Abstract
“Alone we go faster, together we go further”. This popular quote characterizes exactly the vision on which our article focuses through our proposed collective intelligence system. It allows the different data holders of a country to share and store their large and structured data in a secure way thanks to the blockchain and the IPFS (Inter-Planetary File System). Then, such data are processed in a transparent and ethical way by a government entity. Indeed, to take advantage of all these data, we opt for a data integration approach based on ontology, which will enable to obtain rich and relevant information useful for the development of a smart city. In the literature, some works addressed the data sharing aspect based on blockchain and IPFS in specific domains, while others focused on the data analysis aspect. Our work differs in that it combines all these aspects and extends to several fields in order to achieve a common intelligence serving all dimensions of the smart city.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ma, Y., Li, G., Xie, H., Zhang, H.: City Profile: using smart data to create digital urban spaces. ISPRS Ann. Photogram. Remote Sens. Spatial Inf. Sci., 75–82 (2018)
Batty, M.: The New Science of Cities. The MIT Press, London (2013)
Anthopoulos, L.: Understanding the smart city domain: a literature review. Public Adm. Inf. Technol. 8, 9–21 (2015). https://doi.org/10.1007/978-3-319-03167-5_2
Silva, B.N., Khan, M., Han, K.: Towards sustainable smart cities: a review of trends, architectures, components, and open challenges in smart cities. Sustain. Cities Soc. 38, 697–713 (2018)
Camero, A., Alba, E.: Smart city and information technology: a review. Cities 93, 84–94 (2019)
Lemieux, V.L.: Blockchain and distributed ledgers as trusted record-keeping systems: An archival theoretic evaluation framework. In: Future Technologies Conference (FTC), pp. 1–11, Vancouver (2017)
Alizadeh, M., Anderson, K., Schelén, O.: Efficient decentralized data storage based on public blockchain and IPFS. In: 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), IEEE, Gold Coast (2020)
McLean, S., Deane-Johns, S.: Demystifying blockchain and distributed ledger technology – hype or hero? Comput. Law Rev. Int. 17(4), 97–102 (2016). https://doi.org/10.9785/cri-2016-0402
Islam, M.R., Rahman, M.M., Mahmud, M., Rahman, M.A., Mohamad, M.H.S., Embong, A.H.: A review on blockchain security issues and challenges. In: 2021 IEEE 12th Control and System Graduate Research Colloquium (ICSGRC), IEEE, Shah Alam (2021)
Cong, L.W., He, Z.: Blockchain disruption and smart contracts. Rev. Financ. Stud. 32(5), 1754–1797 (2019)
Kumar, S., Bharti, A.K., Amin, R.: Decentralized secure storage of medical records using Blockchain and IPFS: a comparative analysis with future directions. Secur. Priv. 4(5) (2021). https://doi.org/10.1002/spy2.162
Souza, J.T., Francisco, A.C., Piekarski, C.M., Prado, G.F.: Data mining and machine learning to promote smart cities: a systematic review from 2000 to 2018. Sustainability 11(4), 1077 (2019)
Nguyen, D.C., et al.: Enabling AI in future wireless networks: a data life cycle perspective. IEEE Commun. Surv. Tutorials 23(1), 553–595 (2021)
Hassan, M., Chen, J., Zhu, C., Zukaib, U.: Adoption of blockchain-based artificial intelligence in healthcare. In: 2022 5th International Conference on Artificial Intelligence and Big Data (ICAIBD), IEEE, Chengdu (2022)
Al Asad, N., Elahi, M.T., Al Hassan A., Yousuf, M.A.: Permission-based blockchain with proof of authority for secured healthcare data sharing. In: 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT), IEEE, Dhaka (2020)
Bhattacharya, P., Tanwar, S., Bodkhe, U., Tyagi, S., Kumar, N.: BinDaaS: blockchain-based deep-learning as-a-service in healthcare 4.0 applications. IEEE Trans. Network Sci. Eng. 8(2), 1242–1255 (2021). https://doi.org/10.1109/TNSE.2019.2961932
Makina, H., Ben Letaifa, A., Rachedi, A.: Leveraging edge computing, blockchain and IPFS for addressing ehealth records challenges. In: 2022 15th International Conference on Security of Information and Networks (SIN), IEEE, Sousse (2022)
Nyaletey, E., Parizi, R.M., Zhang, Q., Choo, K.: BlockIPFS- Blockchain-enabled interplanetary file system for forensic and trusted data traceability. In: 2nd IEEE International Conference on Blockchain (Blockchain), IEEE, Atlanta (2019)
Hasan, H.R., Salah, K., Yaqoob, I., Jayaraman, R., Pesic, S., Omar, M.: Trustworthy IoT data streaming using blockchain and IPFS. IEEE Access 10, 17707–17721 (2022)
Alamri, B., Javed, I.T., Margaria, T.: A GDPR-compliant framework for IoT-based personal health records using blockchain. In: 2021 11th IFIP International Conference on New Technologies, Mobility and Security (NTMS), IEEE, Paris (2021)
Vitor, G., Rito, P., Sargento, S.: Smart city data platform for real-time processing and data sharing. In: 2021 IEEE Symposium on Computers and Communications (ISCC), IEEE, Athens (2021)
Saha, S., Usman, Z., Jones, S., Kshirsagar, R., Li, W.: Towards a formal ontology to support interoperability across multiple product lifecycle domains. In: 2017 IEEE 11th International Conference on Semantic Computing (ICSC), IEEE, San Diego (2017)
Adel, E., Barakat, S., Elmogy, M.: Distributed electronic health records semantic interoperability based on a fuzzy ontology architecture. In: 2019 14th International Conference on Computer Engineering and Systems (ICCES), IEEE, Cairo (2019)
Alkhamisi, A.O., Saleh, M.: Ontology opportunities and challenges: discussions from semantic data integration perspectives. In: 2020 6th Conference on Data Science and Machine Learning Applications (CDMA), IEEE, Riyadh (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Adje, K.D.C., Habachi, O., Letaifa, A.B., Haddad, M. (2024). Smart City Development Through Collective Intelligence Based on Blockchain-IPFS-Data Analytics. In: Habachi, O., Chalhoub, G., Elbiaze, H., Sabir, E. (eds) Ubiquitous Networking. UNet 2023. Lecture Notes in Computer Science, vol 14757. Springer, Cham. https://doi.org/10.1007/978-3-031-62488-9_3
Download citation
DOI: https://doi.org/10.1007/978-3-031-62488-9_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-62487-2
Online ISBN: 978-3-031-62488-9
eBook Packages: Computer ScienceComputer Science (R0)