Journal of Platform Technology

ICT Platform Society (ICT플랫폼학회)
권호 표지
DOI QR코드

DOI QR Code

Designing a Blockchain-Enabled Smart Contract System for Monitoring Crop Environmental Data

작물 환경 데이터를 모니터링하기 위한 블록체인 기반 스마트 계약 시스템 설계

  • 정나영 (강남대학교 ICT 융합공학부) ;
  • 이현숙 (강남대학교 AI SW 융합 연구소) ;
  • 최웅 (강남대학교 컴퓨터공학부)
  • Received : 2025.03.22
  • Accepted : 2025.05.27
  • Published : 2025.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

This research integrates blockchain technology into agricultural systems to establish a transparent crop environment monitoring system. While smart agriculture systems have improved productivity and quality, centralized data management and mistrust can compromise data integrity. To address these issues, we propose a monitoring system using blockchain smart contracts to ensure transparency and integrity of crop environment data. Our approach leverages IoT devices to collect real-time data, securely recorded on a blockchain. This decentralized method enhances data security and ensures all stakeholders access trustworthy, tamper-proof data. By providing a reliable and transparent data management system, we aim to contribute to the digital transformation of agriculture, ultimately increasing the efficiency and reliability of the production process. The proposed system is expected to build confidence in crop data, streamline the production process, and enhance overall agricultural productivity and quality.

본 연구는 농업 시스템에 블록체인 기술을 통합하여 투명한 작물 환경 모니터링 시스템을 구축하는 것을 목표로 한다. 스마트 농업 시스템은 생산성과 품질을 향상시켰지만, 중앙집중식 데이터 관리와 신뢰 부족으로 인해 데이터 무결성이 손상될 수 있다. 이러한 문제를 해결하기 위해, 우리는 블록체인 스마트 계약을 이용한 모니터링 시스템을 제안하여 작물 환경 데이터의 투명성과 무결성을 보장하고자 한다. 이 접근 방식은 IoT 기기를 활용하여 실시간 데이터를 수집하고, 이를 안전하게 블록체인에 기록한다. 이러한 분산 방식은 데이터 보안을 강화하고, 모든 이해관계자가 신뢰할 수 있으며 위변조가 불가능한 데이터에 접근할 수 있도록 보장한다. 신뢰할 수 있고 투명한 데이터 관리 시스템을 제공함으로써 우리는 농업의 디지털 전환에 기여하고, 궁극적으로 생산 과정의 효율성과 신뢰성을 높이고자 한다. 제안된 시스템은 작물 데이터에 대한 신뢰를 구축하고, 생산 과정을 간소화하며, 전반적인 농업 생산성과 품질을 향상시킬 것으로 기대된다.

Keywords

References

  1. A. A. Aliyu and J. Liu, "Blockchain-based smart farm security framework for the Internet of Things," Sensors, vol. 23, no. 18, p. 7992, Sept. 2023. [Online]. Available: https://www.mdpi.com/1424-8220/23/18/7992 https://doi.org/10.3390/s23187992
  2. P. Praveen, M. A. Shaik, T. S. Kumar, and T. Choudhury, "Smart farming: Securing farmers using blockchain technology and IoT," Springer, vol. XX, no. XX, pp. 225–208, 2021. [Online]. Available: https://link.springer.com/chapter/10.1007/978-3-030-65691-1_15
  3. V. K. Maurya, P. Sachdev, N. S. Rathore, and L. Khan, "Adopting blockchain technology for smart farming and food security," IEEE Internet Things J., vol. 2020, pp. 390–395, Dec. 2019. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-7817-5_42
  4. M. Srikanth, R. N. V. J. Mohan, and M. C. Naik, "Blockchain-based consensus for a secure smart agriculture supply chain," Eur. Chem. Bull., vol. 2023, pp. 1–10, 2023. [Online]. Available: https://www.researchgate.net/publication/370776545
  5. M. U. Rahman, F. Baiardi, and L. Ricci, "Blockchain smart contract for scalable data sharing in IoT: A case study of smart agriculture," IEEE Internet Things J., vol. 2020, pp. 1–15, 2020. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9345874 https://doi.org/10.1109/GCAIoT51063.2020.9345874
  6. S. Stranieri, F. Riccardi, M. P. Meuwissen, and C. Soregaroli, "Exploring the impact of blockchain on the performance of agri-food supply chains," Food Control, vol. 119, p. 107495, May 2021. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0956713520304114 https://doi.org/10.1016/j.foodcont.2020.107495
  7. B. K. Mohanta, S. Chedup, and M. K. Dehury, "Secure trust model based on blockchain for Internet of Things Enable smart agriculture," in Proc. of the 19th OITS Int. Conf. Inf. Technol. (OCIT), Bhubaneswar, India, Nov. 2021, pp. 410–415. [Online]. Available: https://ieeexplore.ieee.org/document/9719520
  8. K. Dey and U. Shekhawat, "Blockchain for sustainable e-agriculture: Literature review, architecture for data management, and implications," J. Clean. Prod., vol. 294, p. 125264, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0959652621024707 1024707
  9. S. H. Awan, S. Ahmed, A. Nawaz, and S. Sulaiman, "Blockchain with IoT, an emergent routing scheme for smart agriculture," Int. J. Adv. Comput. Sci., vol. 2020, pp. 150–160, 2020. [Online]. Available: https://thesai.org/Publications/ViewPaper?Volume=11&Issue=4&Code=IJACSA&SerialNo=57 https://doi.org/10.14569/IJACSA.2020.0110457
  10. H. R. Hasan, A. Musamih, K. Salah, and R. Jayaraman, "Smart agriculture assurance: IoT and blockchain for trusted sustainable produce," Electron. Agric., vol. 2024, no. X, pp. 1–10, Jan. 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0168169924005751
  11. R. Chaganti, V. Varadarajan, V. S. Gorantla, and T. R. Gadekallu, "Blockchain-based cloudenabled security monitoring using Internet of Things in smart agriculture," Future Internet, vol. 14, no. 9, p. 250, 2022. [Online]. Available: https://www.mdpi.com/1999-5903/14/9/250 https://doi.org/10.3390/fi14090250
  12. W. Ren, X. Wan, and P. Gan, "A double-blockchain solution for agricultural sampled data security in Internet of Things network," Future Gener. Comput. Syst., vol. 2021, pp. 1–15, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0167739X20330697
  13. G. Drosatos and P. S. Efraimidis, "Blockchain-Based Traceability for Agricultural Products: A Systematic Literature Review," Appl. Sci., vol. 12, no. 16, p. 8061, Aug. 2022. [Online]. Available: https://www.mdpi.com/2077-0472/13/9/1757 https://doi.org/10.3390/agriculture13091757
  14. T. H. Pranto, A. A. Noman, and A. Mahmud, "Blockchain and smart contract for IoT-enabled smart agriculture," PeerJ Comput. Sci., vol. 2021, pp. 1–12, 2021. [Online]. Available: https://peerj.com/articles/cs-407.pdf https://doi.org/10.7717/peerj-cs.407
  15. F. Imtiaz, A. A. Farooque, G. S. Randhawa, and X. Wang, "An inclusive approach to crop soil moisture estimation: Leveraging satellite thermal infrared bands and vegetation indices on Google Earth Engine," Agric. Water Manag., vol. 280, pp. 1–15, Jan. 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0378377424005080 https://doi.org/10.1016/j.agwat.2024.109172
  16. Y. K. Kushwaha, R. K. Panigrahi, and A. Pandey, "Performance analysis of capacitive soil moisture, temperature sensors and their applications at farmer's field," Environ. Monit. Assess., vol. 196, no. 2, pp. 1–10, Feb. 2024. [Online]. Available: https://link.springer.com/article/10.1007/s10661-024-12946-y
  17. M. Muthmainnah, M. F. Mulyadi, and I. Tazi, "Development of an automated monitoring system for soil moisture and temperature in smart agriculture to enhance lettuce farming productivity based on IoT," Multidiscip. Sci. J., vol. 10, no. 1, pp. 45–53, Jan. 2024. [Online]. Available: https://malque.pub/ojs/index.php/msj/article/view/2342
  18. N. S. D. P. Korlepara, V. S. N. N. Raju, and P. Venugopal, "Real-time precision irrigation system for optimal crop yield and water conservation," in Proc. of the IOP Conf. Ser. Earth Environ. Sci., vol. 1375, p. 012019, Jan. 2024. [Online]. Available: https://iopscience.iop.org/article/10.1088/1755-1315/1375/1/012019
  19. V. Bawadkar, A. Verma, and A. Pawar, "Agritech Harmony: Real-time ESP32 automation and cloud computing for socially-informed crop suggestions," in Proc. of the 5th Int. Conf. Smart Agric. Technol., New York, NY, Feb. 2024, pp. 35–42. [Online]. Available: https://ieeexplore.ieee.org/document/10593303
  20. R. Kaur, R. K. Tiwari, and R. Maini, "Detection of soil moisture variations with fusion-based change detection algorithm for MODIS and SCATSAT-1 datasets," J. Indian Soc. Remote Sens., vol. 52, no. 1, pp. 23–36, Feb. 2024. [Online]. Available: https://link.springer.com/article/10.1007/s12524-024-01967-2