Blockchain Papers

Zakariae Ismaili, Ali Younes, Abdel Ali Harchaoui, Monir EL Mounaoui

No abstract is available for this record.

Amin Khoshkenar, Hala Nassereddine

Smart Cities (SCs) leverage advanced technologies and data analytics to optimize infrastructure and services for economic and quality of life benefits. However, realizing the potential of SCs requires interoperability between different systems, which remains challenging due to fragmentation. Thus, unified architectures are needed to enable effective coordination through common languages and protocols. Digital Twin (DT) models, bidirectional virtual representations of physical assets, show immense promise for unifying SCs by integrating massive heterogeneous data streams. Although there have been numerous studies investigating unified models for SCs, in the context of DT, most studies narrowly focus on using DT for different systems within cities rather than citywide implementation. As a response, this study identified 34 recent papers investigating interoperability and unified models in SCs, out of which 19 papers were focused on developing unified models for SCs and 15 papers were focused on unified DT models in SCs. These 15 papers were systematically reviewed, identifying the key factors, benefits, and challenges of such models. To help city leaders and to make focused, context-aware decisions aligned to their objectives, whole factors were categorized into four groups, including relevance-based, influence-based, complexity-based, and risk-based. To guide future research, the study highlights edge computing and implementing blockchains as underrepresented areas within the realm of SCs.

Abhaar Gupta

This chapter discusses the growing challenges faced by cities as their population continues to grow and citizen services become more and more complex and interconnected. It argues that many of the inefficiencies and mistrust are not because of a lack of digitization of urban services, but because of fragmented data, agencies operating in silos, and a lack of transparency in government processes. With that in mind, the chapter introduces blockchain as a distributed ledger technology and a tool that governments can use to fundamentally redefine management of data, processes, and coordination across agencies while maintaining transparency. The chapter further dives into cases where blockchain has been used to manage public records, procurement, utilities, citizen participation, and resource management. It also discusses technical, legal, financial, and social limitations of the technology. The chapter concludes with an explanation of an implementation framework with a strong focus on long-term sustainability, inclusiveness, regulatory compatibility, and incremental adoption. The combination of these makes blockchain a strategic solution to reestablish accountability, transparency, and confidence in urban services instead of a panacea.

Shafiqul Hassan, Mohsin Dhali

The rapid expansion of fourth industrial revolution (4IR) technologies has intensified the expectation that artificial intelligence (AI), blockchain, the Internet of Things (IoT), big data analytics, and automation can accelerate the process of achieving the United Naitons Sustainable Development Goals (SDGs), particularly in developing nations. Whether these technologies live up to their expectation, however, depends not only on technological capability but also on the legal, regulatory, and institutional environment in which they operate. However, the governance of 4IR technologies has gained far less scholarly attention than their technological potential. The present study examines how legal frameworks, policy instruments, and governance arrangements influence the contribution of 4IR technologies to sustainable development in developing countries. Following the PRISMA 2020 guidelines, literature published between 2015 and 2025 was identified through searches of Web of Science, Scopus, Google Scholar, Pub Med, and arXiv. From 721 retrieved records, 50 peer reviewed studies met the eligibility criteria and were synthesised using a narrative approach. The analysis reveals three consistent patterns. First, legal authority is fragmented within and across jurisdictions. Second, policy commitments frequently outstrip implementation capacity, a performativity in which governments announce SDG ambitions without building the institutional means to deliver them. Third, governance is constrained by limited expertise, weak enforcement, and poor coordination between agencies. The review also identifies three important gaps in the literature: a predominant focus on artificial intelligence at the expense of other technologies, limited empirical testing of the links between fourth industrial revolution technologies and SDG outcomes, and minimal attention to how rules are enforced in practice. These finding suggest that the prime difficulty of harnessing 4IR technologies for sustainable development in developing nations are institutional rather than technological. Therefore, it is not only about advancing technological innovation but also strengthening regulatory coherence, governance capacity, and the effective implementation of legal frameworks to achieve SDGs in developing countries.

