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Low Power Blockchain in Industry 4.0 Case Study: Water Management in Tunisia

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Abstract

Industry has undergone, during this decade, significant technological changes and improvements. The industrial sector is further moving towards IIoT (Industrial IoT) and Industry 4.0. Security and data reliability are IoT limitations that can be overcome using the Blockchain technology. In this work, the integration of blockchain in Industry 4.0 is presented. We develop a new platform based on artificial intelligence and smart contracts to monitor and track water consumption in Tunisia. A secure multiservice solution for water management is proposed. Water service providers and customers will be able to benefit from such services as consumption monitoring, traceability, security, water leak detection, visualization of water consumption and drinking water coverage. This approach allows reinforcing the trust and security among the different stakeholders.

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References

  1. Nakamoto, S. (2008). : Bitcoin a peer-to-peer electronic cash system. Decentralized Business Review : 21260.

  2. Monrat, A. F., Schelén, O., & Andersson, K. (2019). A survey of blockchain from the perspectives of applications, challenges, and opportunities. Ieee Access : Practical Innovations, Open Solutions, 7, 117134–117151.

    Article  Google Scholar 

  3. Nader, M., & Al-Jaroodi, J. (2019). : Applying blockchain in industry 4.0 applications, 2019 IEEE 9th annual computing and communication workshop and conference (CCWC). IEEE.

  4. Justin, S., Undralla, N., & Pillai, V. M. (2020). Supply chain transparency through blockchain-based traceability: An overview with demonstration. Computers& Industrial Engineering, 150, 106895.

    Article  Google Scholar 

  5. Zuo, Y. (2021). Making smart manufacturing smarter – a survey on blockchain technology in industry 4.0. Enterprise Information Systems, 15(10), 1323–1353. https://doi.org/10.1080/17517575.2020.185642

    Article  Google Scholar 

  6. Hakkak, S., Khan, W., & Gilkar, A. (2020). Industrial wastewater management using blockchain technology: Architecture, requirements, and future directions. IEEE Internet of Things Magazine, 3(2), 38–43.

    Article  Google Scholar 

  7. Gamage, H. T., Weerasinghe, D., & Dias, N. G. J. (2020). A survey on blockchain technology concepts, applications, and issues. SN Computer Science, 1(2), 1–15.

    Article  Google Scholar 

  8. Ezzeddini, L., Ktari, J., Zouaoui, I., Talha, A., Jarray, N., & Frikha, T. (2022, November). Blockchain for the electronic voting system: case study: student representative vote in Tunisian institute. In 2022 15th International Conference on Security of Information and Networks (SIN) (pp. 01–07). IEEE. https://doi.org/10.1109/SIN56466.2022.9970543

  9. Li, Y., Cao, B., Peng, M., Zhang, L., Zhang, L., Feng, D., & Yu, J. : Direct acyclic graph based blockchain for Internet of Things: Performance and security analysis, 2019, arXiv:1905. 10925. [Online]. Available: https://arxiv.org/abs/1905.10925

  10. Buterin, V. (2019). : Ethereum White paper A next generation smart contract & decentralized application platform, available https://blockchainlab.com/pdf/Ethereum_white_paper-a_next_generation_smart_contract_and_decentralized_application_platform-vitalik-buterin.pdf

  11. Androulaki, E., Barger, A., Bortnikov, V., Cachin, C., Christidis, K., De Caro, A., Enyeart, D., & Ferris, C. (2018). : Hyperledger fabric: A distributed operating system for permissioned blockchains, in Proc. 13th EuroSys Conf., Lisbon, Portugal, Apr. https://doi.org/10.1145/3190508.3190538

  12. Smart Quorum, & Accessed : May 23, 2019. [Online]. Available: https://smartquorum.com/download/WhitePaperSmartQuorum.pdf

  13. Rebello, G., Gabriel Antonio, F., Camilo, G., & Guimaraes, L. (2020). Security and performance analysis of quorum-based blockchain consensus protocols. Electrical Engineering Program, COPPE/UFRJ, Tech. Rep.

  14. Baliga, A., Subhod, I., Kamat, P., & Chatterjee, S. : Performance evaluation of the quorum blockchain platform, 2018, arXiv:1809.03421. Accessed: May 23, 2020. [Online]. Available: http://arxiv.org/abs/1809.03421

  15. Narbayeva, S., Bakibayev, T., Abeshev, K., Makarova, I., Shubenkova, K., & Pashkevich, A. (2020). : Blockchain technology on the way of autonomous vehicles development. Transportation research Proc., 44, 168–175.

  16. Yanovich, Y., Ivashchenko, I., Ostrovsky, A., Shevchenko, A., & Sidorov, A. : Exonum: Byzantine Fault Tolerant Protocol for Blockchains. Accessed: May 23, 2022. [Online]. Available: https://bitfury.com/content/downloads/wp_consensus_181227.pdf

  17. Valdeolmillos, D., Mezquita, Y., González-Briones, A., Prieto, J., & Corchado, J. M. (2019, June). Blockchain technology: A review of the current challenges of cryptocurrency. International Congress on Blockchain and Applications (pp. 153–160). Cham: Springer.

  18. Rehman, U., Salah, M. H., & Damiani, K. : Trust in blockchaincryptocurrency ecosystem. IEEE Transactions on Engineering Management, 67(4), 1196–1212.

  19. Yong, Y., & Wang, F. (2018). Blockchain and cryptocurrencies: Model, techniques, and applications. IEEE Transactions on Systems Man and Cybernetics: Systems, 48(9), 1421–1428.

    Article  Google Scholar 

  20. Martino, P., Wang, P., & Bellavitis, K. (2020). : An introduction to blockchain, cryptocurrency and initial coin offerings. In: New frontiers in entrepreneurial finance research. p. 181–206.

  21. Bermeo-Almeida, O., Cardenas-Rodriguez, M., Samaniego-Cobo, T., Ferruzola-Gómez, E., Cabezas, R., & Bazán-Vera, W. (2018, November). : Blockchain in agriculture: A systematic literature review. In International Conference on Technologies and Innovation (pp. 44–56). Springer, Cham.

  22. Demestichas, K., Peppes, K., & Alexakis, N. (2020). Blockchain in agriculture traceability systems: A review. Applied Sciences, 10(12), 4113.

    Article  Google Scholar 

  23. Sajja, G. S., & Rane, K. P. (2021). Phasinam k.: Towards applicability of blockchain in agriculture sector. Materials Today: Proceedings.

  24. Lin, J., Shen, Z., & Zhang, A. (2018). : Blockchain and IoT based food traceability for smart agriculture. In: Proceedings of the 3rd international conference on crowd science and engineering. p. 1–6.

  25. Al-Jaroodi, J., & Mohamed, N. (2019). Blockchain in industries: A survey. Ieee Access : Practical Innovations, Open Solutions, 7, 36500–36515.

    Article  Google Scholar 

  26. Perera, S., Nanayakkara, S., & Senaratne, M. N. N. : Blockchain technology: Is it hype or real in the construction industry?, Journal of Industrial Information Integration, 17, 100125.

  27. Leng, J., Ye, S., Zhou, M., et al. (2020). Blockchain-secured smart manufacturing in industry 4.0: A survey. IEEE Transactions on Systems Man and Cybernetics: Systems, 51(1), 237–252.

    Article  Google Scholar 

  28. Agbo, C., Mahmoud, Q. H., & Eklund, J. M. (2019, April). : Blockchain technology in healthcare: a systematic review. In Healthcare Vol. 7, No. 2, p. 56. MDPI.

  29. Ayesha, S., Qamar, U., & Khalid, A. (2019). Using blockchain for electronic health records. Ieee Access : Practical Innovations, Open Solutions, 7, 147782–147795.

