Skip to main content
SpringerLink
Log in

Spatiotemporal Data Compression on IoT Devices in Smart Irrigation System

  • Conference paper
  • First Online:
Pattern Recognition and Data Analysis with Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 888))

  • 679 Accesses

Abstract

With the advancement in technology and the evolution of the Internet of Things (IoT) era, the quantity of data generated by devices has increased tremendously. The IoT is an umbrella domain with enormously prolific applications like smart homes, waste management, agriculture, and retail. A huge amount of data is generated by these applications. This creates the need for data handling as well as management to be used for data processing. IoT applications are achieved by means of sensor-interfaced battery-powered device deployments. Low energy consumption, data handling, and fast performance are some of the key features an IoT device should possess. However, the limited memory of these devices is a concern as it is insufficient to handle the amount of data generated by the sensors. These concerns are targeted in the paper and applied to smart agriculture applications where real-time data fetched by sensors are compressed and saved onto the device, thus properly handling the data. The reconstructed data are obtained post-compression and decompression and are used for decision-making. It provides 100% accuracy, and compression has no ill effect on the data. Further, the energy efficacy of the work is compared, and it is found to be on an average ∼47% efficient against the compared algorithms.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. Ashton, K.: That ‘Internet of Things’ thing. RFiD J. 22(7), 97–114 (2009)

    Google Scholar 

  2. Jin, J., Gubbi, J., Marusic, S., Palaniswami, M.: An information framework for creating a smart city through internet of things. IEEE Internet Things J. 1(2), 112–121 (2014)

    Article  Google Scholar 

  3. Yang, G., Xie, L., Mantysalo, M., Zhou, X., Pang, Z., Da Xu, L., Kao-Walter, S., Chen, Q., Zheng, L.R.: A health-IoT platform based on the integration of intelligent packaging, unobtrusive bio-sensor, and intelligent medicine box. IEEE Trans. Ind. Inform. 10(4), 2180–2191 (2014)

    Google Scholar 

  4. Gutierrez, J., Villa-Medina, J.F., Nieto-Garibay, A., Porta-G´andara, M.A.: Automated irrigation system using a wireless sensor network and GPRS module. IEEE Trans. Instrum. Measure. 63(1), 166–176 (2014)

    Google Scholar 

  5. Lee, S.W., Kim, H.Y.: An energy-efficient low-memory image compression system for multimedia IoT products. EURASIP J. Image Video Process. 2018(1), 87 (2018)

    Article  Google Scholar 

  6. Lee, Y., Hwang, E., Choi, J.: A unified approach for compression and authentication of smart meter reading in Ami. IEEE Access 7, 34383–34394 (2019)

    Article  Google Scholar 

  7. Del Testa, D., Rossi, M.: Lightweight lossy compression of biometric patterns via denoising autoencoders. IEEE Signal Process. Lett. 22(12), 2304–2308 (2015)

    Article  Google Scholar 

  8. Tekeste, T., Saleh, H., Mohammad, B., Ismail, M.: Ultra-low power QRS detection and ECG compression architecture for IoT healthcare devices. IEEE Trans. Circuits Syst. I Regul. Pap. 66(2), 669–679 (2018)

    Article  Google Scholar 

  9. Bhargava, K., Ivanov, S., Donnelly, W., Kulatunga, C.: Using edge analytics to improve data collection in precision dairy farming. In: 2016 IEEE 41st Conference on Local Computer Networks Workshops (LCN Workshops), pp. 137–144. IEEE (2016)

    Google Scholar 

  10. Vecchio, M., Giaffreda, R., Marcelloni, F.: Adaptive lossless entropy compressors for tiny IoT devices. IEEE Trans. Wireless Commun. 13(2), 1088–1100 (2014)

    Article  Google Scholar 

  11. Nawandar, N.K., Satpute, V.R.: Energy efficient quality tunable CORDIC for DSP applications on battery operated portable devices. J. Circuits Syst. Comput. 27(04), 1850051 (2018)

    Article  Google Scholar 

  12. Nawandar, N.K., Satpute, V.R.: IoT based low cost and intelligent module for smart irrigation system. Comput. Electron. Agric. 162, 979–990 (2019)

    Article  Google Scholar 

  13. Volder, J.E.: The CORDIC trigonometric computing technique. IRE Trans. Electron. Comput. 3, 330–334 (1959)

    Article  Google Scholar 

  14. Aggarwal, S., Khare, K.: Hardware efficient architecture for generating Sine/Cosine waves. In: Proceedings of the 2012 25th International Conference on VLSI Design, pp. 57–61. IEEE Computer Society (2012)

    Google Scholar 

  15. Lee, M.W., Yoon, J.H., Park, J.: Reconfigurable CORDIC-based low-power DCT architecture based on data priority. IEEE Trans. Very Large Scale Integr. (VLSI) Syst. 22(5), 1060–1068 (2013)

    Google Scholar 

Download references

Acknowledgements

The work proposed in this paper has been supported by Visvesvaraya a Ph.D. scheme, Ministry of Electronics and Information Technology, Government of India.

Author information

Authors and Affiliations

  1. Department of ECE, VNIT Nagpur, Nagpur, India

    Neha K. Nawandar & Vishal R. Satpute

Authors
  1. Neha K. Nawandar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vishal R. Satpute
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Neha K. Nawandar .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Arunachal Pradesh, Jote, Arunachal Pradesh, India

    Deepak Gupta

  2. Department of Computer Science and Engineering, National Institute of Technology Arunachal Pradesh, Jote, Arunachal Pradesh, India

    Rajat Subhra Goswami

  3. Department of Computer Science and Engineering, National Institute of Technology Arunachal Pradesh, Jote, Arunachal Pradesh, India

    Subhasish Banerjee

  4. Department of Mathematics, Indian Institute of Technology Indore, Indore, Madhya Pradesh, India

    M. Tanveer

  5. Department of Electrical Engineering, Indian Institute of Technology Indore, Indore, Madhya Pradesh, India

    Ram Bilas Pachori

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

Nawandar, N.K., Satpute, V.R. (2022). Spatiotemporal Data Compression on IoT Devices in Smart Irrigation System. In: Gupta, D., Goswami, R.S., Banerjee, S., Tanveer, M., Pachori, R.B. (eds) Pattern Recognition and Data Analysis with Applications. Lecture Notes in Electrical Engineering, vol 888. Springer, Singapore. https://doi.org/10.1007/978-981-19-1520-8_66

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-1520-8_66

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1519-2

  • Online ISBN: 978-981-19-1520-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation