Skip to main content

Smart Farming: Securing Farmers Using Block Chain Technology and IOT

  • Chapter
  • First Online:
Blockchain Applications in IoT Ecosystem

Abstract

Agriculture is a fundamental human activity and has a lot of significance in India. The quality and quantity of production have reduced drastically due to diseases that occur and impact of bad weather. Though farmers are producing a good quantity of crops, middle men are stealing the benefits, and this leads to a curb in financial position to start the next crop. The utilization of blockchain technology in the agriculture sector can yield significant results by creation of direct markets to farmers as the blockchain tools are capable of tracing the origin of appetite as it facilitates the creation of reliable food supply chain and constructs faith among the consumer and farmer. It is the reliable process of storing data that smooth the progress of various aspects of the information motivated tools that makes smarter agriculture and this chapter examines the main areas of smart farming, insurance to farm, agricultural transactions and food supply chains. The blockchain technology is growing as an inclusive full-fledged technology which can be utilized in almost all smart applications established within future generation aspects of the Internet, and it is a flourishing technology where each and every node that is involved within the blockchain comprises a disseminated ledger that reinforces the protection and transparency aspects of data. Prohibited users will be restricted to perform any illegitimate transaction in the blockchain network as it has the potential to perform smart contract and consensus. Due to COVID-19 Indian government has taken decision to facilitate farmers to sell their crops anywhere in India and the Real time environment IoT can be combined with the block chain to get better the performance by eliminating the middleperson.

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

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
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. P.E. Colombo, E. Patterson, L.S. Elinder, A.K. Lindroos, U. Sonesson, N. Darmon, A. Parlesak, Optimizing School Food Supply: Integrating Environmental, Health, Economic, and Cultural Dimensions of Diet Sustainability with Linear Programming (2019)

    Google Scholar 

  2. R. Casado-Vara, J. Prieto, F. De la Prieta, J.M. Corchado, How blockchain improves the supply chain: Case study alimentary supply chain. Proc. Comput. Sci. 134, 393–398 (2018)

    Article  Google Scholar 

  3. W. Chen, G. Feng, C. Zhang, P. Liu, W. Ren, N. Cao, J. Ding, Development and application of big data platform for garlic industry chain. Comput. Mater. Contin. 58(1), 229–248 (2019)

    Article  Google Scholar 

  4. Y.C. Choe, J. Park, M. Chung, J. Moon, Effect of the food traceability system for building trust: Price premium and buying behavior. Inf. Syst. Front. 11(2), 167–179 (2009)

    Article  Google Scholar 

  5. T.K. Dasaklis, F. Casino, C. Patsakis, Defining granularity levels for supply chain traceability based on IoT and blockchain, in Proceedings of the International Conference on Omni-Layer Intelligent Systems, (ACM, 2019), pp. 184–190

    Google Scholar 

  6. P. Praveen, B. Rama, An optimized clustering method to create clusters efficiently. J. Mech. Contin Math Sci, ISSN (Online): 2454-7190. 15(1), 339–348 (2020, January). ISSN (Print): 0973-8975. https://doi.org/10.26782/jmcms.2020.01.00027

  7. B.F. Glunz, W.R. Pearson, A.F. Munoz, Method and system for creating 3D models from 2D data for building information modeling (BIM). U.S. Patent 9,817,922, issued 14 Nov 2017

    Google Scholar 

  8. B. Rama, P. Praveen, H. Sinha, T. Choudhury, A study on causal rule discovery with PC algorithm, in 2017 International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS), Dubai, (2017), pp. 616–621. https://doi.org/10.1109/ICTUS.2017.8286083

    Chapter  Google Scholar 

  9. A. Parikh, M.S. Raval, C. Parmar, S. Chaudhary, Disease detection and severity estimation in cotton plant from unconstrained images, in 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), (IEEE, 2016), pp. 594–601

    Google Scholar 

  10. A.A. Sarangdhar, V. Pawar, Machine learning regression technique for plant leaf disease detection and controlling using IoT, in 2017 International Conference of Electronics Communication and Aerospace Technology (ICECA), vol. 2, (IEEE, 2017), pp. 449–454