    Article  Google Scholar 

  30. Attaran, M. (2022). Blockchain technology in healthcare Challenges and opportunities. International Journal of Healthcare Management, 15(1), 70–83.

    Article  Google Scholar 

  31. Paarssinen, M., Kotila, M., Rumin, R. C., et al. (2018). Is blockchain ready to revolutionize online advertising? IEEE access, 6, 54884–54899.

    Article  Google Scholar 

  32. Liu, D., Huang, C., & Ni, J. (2020). Blockchain-based smart advertising network with privacy-preserving accountability. IEEE Transactions on Network Science and Engineering, 8(3), 2118–2130.

    Article  Google Scholar 

  33. Sanka, A. I., Irfan, M., Huang, I., et al. (2021). A survey of breakthrough in blockchain technology: Adoptions, applications, challenges and future research. Computer Communications, 169, 179–201.

    Article  Google Scholar 

  34. Rauchs, M., Blandin, A., Bear, K., & McKeon, S. B. (2019). : 2nd global enterprise blockchain benchmarking study, Cambridge Centre for Alternative Finance Available at SSRN, URL https://ssrn.com/abstract=3461765

  35. https:// (2022). terradelyssa.fr/tracabilite/ Accessed: May 23.

  36. Abbas, Q. E., & Sung-Bong, J. (2019, February). : A survey of blockchain and its applications. In 2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) (pp. 001–003). IEEE.

  37. Bodkhe, U., Tanwar, S., Parekh, K., Khanpara, P., Tyagi, S., Kumar, N., & Alazab, M. : Blockchain for industry 4.0: A comprehensive review. Ieee Access : Practical Innovations, Open Solutions, 8, 79764–79800.

  38. Esmaeilian, B., Sarkis, J., Lewis, & Behdad, S. (2020). Blockchain for the future of sustainable supply chain management in industry 4.0. Resources. Conservation and Recycling, 163, 105064.

    Article  Google Scholar 

  39. Attaran, M., & Gunasekaran, A. (2019). Financial Services: The Largest Blockchain Market. Applications of Blockchain Technology in Business (pp. 21–26). Cham: Springer.

    Chapter  Google Scholar 

  40. Sandner, P. (2019). : Application of blockchain technology in the manufacturing industry. Frankfurt School BlockchainCenter, November 18. Retrieved April 12, from https://medium.com/@philippsandner/application-of-blockchain-technology-in-the-manufacturing-industryd03a8ed3ba5e

  41. Mao, M., & Hong, X. (2018). H.: Blockchain-based Technology for Industrial Control System CyperSecurity”. In 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018). Atlantis Press, p. 903–907.

  42. Gallo, I., Zamberletti, A., & Noce, L. (2015). : Robust Angle Invariant GAS Meter Reading. https://doi.org/10.1109/DICTA.2015.7371300

  43. Pahonțu, B., Arsene, D., Predescu, A., & Mocanu, M. : Application and challenges of Blockchain technology for real-time operation in a water distribution system. In 2020 24th International Conference on System Theory, Control and Computing (ICSTCC) (pp. 739–744). IEEE.

  44. Duc, H. N., Manh, T. N., Le, H. T., & Ferrero, F. : Research and Implement Embedded Artificial Intelligence in Low-Power Water Meter Reading Device. In 2021 International IEEE Conference on Advanced Technologies for Communications (ATC) (pp. 119–124).

  45. Suresh, M., Muthukumar, U., & Chandapillai, J. : A novel smart water-meter based on IoT and smartphone app for city distribution management, in 2017 IEEE Region 10 Symposium (TENSYMP), https://doi.org/10.1109/TENCONSpring.2017.8070088

  46. Yang, F., Jin, L., Lai, S., Gao, X., & Li, Z. : Fully Convolutional sequence Recognition Network for Water Meter Number Reading, in 2019 IEEE Access (volume 7, pages 11679–11687), https://doi.org/10.1109/ACCESS.2019.2891767

  47. Naim, A., Aaroud, A., Akodadi, K., & Hachimi, E. (2021). A fully AI-based system to automate water meter data collection in Morocco country. Array, 10, 100056.

    Article  Google Scholar 

  48. Pahonțu, B., Arsene, D., Predescu, A., & Mocanu, M. : Application and challenges of Blockchain technology for real-time operation in a water distribution system. In 2020, 24th International IEEE Conference on System Theory, Control and Computing (ICSTCC) (pp. 739–744).

  49. Bordel, B., Martin, D., Alcarria, R., & Robles, T. : A Blockchain-based Water Control System for the Automatic Management of Irrigation Communities, in 2019 IEEE International Conference on Consumer Electronics (ICCE).

  50. Enescu, F. M. (Feb. 2020). : Implementing Blockchain Technology in Irrigation Systems That Integrate Photovoltaic Energy Generation Systems. Sustainability, vol. 12, no. 4, p. 1540, https://doi.org/10.3390/su12041540

  51. Dogo, E., Salami, A., Nwulu, N., & Aigbavboa, C. (2019). : Blockchain and Internet of Things-Based Technologies for Intelligent Water Management System, pp. 129–150, https://doi.org/10.1007/978-3-030-04110-6_7

  52. “Goal 6 - Sustainable Development Knowledge Platform (accessed May 3,2022). ” https://sustainabledevelopment.un.org/sdg6

  53. Ktari, J., Frikha, T., Yousfi, M. A., Belghith, M. K., & Sanei, N. (2022). : Embedded Keccak implementation on FPGA, 2022 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS), pp. 01–05, https://doi.org/10.1109/DTS55284.2022.9809847

  54. Ktari, J., & Abid, M. (2009). A low Power Design Space Exploration Methodology based on high level models and confidence intervals. Journal of Low Power Electronics, 5(1), 17–30. https://doi.org/10.1166/jolpe.2009.1003

    Article  Google Scholar 

  55. Ktari, J., & Abid, M. : System level power and energy modeling for signal processing applications, 2007 2nd IEEE, International Design and Test Workshop, Egypt. pp. 218–221, https://doi.org/10.1109/IDT.2007.4437463

  56. Ktari, J., & Abid, M. : A Low Power Design Methodology Based on High Level Models. In International Conference on Embedded Systems & Applications, USA 2008, pp. 10–15. https://dblp.org/rec/conf/csreaESA/KtariA08.html

  57. Ktari, J., Frikha, T., Ben Amor, N., Louraidh, L., Elmannai, H., & Hamdi, M. : IoMT-Based Platform for E-Health Monitoring Based on the Blockchain. Electronics 2022, 11, 2314. https://doi.org/10.3390/electronics11152314

  58. Frikha, T., Chaari, A., Chaabane, F. (2021). : Healthcare and Fitness Data Management Using the IoT-Based Blockchain Platform, Journal of Healthcare Engineering, vol. Article ID 9978863, 12 pages, 2021. https://doi.org/10.1155/2021/9978863

  59. Allouche, M., Frikha, T., Mitrea, M., Memmi, G., & Chaabane, F. (2021). Lightweight Blockchain Processing. Case Study: Scanned document tracking on TezosBlockchain. Appl Sci, 11, 7169. https://doi.org/10.3390/app11157169

    Article  Google Scholar 

  60. Frikha, T., Chaabane, F., Aouinti, N., Cheikrouhou, O., Ben Amor, N., & Kerrouche, A. (2021). : Implementation of Blockchain Consensus Algorithm on Embedded Architecture, Security and Communication Networks, vol. Article ID 9918697, 11 pages, 2021. https://doi.org/10.1155/2021/9918697

  61. Zuo, L., He, P., Zhang, C., & Zhang, Z. (2020). : A robust approach to reading recognition of pointer meters based on improved mask-RCNN. https://doi.org/10.1016/j.neucom.2020.01.032. Neurocomputing.

  62. Affes, N., Ktari, J., Ben Amor, N., Frikha, T., & Hamam, H. (2022). : Real time detection and tracking in multi speakers video conferencing, ISDA : 22nd International Conference on Intelligent Systems Design and Applications. ISDA 2022, LNNS 646, pp. 1–11, 2023. https://doi.org/10.1007/978-3-031-27440-4_122

  63. Rpi3-tesseract (March 2022). https://github.com/thortex/rpi3-tesseract accessed at 11.

  64. Ktari, J., Frikha, T., Hamdi, M., Elmannai, H., & Hamam, H. : Lightweight AI Framework for Industry 4.0 Case Study: Water Meter Recognition. Big Data and Cognitive Computing, 6(3), 72. https://doi.org/10.3390/bdcc6030072

  65. https://colab. research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/train-yolov4 -tiny-object-detection-on-custom-data.ipynb, accessed at 11.

  66. Chaabane, F., Ktari, J., Frikha, T., & Hamam, H. (2022). Low power blockchained E-Vote platform for University Environment. Future Internet, 14(9), 269. https://doi.org/10.3390/fi14090269

    Article  Google Scholar 

  67. Han, Z., Li, S., & Liu, H. (2020). Composite learning sliding mode synchronization of chaotic fractional-order neural networks[J]. Journal of Advanced Research, 25, 87–96.

    Article  Google Scholar 

  68. Ha, S., Chen, L., & Liu, H. (2021). Command filtered adaptive neural network synchronization control of fractional-order chaotic systems subject to unknown dead zones. Journal of The Franklin Institution, 358(7), 3376–3402.

    Article  MathSciNet  Google Scholar 

  69. Frikha, T., Ben Amor, N., Diguet, J. P., et al. (2019). A novel Xilinx-based architecture for 3D-graphics. Multimed Tools Appl, 78, 14947–14970. https://doi.org/10.1007/s11042-018-6886-4

    Article  Google Scholar 

  70. Dhouioui, M., & Frikha, T. (2021). Design and implementation of a radar and camera-based obstacle classification system using machine-learning techniques. Journal of Real-Time Image Processing. https://doi.org/10.1007/s11554-021-01117-8

    Article  Google Scholar 

  71. Loukil, K., Khalfa, M., Jmal, M., Frikha, T., & Abid, M. (2017). Design and test of smart IP-camera within reconfigurable platform, 2017 2nd International Conference on Anti-Cyber Crimes (ICACC), pp. 25–29, https://doi.org/10.1109/Anti-Cybercrime.2017.7905257

  72. Taloba, A. I. (2022). An Artificial neural network mechanism for optimizing the Water treatment process and desalination process. Alexandria Engineering Journal, 61(12), 9287–9295.

    Article  Google Scholar 

  73. Sewisy, A., El-Aziz, A., Marghny, M., & Ahmed, I. (2014). Taloba “Fast efficient clustering algorithm for balanced data " Available at SSRN 2545138.

  74. Taloba, A. I., Adel, A., Sewisy, Yasser, A., & Dawood (2018). “Accuracy enhancement scaling factor of Viola-Jones using genetic algorithms.“ In 2018 14th International Computer Engineering Conference (ICENCO), pp. 209–212. IEEE.

  75. Frikha, T., Chaabane, F., Halima, R. B., et al. (2023). Embedded decision support platform based on multi-agent systems. Multimed Tools Appl. https://doi.org/10.1007/s11042-023-14843-x

    Article  Google Scholar 

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Acknowledgements

This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R125),Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

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This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R125), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

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Correspondence to Monia Hamdi.

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Frikha, T., Ktari, J., Amor, N.B. et al. Low Power Blockchain in Industry 4.0 Case Study: Water Management in Tunisia. J Sign Process Syst 96, 257–271 (2024). https://doi.org/10.1007/s11265-023-01880-w

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