Skip to main content
SpringerLink
Log in

IoT and artificial intelligence–based fuzzy-integral N-transform for sustainable groundwater management

  • Original Paper
  • Published:
Applied Geomatics Aims and scope Submit manuscript

Abstract

Fuzzy integral transforms are simpler and the most popular mathematical methods to solve differential and partial equations as well as integral equations. A lesser-known data fusion approach, the fuzzy integral, has been applied in many fuzzy applications, and a comprehensive body of sound mathematical theory is presented alongside it. In this study, a new fuzzy transformation derived from the fuzzy Laplace transform, but more broadened in terms of the center, was shown, and the proposed first- and second-degree transformation and third-order fuzzy derivative formula are discovered. A general formula of nth-order fuzzy derivative e(FNT) is obtained using highly generalized H-differentiability notions. The Internet of Things (IoT) global advancement has improved the tradition of data collection for groundwater resource management. Additionally, information about changes in groundwater resources along with their accessibility is crucial for effective data-driven sustainable groundwater management. In this research work, sustainable groundwater management can be implemented using IoT and artificial intelligence (AI). Finally, a real-world example (liquid tank system) is illustrated to show the effectiveness of this fuzzy N-transform and applied for enhanced sand-dune image detection. From the results, it can be foreseen that the proposed method is exclusively suitable for sustainable groundwater management.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

Based on the request, authors can provide.

References

  • Abbas ST, Alkiffai AN, Albukhuta AN (2021) Solving a circuit system using fuzzy Aboodh transform. Turk J Comput Math Edu 12(12):3317–3323

    Google Scholar 

  • Bagnold RA (2012) The physics of blown sand and desert dunes. Courier Corporation

  • Fadhil AM (2009) Land degradation detection using geo-information technology for some sites in Iraq. J Al-Nahrain Univ Sci 12(3):94–108. https://doi.org/10.22401/JNUS.12.3.13

    Article  Google Scholar 

  • Haydar AK, Hassan RH (2016) Generalization of fuzzy Laplace transforms of fuzzy fractional derivatives about the general fractional order. Mathematical Problems in Engineering, Hindawi 2016:1–13

  • Jassim SZ, Goff JC (2006) Geology of Iraq. DOLIN, sro, distributed by Geological Society of London 8(5)

  • Lee M, Yeh C (2009) Applying remote sensing techniques to monitor shifting wetland vegetation: a case study of Danshui River estuary mangrove communities Taiwan. EcolEng 35:487–496. https://doi.org/10.1016/j.ecoleng.2008.01.007(Accessedon8/6/2020)

    Article  Google Scholar 

  • Levin N, Ben-Dor E (2004) Monitoring sand dune stabilization along the coastal dunes of Ashdod-Nizanim, Israel, 1945–1999. J Arid Environ 58(3):335–355. https://doi.org/10.1016/j.jaridenv.2003.08.007

    Article  Google Scholar 

  • Li X, Chen Y, Liu X, Xu X, Chen G (2017) Experiences and issues of using cellular automata for assisting urban and regional planning in China. Int J Geogr Inf Sci 31:1606–1629. https://doi.org/10.1080/13658816.2017.1301457(Accessedon8/6/2020)

    Article  Google Scholar 

  • Mandhare RA, Upadhyay P, Gupta S (2013) Pixel-level image fusion using Brovey transform and wavelet transform. Int J Adv Res Electr Electron Instrum Eng (IJAREEIE) 2(6):2690–2695

    Google Scholar 

  • Mondini G (2016) Integrated assessment for the management of new social challenges. Valori e Valutazioni 17:15–18

    Google Scholar 

  • Moradi S, Yousefi H, Noorollahi Y, Rosso D (2020) Multi-criteria decision support system for wind farm site selection and sensitivity analysis: case study of Alborz Province Iran. Energ Strat Rev 29:100478

    Article  Google Scholar 

  • Padwick C, Deskevick M, Pacifici S, Smallwood S (2010) Worldview-2 Pan-sharpening. ASPRS 2010 Annual Conference, San Diego

    Google Scholar 

  • Puri ML and Ralescu D (1983) Differential for fuzzy function. J Math AnalAppl

  • Sleibi and Alkiffai (2020) AN Solving ordinary differental equations using fuzzy transformation. Msc. Theses, Kufa University, Thesis Publication

  • Xiong Z, Guo Q, Liu M, Li A (2021) Pan-sharpening based on panchromatic colorization using WorldView-2. IEEE Access 9:115523–115534

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Computer Science and Mathematics, Kufa University, Kufa, Iraq

    Shaymaa Maki Kadham

  2. Department of English, College of Arts, Imam Ja’afer Alsadiq University, Salah-Aldin, Iraq

    Mohammed Ahmed Mustafa & Nisreen Khalid Abbass

  3. Gobi Arts & Science College (Autonomous), Gobichettipalayam, Tamilnadu, India

    Sathishkumar Karupusamy

Authors
  1. Shaymaa Maki Kadham
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohammed Ahmed Mustafa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nisreen Khalid Abbass
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sathishkumar Karupusamy
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

There is no authorship contribution.

Corresponding author

Correspondence to Nisreen Khalid Abbass.

Ethics declarations

Ethics approval and consent to participate

No participation of humans takes place in this implementation process.

Human and animal rights

No violation of human and animal rights is involved.

Conflict of interest

The authors declare no competing interests.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kadham, S.M., Mustafa, M.A., Abbass, N.K. et al. IoT and artificial intelligence–based fuzzy-integral N-transform for sustainable groundwater management. Appl Geomat 16, 1–8 (2024). https://doi.org/10.1007/s12518-022-00479-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12518-022-00479-3

Keywords

Search

Navigation