    Google Scholar 

  11. S. Patel, I.U. Sayyed, Impact of information technology in agriculture sector. Int. J. Food Agric. Vet. Sci. 4(2), 17–22 (2014)

    Google Scholar 

  12. V. Nedovic, A. Kalusevic, V. Manojlovic, S. Levic, B. Bugarski, An overview of encapsulation technologies for food applications. Proc. Food Sci. 1, 1806–1815 (2011)

    Article  Google Scholar 

  13. L. Ruiz-Garcia, L. Lunadei, The role of RFID in agriculture: Applications, limitations and challenges. Comput. Electron. Agric. 79(1), 42–50 (2011)

    Article  Google Scholar 

  14. D. Sharma, A.P. Bhondekar, A. Ojha, A.K. Shukla, C. Ghanshyam, A technical assessment of IoT for Indian agriculture sector. Int. J. Comput. Appl. (2016)

    Google Scholar 

  15. S. Han, H. Yang, Understanding adoption of intelligent personal assistants: A parasocial relationship perspective. Ind. Manag. Data Syst. 118(3), 618–636 (2018)

    Article  Google Scholar 

  16. G. Perboli, S. Musso, M. Rosano, Blockchain in logistics and supply chain: A lean approach for designing real-world use cases. IEEE Access 6, 62018–62028 (2018)

    Article  Google Scholar 

  17. T. Choudhury, A. Gupta, S. Pradhan, P. Kumar, Y.S. Rathore, Privacy and security of cloud-based Internet of Things (IoT), in 2017 3rd International Conference on Computational Intelligence and Networks (CINE), (2017), pp. 40–45

    Chapter  Google Scholar 

  18. Z. Ajazmoharkan, T. Choudhury, S.C. Gupta, G. Raj, Internet of Things and its applications in E-learning, in 3rd IEEE International Conference On, (2017). https://doi.org/10.1109/CIACT.2017.7977333

    Chapter  Google Scholar 

  19. A. Khanna, A. Sah, T. Choudhury, Intelligent mobile edge computing: A deep learning based approach. Commun. Comput. Inf. Sci. 1244(CCIS) (2020). https://doi.org/10.1007/978-981-15-6634-9_11

  20. A. Khanna, R. Goyal, M. Verma, D. Joshi, Intelligent traffic management system for smart cities. Commun. Comput. Inf. Sci. 958 (2019). https://doi.org/10.1007/978-981-13-3804-5_12

  21. M. Khurana, T. Choudhury, P. Malik, A review on network security challenges and the internet of things (IoT), in Proceedings of the 4th International Conference on Contemporary Computing and Informatics, IC3I, (2019). https://doi.org/10.1109/IC3I46837.2019.9055675

    Chapter  Google Scholar 

  22. A. Kamilaris, A. Fonts, F.X. Prenafeta-Boldύ, The Rise of the Blockchain Technology in Agriculture and Food Supply Chain (2018)

    Google Scholar 

  23. D. Ivanov, A. Tsipoulanidis, J. Schönberger, Operations and supply chain strategy, in Global Supply Chain and Operations Management, (Springer, Cham, 2019), pp. 81–110

    Chapter  Google Scholar 

  24. P. Praveen, C. Jayanth Babu, Big Data Clustering: Applying Conventional Data Mining Techniques in Big Data Environment. Innovations in Computer Science and Engineering, Lecture Notes in Networks and Systems, vol. 74 (Springer, Singapore, 2019), ISSN 2367-3370, https://doi.org/10.1007/978-981-13-7082-3_58

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Praveen, P., Shaik, M.A., Kumar, T.S., Choudhury, T. (2021). Smart Farming: Securing Farmers Using Block Chain Technology and IOT. In: Choudhury, T., Khanna, A., Toe, T.T., Khurana, M., Gia Nhu, N. (eds) Blockchain Applications in IoT Ecosystem. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-65691-1_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-65691-1_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65690-4

  • Online ISBN: 978-3-030-65691-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics