Skip to main content
SpringerLink
Log in

Predictive Analysis of Biomass with Green Mobile Cloud Computing for Environment Sustainability

  • Chapter
  • First Online:
Green Mobile Cloud Computing

Abstract

Biomass is an organic material that comes from plants and animal. It is the oldest form of retrieving energy from the dead remains of plants and animal. Since these remnants gets decomposed unless energy is retrieved. The energy retrieved or extracted by these leftovers is called biomass energy which is a renewable source of energy. In this article, it is tried to predict and classify the amount of energy produced by the biomass and the type of biomass and storing this data into the cloud (mobile) for analyzing and help the users to predict. Cloud platforms have been used to store information such as AWS. A small-scale test on some sample has also been performed. The key target of this chapter is to predict unknown data, categorize and analyze the different parameters of biomass such as amount of energy produced by the biomass, Carbon dioxide (CO2) produced by the biomass and also predicting these parameters according to the needs and storage of the gathered data into the mobile cloud. A proposed model of microbot will gather the required data from the point of source. The model to be deployed in the cloud and will not only help the users to determine the amount of energy they can extract from biomass but also aware them about the type of biomass. The conclusion of this work indicates that the biomass-based method assures alternatives for convenience and integrates mankind in addition to nature but is involved in augmentation to create a more aggressive dimension.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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. National Institute of Standards and Technology Special Publication 500-291 Natl. Inst. Stand. Technol. Spec. Publ. 500–291, 83 pages (2011)

    Google Scholar 

  2. Gong, C., Liu, J., Zhang, Q., Chen, H., Gong, Z.: The characteristics of cloud computing. In: 39th International Conference on Parallel Processing Workshops, pp. 275–279 (2010). https://doi.org/10.1109/ICPPW.2010.45

    Chapter  Google Scholar 

  3. Keahey, K., Figueiredo, R., Fortes, J., Freeman, T., Tsugawa, M.: Science clouds: early experiences in cloud computing for scientific applications. Cloud Comput. Appl. 2008, 825–830 (2008)

    Google Scholar 

  4. Kumar, R., Jain, K., Maharwal, H., Jain, N., Dadhich, A.: Apache Cloudstack: open source infrastructure as a service cloud computing platform. Proc. Int. J. Adv. Eng. Technol. Manag. Appl. Sci. 1(2), 111–116 (2014)

    Google Scholar 

  5. Li, W., Shao, H., Wang, S., Zhou, X., Wu, S.: A2CI: a cloud-based, service-oriented geospatial cyberinfrastructure to support atmospheric research. In: Vance, T.C., Merati, N., Yang, C., Yuan, M. (eds.) Cloud Computing in Ocean and Atmospheric Sciences, pp. 137–161 (2016)

    Chapter  Google Scholar 

  6. Liu, Y., Wei, X., Guo, X., Niu, D., Zhang, J., Gong, X., Jiang, Y.: The long-term effects of reforestation on soil microbial biomass carbon in sub-tropic severe red soil degradation areas. For. Ecol. Manag. 285, 77–84 (2012). https://doi.org/10.1016/j.foreco.2012.08.019

    Article  Google Scholar 

  7. Lobell, D.B., Thau, D., Seifert, C., Engle, E., Little, B.: A scalable satellite-based crop yield mapper. Remote Sens. Environ. 164, 324–333 (2015). https://doi.org/10.1016/j.rse.2015.04.021

    Article  Google Scholar 

  8. Ma, Y., Wu, H., Wang, L., Huang, B., Ranjan, R., Zomaya, A., Jie, W.: Remote sensing big data computing: challenges and opportunities. Futur. Gener. Comput. Syst. 51, 47–60 (2015). https://doi.org/10.1016/j.future.2014.10.029

    Article  Google Scholar 

  9. Okoro, S.U., Schickhoff, U., Bohner, J., Schneider, U.A.: A novel approach in monitoring land-cover change in the tropics: oil palm cultivation in the Niger Delta, Nigeria. Erde. 147, 40–52 (2016)

    Google Scholar 

  10. Padarian, J., Minasny, B., McBratney, A.B.: Using Google’s cloud-based platform for digital soil mapping. Comput. Geosci. 83, 80–88 (2015). https://doi.org/10.1016/j.cageo.2015.06.023

    Article  Google Scholar 

  11. Patel, N.N., Angiuli, E., Gamba, P., Gaughan, A., Lisini, G., Stevens, F.R., Tatem, A.J., Trianni, G.: Multitemporal settlement and population mapping from Landsat using Google Earth Engine. Int. J. Appl. Earth Obs. Geoinf. 35, 199–208 (2015). https://doi.org/10.1016/j.jag.2014.09.005

