultural monitoring and control system. In: 1st International Conference on Robotics, Electrical and Signal Processing Techniques, ICREST 2019, pp. 13–16. Institute of Electrical and Electronics Engineers Inc. (2019)

    Google Scholar 

  9. Munir, M., et al.: Intelligent and smart irrigation system using edge computing and IoT. Complexity 2021, 1–16 (2021)

    Google Scholar 

  10. Sophocleous, M., Karkotis, A., Georgiou, J.: A versatile, stand-alone, in-field sensor node for implementation in precision agriculture. IEEE J. Emerg. Sel. Top. Circ. Syst. 11(3), 449–457 (2021)

    Article  Google Scholar 

  11. Shanmuga, J.P., et al.: A survey on LoRa networking: research problems, current solutions, and open issues. IEEE Commun. Surv. Tut. 22(1), 371–388 (2020)

    Article  Google Scholar 

  12. Lloret, J., et al.: Cluster-based communication protocol and architecture for a wastewater purification system intended for irrigation. IEEE Access 9, 142374–142389 (2021)

    Article  Google Scholar 

  13. Di Renzone, G., et al.: LoRaWAN underground to aboveground data transmission performances for different soil compositions. IEEE Trans. Instrum. Meas. 70(2021), 1–13 (2021)

    Article  Google Scholar 

  14. Willockx, B., Herteleer, B., Cappelle, J.: Theoretical potential of agrovoltaic systems in Europe: a preliminary study with winter wheat. In: 2020 47th IEEE Photovoltaic Specialists Conference (PVSC), pp. 0996–1001 (2020)

    Google Scholar 

  15. John, R., Mahto, V.: Agrovoltaics farming design and simulation. In 2021 IEEE 48th Photovoltaic Specialists Conference (PVSC), pp. 2625–2629 (2021)

    Google Scholar 

  16. Huang, C., et al.: Smart meter pinging and reading through AMI two-way communication networks to monitor grid edge devices and DERs. IEEE Trans. Smart Grid (2021)

    Google Scholar 

  17. Alharbi, H., Aldossary, M.: Energy-efficient edge-fog-cloud architecture for IoT-based smart agriculture environment. IEEE Access 9(2021), 110480–110492 (2021)

    Article  Google Scholar 

  18. Taneja, M., et al.: Connected cows: utilizing fog and cloud analytics toward data-driven decisions for smart dairy farming. IEEE IoT Mag. 2(4), 32–37 (2019)

    Google Scholar 

  19. Habibi, M., et al.: A comprehensive survey of RAN architectures toward 5G mobile communication system. IEEE Access 7, 70371–70421 (2019)

    Article  Google Scholar 

  20. Liya, M., Arjun, D.: A survey of LPWAN technology in agricultural field. In: 2020 4th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), pp. 313–317 (2020)

    Google Scholar 

  21. Valecce, G., et al.: NB-IoT for smart agriculture: experiments from the field. In: 2020 7th International Conference on Control, Decision and Information Technologies (CoDIT), pp. 71–75 (2020)

    Google Scholar 

  22. Chew, K., et al.: Fog-based WSAN for agriculture in developing countries. In: 2021 IEEE International Conference on Smart Internet of Things (SmartIoT), pp. 289–293 (2021)

    Google Scholar 

  23. Pressman, R., Maxim, B.: Software Engineering: A Practitioner’s Approach, 9th edn. McGraw Hill (2020). ISBN 9781259872976

    Google Scholar 

Download references

Acknowledgments

The authors thank the Tecnológico Nacional de México for partial financial support through grant 13537-22.P and the British Council Newton Fund grant 540323618.

Author information

Authors and Affiliations

  1. Tecnológico Nacional de México/I. T. de Morelia, Av. Tecnológico 1500, Lomas de Santiaguito, Morelia, Mexico

    Juan C. Olivares-Rojas, José A. Gutiérrez-Gnecchi, Enrique Reyes-Archundia & Adriana C. Téllez-Anguiano

  2. Department of Electrical and Electronic Engineering, The University of Manchester, Manchester, M13 9PL, UK

    Wuqiang Yang

Authors
  1. Juan C. Olivares-Rojas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. José A. Gutiérrez-Gnecchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wuqiang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Enrique Reyes-Archundia
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Adriana C. Téllez-Anguiano
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Juan C. Olivares-Rojas .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. University of Technology Sydney, Sydney, NSW, Australia

    Farookh Hussain

  3. Faculty of Bussiness Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Olivares-Rojas, J.C., Gutiérrez-Gnecchi, J.A., Yang, W., Reyes-Archundia, E., Téllez-Anguiano, A.C. (2022). Smart Metering Architecture for Agriculture Applications. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 451. Springer, Cham. https://doi.org/10.1007/978-3-030-99619-2_39

Download citation

Publish with us

Policies and ethics

Search

Navigation