Authors unavailable

Smart cities are quickly becoming data-driven environments that are dependent on intelligent technologies to make cities efficient and their citizens happy. In this chapter, the author introduces a comprehensive concept of deep learning and blockchain that will be used to secure and improve multimodal smart city applications. It explores the heterogeneity issues of Internet of Multimedia Things (IoMT) data, such as security, privacy, and trust, and shows how deep learning can facilitate intelligent analysis by means of feature extraction, multimodal fusion, and real-time decision-making. Data integrity and transparency, as well as decentralized governance, are guaranteed by blockchain and secure access control and policy automation through smart contracts. It is also in this chapter that mechanisms of identity and trust management, secure data and model management, and privacy are discussed. Applied benefits are demonstrated by use cases in surveillance, transportation, and energy management, whereas challenges and future research discussions provide a basis for secure, resilient, and intelligent urban ecosystems.

Raj Kumar Goel, Shweta Vishnoi

Rapid urbanization is increasing pressure on infrastructure, natural resources, social well-being, and institutional capacity, while climate change, demographic shifts, migration, technological disruption, and geopolitical instability are further complicating paths to sustainable urban development. This study develops a conceptual, SDG-aligned framework to examine the interactions between six major global megatrends and their associated sub-trends, with a particular emphasis on their cascading effects, interdependencies, and impact on urban resilience. Drawing on existing scholarly and policy literature, this study synthesizes case-based evidence from diverse urban contexts to demonstrate how global trends translate into locally distinct sustainability challenges. Within this framework, the study proposes an Extended Composite Sustainability Index (ECSI) that conceptually integrates six interconnected dimensions namely urbanization, demographic shift, climate change, technological transformation, spatial change, and geopolitical instability to provide a multidimensional framework for assessing sustainable urban development. This framework conceptualizes resilience and SDG progress as outcomes of interactions between these dimensions, rather than as independent variables. The proposed ECSI and its associated formulations are presented as conceptual constructs. The analysis shows that technological innovations, such as artificial intelligence, big data, blockchain, and the Internet of Things, can contribute to resource efficiency, safety, and inclusive urban development, but without proper governance and institutional safeguards, they can also reinforce privileged and digital inequalities. Overall, this study highlights the need for an integrated assessment approach that simultaneously evaluates sustainability dimensions, while also providing a conceptual basis for future empirical calibration, sensitivity testing, and validation using real-world urban datasets.

Mrs. Meghana Dinesh Palkar

The rapid growth of urbanization in India has significantly increased the demand for efficient urban infrastructure, intelligent public services, and sustainable resource management. Cities are facing numerous challenges, including traffic congestion, rising energy consumption, water scarcity, environmental pollution, inefficient waste management, and increasing pressure on healthcare and public safety systems. Conventional urban management techniques are often inadequate for handling these complex and interconnected challenges because they rely heavily on manual monitoring and reactive decision-making. The Internet of Things (IoT), combined with smart electronic systems, has emerged as a transformative technology capable of addressing these issues by enabling real-time monitoring, automation, and intelligent decision-making. IoT-based smart electronics integrate sensors, embedded processors, wireless communication technologies, cloud computing, artificial intelligence, and data analytics to create interconnected systems that continuously collect, process, and exchange information. These technologies enable city administrators to monitor infrastructure, optimize resource utilization, improve service delivery, and enhance the quality of life for citizens. In India, the Smart Cities Mission has accelerated the adoption of IoT-enabled technologies across various sectors, including transportation, energy management, water distribution, environmental monitoring, healthcare, public safety, and digital governance. Smart electronics have enabled intelligent traffic control systems, smart street lighting, smart electricity meters, connected surveillance systems, and automated waste management solutions, thereby improving operational efficiency and reducing environmental impact. Despite significant progress, several challenges remain, including cybersecurity threats, interoperability issues, data privacy concerns, high deployment costs, and the need for standardized communication protocols. This paper presents a comprehensive discussion on the role of IoT-based smart electronics in building smart cities in India. It examines the technological architecture, key applications, implementation challenges, and future opportunities associated with IoT-driven urban development. The paper concludes that the integration of IoT with emerging technologies such as artificial intelligence, edge computing, fifth-generation (5G) communication, blockchain, and digital twin technologies will play a crucial role in achieving sustainable, resilient, and citizen-centric smart cities in India.

Cynthia Jayapal

No abstract is available for this record.

Jaume Martin Bosch, Marco Combetto, Luca Tangi, A. Paula Rodriguez Müller

Introduction Blockchain technology (BCT) has been widely discussed as a potentially valuable technology for advancing sustainable development in the public sector. Its core features, including transparency, immutability and decentralisation, may contribute to more accountable, efficient and inclusive public services. However, limited empirical evidence exists on how BCT-based public sector initiatives align with the United Nations Sustainable Development Goals (SDGs). Methods This study examines 306 public sector BCT-based use cases across the EU, compiled by the Public Sector Tech Watch observatory. We apply a GPT-4o-based AI text classification pipeline to assess the degree of alignment between project descriptions and the 17 SDGs. The pipeline combines refined SDG descriptors, structured prompting and documented model parameters. Its outputs are benchmarked against a human-coded subset to assess validity. Results The results show strong alignment with SDG 9 (Industry, Innovation and Infrastructure) and SDG 17 (Partnerships for the Goals), followed by more moderate alignment with SDG 8 (Decent Work and Economic Growth). By contrast, goals such as SDG 2, SDG 6 and SDG 14 remain weakly represented. These findings provide an empirical overview of how BCT applications in EU public administrations are framed in relation to the SDGs. Discussion By highlighting patterns of alignment between BCT adoption and the SDGs, this study offers evidence to inform policymakers, practitioners and future research on sustainability-oriented public sector innovation. It also demonstrates the value of AI-assisted classification for mapping large corpora of digital government initiatives, while recognising that the results capture stated or perceived alignment rather than verified sustainability impacts.

Omar Al-Jamili, Abdulaziz Fahmi Omar Faqera, Mohd Adan Omar, Shehu M. Sarkintudu · 8 authors

Open Government Data (OGD) has become central to digital transformation and data-driven governance, yet scholarly understanding of how OGD initiatives progress from initial adoption to sustained institutionalization remains fragmented. This study aims to synthesize the existing literature and develop an integrative framework that explains the socio-technical mechanisms underpinning the long-term sustainability and value creation of OGD initiatives. The study integrates bibliometric analysis with a systematic literature review of 481 peer-reviewed articles published between 2010 and 31 December 2024. Quantitative science-mapping techniques are combined with qualitative thematic synthesis to capture the intellectual structure, technological evolution, and theoretical foundations of OGD research. The findings reveal rapid growth and thematic diversification in OGD scholarship, with increasing attention to advanced technologies such as artificial intelligence and blockchain. However, the literature remains theoretically fragmented across behavioral, institutional, and public-value perspectives. Two critical gaps are identified: insufficient theorization of institutional legitimacy as a driver of continuity, and limited exploration of user-centric governance mechanisms shaping sustained data reuse. To address these gaps, the study proposes the Socio-Technical Institutionalization Model (STIM), which conceptualizes OGD sustainability as the dynamic alignment of technological infrastructures, institutional arrangements, and user ecosystems. By combining quantitative science mapping with systematic thematic synthesis and proposing the STIM lifecycle framework, this study offers an integrative synthesis that extends prior OGD reviews. The framework bridges fragmented theoretical perspectives and explains how open data initiatives may evolve from adoption to institutionalized value creation within complex digital governance ecosystems.

Nicolás Merveille

No abstract is available for this record.