    Article  Google Scholar 

  12. Tan, X., Di, L., Deng, M., Fu, J., Shao, G., Gao, M., Sun, Z., Ye, X., Sha, Z., Jin, B.: Building an elastic parallel OGC web processing service on a cloud-based cluster: a case study of remote sensing data processing service. Sustainability. 7(10), 14245–14258 (2015). https://doi.org/10.3390/su71014245

    Article  Google Scholar 

  13. Khurrum, M., Bhutta, S., Omar, A., Yang, X.: Electronic waste: a growing concern in today’s environment. Econ. Res. Int. 2011., Article ID 474230, 8–20 (2011). https://doi.org/10.1155/2011/474230

    Article  Google Scholar 

  14. Perkins, D.N., Drisse, M.-N.B., Nxele, T., Sly, P.D.: E-waste: a global hazard. Ann. Glob. Health. 80(4), 286–295 (2014). ISSN 2214-9996. https://doi.org/10.1016/j.aogh.2014.10.001

    Article  Google Scholar 

  15. Popp, J., Kovács, S., Oláh, J., Divéki, Z., Balázs, E.: Bioeconomy: biomass and biomass-based energy supply and demand. New Biotechnol. 60, 76–84 (2021). ISSN 1871-6784. https://doi.org/10.1016/j.nbt.2020.10.004

    Article  Google Scholar 

  16. Amidon, T.E., Wood, C.D., Shupe, A.M., Wang, Y., Graves, M., Liu, S.: Biorefinery: conversion of woody biomass to chemicals, energy and materials. J. Biobaased Mater. Bioenergy. 2, 100–120 (2008). https://doi.org/10.1166/jbmb.2008

    Article  Google Scholar 

  17. Bartuska, A.: Why Biomass Is Important: The Role of the USDA Forest Service in Managing and Using Biomass for Energy and Other Uses. Speech Given at 25x25 Summit II, Washington, DC (2006). Last Accessed 17 July 2018

    Google Scholar 

  18. Chen, Q., McRoberts, R.E., Wang, C., Radtke, P.J.: Forest aboveground biomass mapping and estimation across multiple spatial scales using model-based inference. Remote Sens. Environ. 184, 350–360 (2016). https://doi.org/10.1016/j.rse.2016.07.023

    Article  Google Scholar 

  19. Dong, J., Xiao, X., Menarguez, M.A., Zhang, G., Qin, Y., Thau, D., Biradar, C., Moore, B.: Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine. Remote Sens. Environ. 185, 142–154 (2016). https://doi.org/10.1016/j.rse.2016.02.016

    Article  Google Scholar 

  20. Foody, G.M., Boyd, D.S., Cutler, M.E.J.: Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions. Remote Sens. Environ. 85, 463–474 (2003). https://doi.org/10.1016/S0034-4257(03)00039-7

    Article  Google Scholar 

  21. Goldblatt, R., You, W., Hanson, G., Khandelwal, A.K.: Detecting the boundaries of urban areas in India: a dataset for pixel-based image classification in Google Earth Engine. Remote Sens. 8, 634–642 (2016). https://doi.org/10.3390/rs8080634

    Article  Google Scholar 

  22. Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R.: Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017). https://doi.org/10.1016/j.rse.2017.06.031

    Article  Google Scholar 

  23. Houghton, R.A.: Aboveground forest biomass and the global carbon balance. Glob. Chang. Biol. 11(6), 945–958 (2005). https://doi.org/10.1111/j.1365-2486.2005.00955.x

    Article  Google Scholar 

  24. Houghton, R.A., Lawrence, K.T., Hackler, J.L., Brown, S.: The spatial distribution of forest biomass in the Brazilian Amazon: a comparison of estimates. Glob. Chang. Biol. 7, 731–746 (2001). https://doi.org/10.1046/j.1365-2486.2001.00426.x

    Article  Google Scholar 

  25. Lu, D., Chen, Q., Wang, G., Liu, L., Li, G., Moran, E.: A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems. Int. J. Digit. Earth. 9(1), 63–105 (2016). https://doi.org/10.1080/17538947.2014.990526

    Article  Google Scholar 

  26. Sudhakar Reddy, C., Jha, C., Diwakar, P., Dadhwal, V.: Nationwide classification of forest types of India using remote sensing and GIS. Environ. Monit. Assess. 187 (2015). https://doi.org/10.1007/s10661-015-4990-8

  27. Nathanson, J. A.: Solid-waste management. Encyclopedia Britannica. https://www.britannica.com/technology/solid-waste-management (2020). Last Accessed 8 Oct 2021

  28. New York State’s Solid Waste Program. https://www.dec.ny.gov/chemical/8732.html. Last Accessed 8 Oct 2021

  29. Yun, Y.: Alcohol Fuels: Current Status and Future Direction, Alcohol Fuels – Current Technologies and Future Prospect. IntechOpen (2020). https://doi.org/10.5772/intechopen.89788. Available on https://www.intechopen.com/books/alcohol-fuels-current-technologies-and-future-prospect/alcohol-fuels-current-status-and-future-direction

    Book  Google Scholar 

  30. Williams, C.A., Hasler, N., Gu, H., Zhou, Y.: Forest Carbon Stocks and Fluxes from the NFCMS. Conterminous USA, pp. 1990–2010, ORNL DAAC, Oak Ridge. (2020). https://doi.org/10.3334/ORNLDAAC/1829

  31. Schepaschenko, D., Shvidenko, A., Usoltsev, V., et al.: A dataset of forest biomass structure for Eurasia. Sci. Data. 4, 170070 (2017). https://doi.org/10.1038/sdata.2017.70

    Article  Google Scholar 

  32. Basics of Data Preprocessing, Basic Understandings and Techniques of Data Preprocessing. https://medium.com/easyread/basics-of-data-preprocessing-71c314bc7188#:~:text=What%20 are%20the%20Techniques%20Provided%20in% 20Data%20Preprocessing%3F,Transformati on%20Constructing%20data %20cube.%20...%20More%20items...%20. Last Accessed 8 Oct 2021

    Google Scholar 

  33. Splitting a Dataset into Train and Test Sets. https://www.baeldung.com/cs/train-test-datasets-ratio. Last Accessed 8 Oct 2021

  34. Galdi, P., Tagliaferri, R.: Data mining: accuracy and error measures for classification and prediction. In: Encyclopedia of Bioinformatics and Computational Biology, pp. 431–436. Academic (2019). ISBN 9780128114322. https://doi.org/10.1016/B978-0-12-809633-8.20474-3

    Chapter  Google Scholar 

  35. Hiloidhari, M., Das, D., Baruah, D.C.: Bioenergy potential from crop residue biomass in India. Renew. Sust. Energ. Rev. 32, 504–512 (2014)

    Article  Google Scholar 

  36. Berndes, G., Hoogwijk, M., van den Broek, R.: The contribution of biomass in the future global energy supply: a review of 17 studies. Biomass Bioenergy. 25(1), 1–28 (2003)

    Article  Google Scholar 

  37. About Amazon Web Services – Expedite Business Operations and improve agility through Amazon Web Services. https://www.kcsitglobal.com/solution/cloud/amazon-web-services. Last Accessed 23 Jan 2022

  38. Mendu, V., Tom, S., Elliott Campbell Jr., J., Stork, J., Jae, J., Crocker, M., Huber, G., DeBolt, S.: Global bioenergy potential from high-lignin agricultural residue. PNAS. 109(10), 4014–4019 (2012). https://doi.org/10.1073/pnas.1112757109

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science & Engineering, Haldia Institute of Technology, Haldia, West Bengal, India

    Santanu Koley & Pinaki Pratim Acharjya

  2. Department of Computer Science & Engineering, Budge Budge Institute of Technology, Kolkata, West Bengal, India

    Piyush Keshari

  3. Department of Computer Science, Mankar College, Mankar, Purba Bardhaman, West Bengal, India

    Kunal Kumar Mandal

Authors
  1. Santanu Koley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pinaki Pratim Acharjya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Piyush Keshari
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kunal Kumar Mandal
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Centre of Mobile Cloud Computing, Maulana Abul Kalam Azad University of Technology, West Bengal, Nadia, India

    Debashis De

  2. Department of Computer Science, Mahishadal Raj College Mahishadal, Purba Medinipur, West Bengal, India

    Anwesha Mukherjee

  3. Cloud Computing and Distributed Systems (CLOUDS) Laboratory School of Computing and Information Systems, The University of Melbourne, Parkville, VIC, Australia

    Rajkumar Buyya

Rights and permissions

Reprints and permissions

Copyright information

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

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Koley, S., Acharjya, P.P., Keshari, P., Mandal, K.K. (2022). Predictive Analysis of Biomass with Green Mobile Cloud Computing for Environment Sustainability. In: De, D., Mukherjee, A., Buyya, R. (eds) Green Mobile Cloud Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-08038-8_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-08038-8_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08037-1

  • Online ISBN: 978-3-031-08038-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation