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.
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References
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)
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)
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)
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)
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
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
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
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
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
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
S. Patel, I.U. Sayyed, Impact of information technology in agriculture sector. Int. J. Food Agric. Vet. Sci. 4(2), 17–22 (2014)
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)
L. Ruiz-Garcia, L. Lunadei, The role of RFID in agriculture: Applications, limitations and challenges. Comput. Electron. Agric. 79(1), 42–50 (2011)
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)
S. Han, H. Yang, Understanding adoption of intelligent personal assistants: A parasocial relationship perspective. Ind. Manag. Data Syst. 118(3), 618–636 (2018)
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)
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
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
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
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
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
A. Kamilaris, A. Fonts, F.X. Prenafeta-Boldύ, The Rise of the Blockchain Technology in Agriculture and Food Supply Chain (2018)
D. Ivanov, A. Tsipoulanidis, J. Schönberger, Operations and supply chain strategy, in Global Supply Chain and Operations Management, (Springer, Cham, 2019), pp. 81–110
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
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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
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