Igor Calzada

This record contains the presentation materials prepared for the Data for Policy July Fireside Chat, “Digital Infrastructures of Democracy,” delivered online on 20 July 2026 by Professor Igor Calzada and chaired by Professor Marta Poblet. The talk presents Calzada’s action-research programme on digital citizenship and the democratic governance of digital infrastructures. Building upon the Oxford Research Encyclopedia article Digital Infrastructures of Democracy, it conceptualises democracy as being increasingly mediated by three interconnected infrastructural layers: material infrastructure, data infrastructure and algorithmic infrastructure. These layers are not politically neutral; their ownership, design and governance shape participation, rights, public accountability and the distribution of power. The presentation connects this conceptual framework with research on AI economics, Web3 decentralisation, the Digital Metropolis, EcoTechnoPolitics, territorial digital inclusion, data cooperatives and anticipatory AI governance. Particular attention is devoted to evidence from the Basque Country and Gipuzkoa, including the emerging supercomputing and quantum ecosystem associated with IBM Quantum System Two. The Basque Country is examined not as a model to be replicated mechanically, but as a city-regional laboratory whose lessons can support context-sensitive institutional learning elsewhere. The central argument is that democratic resilience requires the alignment of technical design, institutional reform and civic agency. Advanced computational capacity becomes a democratic public capability only when institutions can govern technological dependencies, territorialise benefits, ensure accountability, respect ecological limits and preserve meaningful opportunities for public participation and contestation.

Muthu Ramachandran

Introduction: The integration of blockchain technology with Internet of Things (IoT) devices in smart city deployments presents significant technical challenges, particularly regarding consensus mechanism design. Traditional blockchain consensus protocols such as Proof of Work (PoW) and standard Proof of Stake (PoS) impose computational, energy, and latency requirements that exceed the capabilities of resource-constrained IoT devices, motivating the development of lightweight alternatives. Materials and methods: This paper examines lightweight consensus mechanisms specifically designed for edge-optimised blockchain deployments, evaluates hybrid on-chain/off-chain architectural patterns, and presents a comparative analysis of emerging solutions. We propose four research hypotheses (H1–H4) regarding hierarchical consensus performance and validate them through extensive discrete-event simulation across five smart city domains, using a 500-node testbed calibrated to representative urban workloads. A novel Business Process Model and Notation (BPMN)-based process model formalises the three-tier consensus workflow, and security analysis quantifies Byzantine fault tolerance guarantees. Results: The proposed three-tier framework achieves a 94.7% ± 2.3% reduction in on-chain transactions while maintaining cryptographic auditability, with consensus latency under 500 ms for district-level operations (p < 0.001 vs. single-tier baseline). District-level throughput reaches 1247 ± 89 transactions per second (TPS), representing an 8.0× improvement over city-wide consensus, with energy consumption per transaction at the edge tier 95% lower than single-tier implementations. The simulation of 10,000 Byzantine attack attempts yielded a 99.97% detection rate. All improvements are statistically significant (p < 0.001, Cohen’s d > 0.8). Conclusions: Hierarchical consensus architectures, combined with selective off-chain processing, offer the most promising pathway towards scalable, secure blockchain–IoT integration in smart city contexts. Through an examination of five practical smart city use cases, we demonstrate that tailored consensus approaches can achieve the security guarantees necessary for critical urban infrastructure while respecting the computational limitations of deployed sensor networks. Remaining challenges in dynamic validator management, cross-chain interoperability, quantum resistance, and regulatory compliance are identified as priorities for future work.

Dr. Jogesh Chandra Mohanty

India’s aspiration to emerge as a developed nation by 2047 under the vision of Viksit Bharat necessitates the identification and scaling of localized innovations. Odisha, characterized by its socio-cultural diversity and rapid technological transition, presents a compelling case as a living laboratory for future-ready developmental models. This study positions Odisha at the intersection of three transformative domains: algorithmic welfare systems, governance challenges arising from silent urbanization, and the digitization of cultural heritage through Web3 technologies such as NFTs. By integrating quantitative modeling, qualitative fieldwork, and policy analysis, the study proposes a framework for culturally rooted, inclusive, and decentralized development. The findings suggest that Odisha’s experiments in adaptive welfare delivery, the recognition of hybrid urban spaces, and digital cultural economies not only address local challenges but also offer scalable insights for national policy. The state thus emerges as a microcosm of a technologically empowered, socially equitable, and culturally vibrant Viksit Bharat.

Vasiliy Krundyshev, Maxim Kalinin, Oleg Vasiliev

In recent years, the distributed ledger systems (DLS) has become an indispensable approach for creating anonymous payment systems in Smart City infrastructures (in transportation and industrial systems, energy planting and distribution, etc.). Although users in such systems are identified indirectly, but through cryptographic protocols, there is a class of attacks aimed at deanonymizing participants by analyzing transactions and constructing a graph of relationships between addresses. To implement these attacks, intruders use statistical analysis methods, graph theory, and specialized utilities for comparing data from external sources, such as exchanges. An analysis of related works in this domain has shown that compromising cryptographic primitives is not a prerequisite for deanonymizing DLS users; in some cases, analyzing public ledger data and the behavioral characteristics of DLS participants is sufficient. The goal of this research is to preserve privacy and develop protocols that minimize the risks of deanonymizing participants in Smart City ledgers built on the UTXO model. This paper presents a developed framework consisting transaction generator, an analyzer for modeling deanonymization attacks, and protocols designed to protect against such attacks. The experimental study has shown that the use of the CoinJoin protocol significantly complicates the deanonymization task and leads to a decrease in the deanonymization accuracy.

Xiaohong Wang, Wei Sun

No abstract is available for this record.

Mohamed El Amine Kheraifia, Abdelatif Sahraoui, Makhlouf Derdour, Abdellah Kouzou · 6 authors

No abstract is available for this record.

Hani Al-Balasmeh

No abstract is available for this record.

Barbara Eszter Huszár, Gabor Gyura

No abstract is available for this record.

Syahirah Balqis Anuar, Fatin Afiqah Md Azmi, Nurul Athirah Badrul Hisham

Efficient administration of small estates in Malaysia is characterized by the complications of the hybrid processes between manual and digital administration, and fragmentation of jurisdiction. This paper examines the operational bottlenecks in the existing system of estate distribution coordinated by the Department of Director General of Lands and Mines (JKPTG) as being the challenges of manual verification, absence of integration of the agencies across states, and security of documents as the major impediments to effective governance. In order to overcome these issues, the paper will offer the Integrated Estate Governance Framework (IEGF) an architectural improvisation based on the Small Estates (Distribution) Act 1955. The framework emerged as a result of adopting a Design Science Research (DSR) approach to the development of the study through the qualitative knowledge of senior officers in the JKPTG in a variety of states. The IEGF integrates a Consortium Blockchain with an AI Engine (to support decisions), Smart Contracts (to automate workflows) and Decentralized Identifiers (DID) with ECDSA (to perform secure authentication). The architecture is designed to be privacy and storage efficient by using Zero-Knowledge Proofs (ZKP) and InterPlanetary File System (IPFS). Findings show that the IEGF allows the jurisdiction-independent application process and automatic title endorsement through the e-Tanah integration. The paper has come up with the conclusion that a combination of these technologies offers a scalable, transparent, and robust solution to modernize the national land administration.

Omar Cheikhrouhou

No abstract is available for this record.

Igor Calzada

Abstract (Recent Book Presentation – AAG2026, San Francisco, California) This presentation introduces the recent book Datafied Democracies & AI Economics Unplugged , which critically examines how artificial intelligence (AI) is reshaping democracy, sovereignty, and economic systems through data infrastructures. Moving beyond techno-centric accounts, the book situates AI within political economy and innovation systems theory to interrogate how platform capitalism and data-driven governance are transforming contemporary societies into “datafied democracies.” The book develops a twofold analytical framework. First, it explores smart cities as key sites of technopolitical transformation, where AI infrastructures consolidate power in “data-opolies,” raising fundamental questions about democratic accountability and representation. While policy initiatives around “trustworthy AI” attempt to address these tensions, the analysis demonstrates that technical solutions alone are insufficient without institutional and territorial embedding. Second, the book examines the emergence of network states, algorithmic nations, and alternative forms of sovereignty in a post-Westphalian context. It critically interrogates the promises of Web3 decentralization, showing how they often reproduce new forms of concentration, including crypto-elite dominance and technocratic governance. In response, the book advances data sovereignty as a contested field—contrasting state-centric, corporate, and collective approaches—and positions data cooperatives as a pathway toward democratic data governance. The central argument is that the key challenge of AI economies lies not in technological innovation per se, but in the governance of data infrastructures and their societal implications. Drawing on global case studies, the book ultimately proposes mission-oriented and institutionally grounded innovation systems to reconnect technological development with democratic values, addressing the enduring tension between frontier innovation and social inclusion.

Fengfeng Bai, Kai Liu, Jihua Liu

The suggested paper introduces an improved lightweight blockchain model designed for smart city infrastructures, mainly focused on intelligent IoT scenarios. Today, smart cities mainly depend on interconnected IoT devices to improve services like transportation, energy and public safety. However, blockchain systems face significant difficulties due to high processing demands, data duplication and capacity problems. To address these issues, in this study, we proposed a novel model called Adaptive Hybrid Consensus (AHC), which combines the advantages of consortium and consensus lightweight concepts. Using a role-based hierarchy, this system classifies IoT devices according to their computing and storage abilities. Here, high-capacity nodes such as fog and edge computing devices can handle data validation and temporary storage, whereas low-capacity IoT devices focus on pre-validating data using an Assisted Local Consensus (ALC) method. Proof of Adaptive Authority and Stake (PoA-S) is a lightweight consensus technique that helps to continuously select validators according to their interest, workload and credibility to ensure balanced and effective operations. By storing only the important data on the blockchain and distributing non-essential data to edge nodes, the Assisted Selected Relevant Data in Local Ledger (ASRDLL) technique is used. Also, it helps to create a selective data storage strategy and reduces storage overhead. Topic-based partitioning is performed further to improve the network performance by classifying data according to their respective application domains. Then, the system enhances network performance by grouping data based on specific areas like healthcare and traffic management. It also focuses on quickly handling essential and time-sensitive data to ensure fast responses in serious situations. This design was tested using a prototype regarding energy reduction efficiency, data handling efficiency and quick response compared to the existing blockchain approaches. Therefore, again, this approach proves its efficacy in resource-constrained IoT environments and makes it suitable for smart cities.

Rutuja Chirwatkar, Beemkumar Nagappan, L. P. Singh, Anoop Dev · 6 authors

Another recent paradigm for enabling ubiquitous smart cities to be efficient, resilient, and innovative is Distributed Resource Management (DRM), in which heterogeneous devices, infrastructures, and services operate autonomously and continuously. This paper discusses more advanced concepts of edge-cloud synergy, decentralized coordination, cyber-physical integration, and context-aware optimization to address the increasing burden on urban energy, transportation, communication, and environmental systems. These are the main objectives: (1) to create scalable DRM frameworks with the features of real-time decision, (2) to enhance the interoperability of distributed heterogeneous resources, and (3) to enhance sustainability and service quality as a result of flexible allocation schemes. The proposed solutions will be the multi-agent systems, distributed ledger technologies (DLT), machine-learning-based prediction systems, and dynamic resource-orchestration algorithms. A hybrid simulation-prototype was applied to test the performance based on the metrics of latency, reliability, load balancing, and energy efficiency. Results suggest that significant improvements (up to a 35 percent reduction in resource contention, a 28 percent reduction in response time, and a 20 percent increase in system robustness under high-density urban workloads) have been achieved. A qualitative measure also fosters greater transparency and trust in cross-domain operations. In totality, the paper identifies that the disruptive potential of decentralized management systems can make smart-city ecologies adaptive, secure, and sustainable.