Skip to main content
Springer Nature Link
Log in

Sana Solo: An Intelligent Approach to Measure Soil Fertility

  • Conference paper
  • First Online:
Internet of Things. Advances in Information and Communication Technology (IFIPIoT 2023)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 683))

Included in the following conference series:

  • 571 Accesses

Abstract

Worm castings (Worm Excretion) are one the richest natural fertilizers on earth, making earthworms a very important and applicable soil health indicator. According to an article published in the Polish journal of Environmental studies, the most important chemical components of worm castings are pH, total organic carbon (TOC), total nitrogen (N), plant available phosphorus (P), plant available potassium (K), and calcium water soluble (Ca). These chemical components of worm castings, paired with soil temperature, humidity and electric conductivity, are all measurable values that can indicate the overall health and fertility of soil. Furthermore, these physical-chemical properties can also be measured and analyzed to estimate worm populations in soil, making traditional manual extraction techniques obsolete. The proposed project, Sana Solo, is a device that uses machine learning to estimate worm populations based on the quantities of the physical-chemical properties listed above. Being able to estimate earthworm populations in a timely manner, without the use of extraction techniques, can be used in farms and gardens to evaluate soil fertility.

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Rachakonda, L.: ETS: a smart and enhanced topsoil health monitoring and control system at edge using IoT. In 2022 IEEE International Symposium on Smart Electronic Systems (iSES), Warangal, India, pp. 689-693 (2022). https://doi.org/10.1109/iSES54909.2022.00153.

  2. Gregory, A.S., et al.: A review of the impacts of degradation threats on soil properties in the UK. Soil Use Manag. 31(Suppl. 1), 1–15 (2015). Epub 12 October 2015. PMID: 27667890; PMCID: PMC5014291. https://doi.org/10.1111/sum.12212

  3. Liu, H., Li, B., Ren, T.: Soil profile characteristics of high-productivity alluvial cambisols in the North China Plain. J. Integr. Agric. 14(4), 765–773 (2015). ISSN 2095-3119, https://doi.org/10.1016/S2095-3119(14)60789-9

  4. Dede, S., Thomas, W.: The Causes and Effects of Soil Erosion, and How to Prevent It. World Resources Institute, February 2000. https://www.wri.org/insights/causes-and-effects-soil-erosion-and-how-prevent-it#:~:text=A%20report%20from%20the%20Intergovernmental,times%20quicker%20than%20it’s%20forming

  5. Martina, S., et al.: A linkage between the biophysical and the economic: assessing the global market impacts of soil erosion. Land Use Policy 86, 299–312 (2019). ISSN 0264–8377, https://doi.org/10.1016/j.landusepol.2019.05.014

  6. Strutt, A.: Trade Liberalisation and Soil Degradation in Indonesia. Indonesia in a Reforming World Economy: Effects on Agriculture, Trade and the Environment, edited by Kym Anderson et al., pp. 40–60. University of Adelaide Press. JSTOR (2009). http://www.jstor.org/stable/10.20851/j.ctt1sq5w4j.10 Accessed 21 June 2023

  7. Möller, A., Ranke, U.: Estimation of the on-farm-costs of soil erosion in Sleman, Indonesia. WIT Trans. Ecol. Environ. 89, 43–52 (2006)

    Google Scholar 

  8. Shepard, K.C.: Oklahoma Farm Report. https://www.oklahomafarmreport.com/okfr/2023/04/. Accessed May 2023

  9. Panagos, P., Standardi, G., Borrelli, P., Lugato, E., Montanarella, L., Bosello, F.: Cost of agricultural productivity loss due to soil erosion in the European Union: from direct cost evaluation approaches to the use of macroeconomic models. Land Degrad. Dev. 29, 471–484 (2018). https://doi.org/10.1002/ldr.2879

    Article  Google Scholar 

  10. Third World Network Berhad. https://twn.my/title/land-ch.htm#:~:text=Its%20shocking%20conclusion%20was%20that,losses%20resulting%20from%20land%20degradation

  11. Kumar, P., Bhagat, K., Lata, K., Jhingran, S.: Crop recommendation using machine learning algorithms. In: International Conference on Disruptive Technologies (ICDT), Greater Noida, India, pp. 100–103 (2023). https://doi.org/10.1109/ICDT57929.2023.10151325

  12. Saha, P., Kumar, V., Kathuria, S., Gehlot, A., Pachouri, V., Duggal, A.S.: Precision agriculture using Internet of Things and Wireless Sensor Networks. In: International Conference on Disruptive Technologies (ICDT), Greater Noida, India, pp. 519–522 (2023). https://doi.org/10.1109/ICDT57929.2023.10150678

  13. Prabha, C., Pathak, A.: Enabling technologies in smart agriculture: a way forward towards future fields. In: International Conference on Advancement in Computation and Computer Technologies (InCACCT), Gharuan, India, pp. 821–826 (2023). https://doi.org/10.1109/InCACCT57535.2023.10141722

  14. Kumar, A., Savaridassan, P.: Monitoring and accelerating plant growth using IoT and Hydroponics. In: International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, pp. 1–6 (2023). https://doi.org/10.1109/ICCCI56745.2023.10128383

  15. Fleming, K., Gardner, A., Nagel, P., Miao, Y., Mizuta, K.: Hyperspectral sensing for soil health. In: IEEE Conference on Technologies for Sustainability (SusTech), Portland, OR, USA, pp. 1–5 (2023). https://doi.org/10.1109/SusTech57309.2023.10129629

  16. Irene Monica, N., Pooja, S.R., Rithiga, S., Madhumathi, R.: Soil NPK prediction using enhanced genetic algorithm. In: 9th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, pp. 2014–2018 (2023). https://doi.org/10.1109/ICACCS57279.2023.10113121

  17. Anuradha, B., Pradeep, R., Ahino, E., Dhanabal, A., Gokul, R.J., Lingeshwaran, S.: Vertical farming algorithm using hydroponics for smart agriculture. In: International Conference on Intelligent Systems for Communication, IoT and Security (ICISCoIS), Coimbatore, India, pp. 432–437 (2023). https://doi.org/10.1109/ICISCoIS56541.2023.10100527

  18. Rohini, V., Meghana, K., Sowmya, R.K., Krishna, K.S., Srikrishna, B.: Application of SMAP images in predicting Crops by using Decision Tree and Random Forest. In: International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF), Chennai, India, pp. 1–6 (2023). https://doi.org/10.1109/ICECONF57129.2023.10083570

  19. Verma, M., Kumar, A., Garg, M., Juneja, S.: Environment quality assessment web application. In: International Conference on Artificial Intelligence and Smart Communication (AISC), Greater Noida, India, pp. 1339–1342 (2023). https://doi.org/10.1109/AISC56616.2023.10085252

  20. Bhowmik, A., Sannigrahi, M., Dutta, P.K., Bandyopadhyay, S.: Using edge computing framework with the Internet of Things for intelligent vertical gardening. In: 1st International Conference on Advanced Innovations in Smart Cities (ICAISC), Jeddah, Saudi Arabia, pp. 1–6 (2023). https://doi.org/10.1109/ICAISC56366.2023.10085507

  21. Nehra, V., Sharma, M., Sharma, V.: IoT based smart plant monitoring system. In: 13th International Conference on Cloud Computing, Data Science and Engineering (Confluence), Noida, India, pp. 60–65 (2023). https://doi.org/10.1109/Confluence56041.2023.10048792

  22. Pallavi, C.V., Usha, S.: IoT based site specific nutrient management system for soil health monitoring. In: International Conference on Smart and Sustainable Technologies in Energy and Power Sectors (SSTEPS), Mahendragarh, India, pp. 166–170 (2022). https://doi.org/10.1109/SSTEPS57475.2022.00050

  23. Sui, X., Lin, C., Zhou, S.: Spatial decision analysis on soil erosion control measures research based on GIS: taking Changting country as an example. In: Third World Congress on Software Engineering, Wuhan, China, pp. 119–122 (2012). https://doi.org/10.1109/WCSE.2012.29

  24. Naik, T.R., et al.: Environmental testing methodology for real-time soil health monitoring system. In: IEEE Applied Sensing Conference (APSCON), Bengaluru, India, pp. 1–3 (2023). https://doi.org/10.1109/APSCON56343.2023.10101082

  25. Microbiometer. https://microbiometer.com/. Accessed March 2023

  26. Weyers, S.L., Schomberg, H.H., Hendrix, P.F., Spokas, K.A., Endale, D.M.: Construction of an electrical device for sampling earthworm populations in the field. Appl. Eng. Agric. 24(3), 391–397 (2008). https://doi.org/10.13031/2013.24492

  27. Kempson Extractor. https://www.ecotech.de/en/product/kempson_extractor_1. Accessed May 2023

  28. Ismayilov, A., Feyziyev, F., Elton, M., Maharram, B.: Soil organic carbon prediction by Vis-NIR spectroscopy: case study the Kur-Aras Plain, Azerbaijan. Commun. Soil Sci. Plant Anal. 51(6), 726–734 (2020)

    Google Scholar 

  29. Tauro, T.P., Mtambanengwe, F., Mpepereki, S., Mapfumo, P.: Soil macrofauna response to integrated soil fertility management under maize monocropping in Zimbabwe. Heliyon 7(12), e08567 (2021). PMID: 34917826; PMCID: PMC8666646. https://doi.org/10.1016/j.heliyon.2021.e08567

  30. Adomako, M.O., Xue, W., Roiloa, S., Zhang, Q., Du, D.L., Yu, F.H.: Earthworms modulate impacts of soil heterogeneity on plant growth at different spatial scales. Front Plant Sci. 23(12), 735495 (2021). PMID: 35003149; PMCID: PMC8732864. https://doi.org/10.3389/fpls.2021.735495

  31. Huang, M., et al.: Rice yield and the fate of fertilizer nitrogen as affected by addition of earthworm casts collected from oilseed rape fields: a pot experiment. PLoS ONE 11, e0167152 (2021). https://doi.org/10.1371/journal.pone.0167152

  32. Rachakonda, L., Bapatla, A.K., Mohanty, S.P., et al.: BACTmobile: a smart blood alcohol concentration tracking mechanism for smart vehicles in healthcare CPS framework. SN Comput. Sci. 3, 236 (2022). https://doi.org/10.1007/s42979-022-01142-9

  33. Rachakonda, L.: Agri-Aid: an automated and continuous farmer health monitoring system using IoMT. In: Camarinha-Matos, L.M., Ribeiro, L., Strous, L. (eds.) Internet of Things. IoT Through a Multi-disciplinary Perspective. IFIPIoT 2022. IFIP Advances in Information and Communication Technology, vol. 665. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-18872-54

Download references

Acknowledgements

This version of the project is funded by the College of Arts and Sciences in the University of North Carolina Wilmington.

Author information

Authors and Affiliations

  1. Department of Computer Science, University of North Carolina Wilmington, Wilmington, USA

    Laavanya Rachakonda & Samuel Stasiewicz

Authors
  1. Laavanya Rachakonda
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Samuel Stasiewicz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Laavanya Rachakonda .

Editor information

Editors and Affiliations

  1. Khalifa University, Abu Dhabi, United Arab Emirates

    Deepak Puthal

  2. University of North Texas, Denton, TX, USA

    Saraju Mohanty

  3. University of Missouri at Kansas City, Kansas City, MO, USA

    Baek-Young Choi

Rights and permissions

Reprints and permissions

Copyright information

© 2024 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Rachakonda, L., Stasiewicz, S. (2024). Sana Solo: An Intelligent Approach to Measure Soil Fertility. In: Puthal, D., Mohanty, S., Choi, BY. (eds) Internet of Things. Advances in Information and Communication Technology. IFIPIoT 2023. IFIP Advances in Information and Communication Technology, vol 683. Springer, Cham. https://doi.org/10.1007/978-3-031-45878-1_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-45878-1_27

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-45877-4

  • Online ISBN: 978-3-031-45878-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships