ABSTRACT Cryptocurrency has rapidly emerged as a disruptive force in the global financial ecosystem, challenging the traditional notions of currency, value exchange, and financial regulation. This study aims to provide a comprehensive analysis of the cryptocurrency market and its dynamic price movements, with a special focus on the factors influencing its growth and volatility. The research delves into the origin and evolution of prominent cryptocurrencies such as Bitcoin, Ethereum, and other altcoins, examining their market capitalization trends, adoption rates, and use cases in various sectors including finance, e-commerce, and decentralized applications. The study investigates the unique characteristics of the cryptocurrency market, such as its 24/7 global trading nature, decentralized governance, and susceptibility to market sentiment, regulatory news, technological developments, and social media trends. It also explores the role of blockchain technology as the foundational infrastructure behind cryptocurrencies, ensuring transparency, security, and immutability in transactions. In addition, this research analyzes market movement patterns, investor behavior, and the influence of macroeconomic factors like inflation, interest rates, and geopolitical events on cryptocurrency valuation. The impact of institutional investments, public perception, legal regulations, and government policies on the cryptocurrency ecosystem is also critically evaluated. The study further highlights the challenges and risks associated with cryptocurrency trading, such as extreme price volatility, cybersecurity threats, market manipulation, and the lack of uniform global regulatory frameworks. Despite these risks, the research identifies significant growth potential in areas such as decentralized finance (DeFi), non-fungible tokens (NFTs), and central bank digital currencies (CBDCs).
Najma Ali Soomro, Suresh Kumar Oad RAJPUT, Ishfaque Ahmed
Predictions regarding returns and price movements in financial markets can be made using online search engines, which track the sentiments of individual investors. This study aims to analyse how the sentiments of Bitcoin investors impact changes in the American stock market returns. The Bitcoin sentiment index was created to benchmark the sentiments of Bitcoin investors from 2013 to 2018. This index is built by analysing terms from leading business magazines and online journals. Such an index measures potential investors’ sentiments about Bitcoin and how those sentiments impact S&P returns. We use the ordinary least squares method to analyse this. It was found that BSI has a negative impact on S&P returns. Furthermore, the Vector Autoregressive (VAR) model is used to determine the relationship between these economic time series. VAR results indicated a significant positive impact of S&P returns on BSI, while BSI could not predict S&P returns. Consequently, it can be concluded that S&P returns cause changes in BSI. Recognising that Bitcoin sentiment can offer valuable insights and guidance for retail investors during market downturns, much like the S&P 500. By tracking changes in the S&P 500, analysts can anticipate shifts in cryptocurrency market sentiment and take preventative measures when needed. Understanding this relationship is crucial for assessing systemic risks, as volatility in traditional markets can impact the crypto space.
Andrea Bongini, Marco Sparacino, Luca Marzi, Carlo Biagini
In recent years, Facility Management has undergone significant technological and methodological advancements, primarily driven by Building Information Modelling (BIM), Computer-Aided Facility Management (CAFM), and Computerized Maintenance Management Systems (CMMS). These innovations have improved process efficiency and risk management. However, challenges remain in asset management, maintenance, traceability, and transparency. This study investigates the potential of blockchain technology and non-fungible tokens (NFTs) to address these challenges. By referencing international (ISO, BOMA) and European (EN) standards, the research develops an asset management process model incorporating blockchain and NFTs. The methodology includes evaluating the technical and practical aspects of this model and strategies for metadata utilization. The model ensures an immutable record of transactions and maintenance activities, reducing errors and fraud. Smart contracts automate sub-phases like progress validation and milestone-based payments, increasing operational efficiency. The study’s practical implications are significant, offering advanced solutions for transparent, efficient, and secure Facility Management. It lays the groundwork for future research, emphasizing practical implementations and real-world case studies. Additionally, integrating blockchain with emerging technologies like artificial intelligence and machine learning could further enhance Facility Management processes.
The accelerating digitization of healthcare has amplified the demand for secure, interoperable, and privacy-preserving information systems capable of managing sensitive patient data across diverse institutions. Traditional Health Information Systems (HIS) often struggle with fragmentation, data breaches, and lack of trust, posing significant barriers to integrated care and real-time medical decision-making. Blockchain technology—characterized by its decentralized architecture, cryptographic security, and immutability—offers a transformative paradigm for healthcare data management. This paper explores the development and deployment of Blockchain-Powered Health Innovation Information Systems (BHIIS), focusing on their potential to enable secure, verifiable, and scalable exchange of electronic health records (EHRs) across providers, payers, and public health institutions. By combining distributed ledger technology with smart contracts, BHIIS can automate data-sharing permissions, enhance patient control over personal health data, and ensure traceable access logs that comply with regulatory standards such as HIPAA and GDPR. This study examines architectural frameworks that integrate blockchain with interoperable health data standards (e.g., HL7 FHIR), enabling seamless communication among heterogeneous systems without compromising privacy. We evaluate consensus mechanisms, off-chain storage strategies, and identity management schemes that address scalability and data ownership concerns in real-world healthcare networks. Furthermore, the paper analyzes emerging use cases—including pandemic response, clinical trials, and chronic disease management—where blockchain-enhanced systems have demonstrated tangible benefits in accuracy, transparency, and trust. Ethical and infrastructural considerations, such as stakeholder governance, energy consumption, and digital divide challenges, are also discussed. By presenting a roadmap for implementing BHIIS, this work contributes to shaping next-generation health IT ecosystems that prioritize patient-centricity, resilience, and innovation.
Emmanuel O. Ajike, Timilehin Olasoji Olubiyi, Folorunso I. Akande, Mofoluwake F. Ayo · 5 authors
Small and medium-sized enterprises (SME) companies try to benefit from environmental sustainability and energy conservation in today’s competitive and technologically advanced world by integrating the most recent technologies into their supply chains. Due to blockchain adoption and what the future of blockchains holds for SMEs market, green supply chain management is improving SME market performance. Blockchain technology is a safe distributed ledger that can lower transaction costs, is transparent, fosters distributed trust, and enables decentralised platforms, with the potential to serve as a new base for decentralised business models. Green supply chain management (GSCM) integrates 4R1D’s sustainable environmental processes into traditional manufacturing, operations, and end-of-life management (reduce, reuse, recycle, reclaim and degradable). In order to shed light on the primary existing blockchain applications in SME market performance, as well as the main disruptions and obstacles in the adoption of Blockchain technology, this chapter examines the impact of blockchain technology adoption and green supply chain practices on SME market performance. The chapter employed a systematic review and synthesis of extensive literature as the research methodology, which is the most suitable for the achievement of the objectives of this study. The analysis of literature sources on blockchain technology adoption, green supply chain management were conducted and presented. The results confirmed a positive impact of blockchain technological adoption and green supply chain practices on SMS market performance.
Abstract : A smart contract is a self-executing program designed to automatically enforce the terms of an agreement between two parties, eliminating the need for intermediaries. Stored on blockchain or other distributed ledger technologies (DLTs), smart contracts ensure high security, immutability, and protection from vulnerabilities. These contracts facilitate various transactions, including financial exchanges, service delivery, and data manipulation, such as updating land titles. Additionally, they can be used to enforce privacy protection by selectively releasing privacy-protected data.While smart contracts are not legally binding by default, they automate business processes based on pre-defined conditions. Legal steps must be taken to make them enforceable in a legal context. This paper provides a comprehensive analysis of the anatomy of smart contracts, focusing on their key components, architectural structure, and underlying working principles., aiming to provide a comprehensive understanding of their operation and the challenges they present for adoption in various industries. Additionally, the study examines the various types of smart contracts, their real-world applications, and the significant benefits they offer, including automation, transparency, and security. The paper also addresses the challenges and limitations associated with smart contract implementation, such as scalability issues, security vulnerabilities, and legal complexities. By providing a detailed exploration of smart contracts from design to deployment, this research aims to offer valuable insights into their transformative potential in the digital economy. Keywords: Blockchain, Smart Contract,dApps,Hyperledger, DeFi,NFT,GDPR.
Hiago Vinícius Benedito dos Santos, Raissa Rosa dos Santos Januario, Ravelly Carvalho Zanatta, Saulo Neves Matos · 5 authors
In recent years, blockchain technology has established itself as an effective, secure, and transparent data storage solution. In this context, smart contracts play a fundamental role by enabling the automated execution of agreements without intermediaries. With the advancement of language models, the opportunity to automatically generate these contracts has emerged, raising concerns about their reliability and potential vulnerabilities. This article proposes a comparative analysis of the available language models for developing smart contracts using Ethereum Virtual Machine’s contracts as a case study. Experiments were made using various Large language models using different metrics to evaluate the susceptibility to vulnerabilities and computational cost. After comparing various models, ChatGPT appears to be the most suitable for generating smart contracts due to its higher compilation rate and, consequently, a larger sample size, despite detecting more vulnerabilities.
Mahesh Prasanna K, S. Chandrappa, K. B. V. Brahma Rao, H K Bhargav · 6 authors
The reliability of decision-making depends on ensuring data integrity when data comes from sensor networks in smart agriculture systems. The research develops a blockchain-supported secure communication model which protects against weaknesses in agricultural IoT systems. Distributed ledger architecture along with smart contract validation protocols forms the basis of the model for authenticating sensor data. Testing conducted in several agricultural settings confirmed data verification reached 99.7% accuracy and the detection of tampering achieved a success rate of 98.2% while authentication methods operated with 43% faster speed than conventional techniques. All simulated security breach attempts failed to penetrate the system which operated effectively in different field conditions. A scalable solution now provides agricultural data protection capabilities which allow farmers and agribusinesses to trust their sensor data for advanced crop management efficiency and resource planning and yield assessment.
This study investigates the connection between the creation of smart contracts in the Ethereum Virtual Machine and the returns of Ethereum and Bitcoin. The analysis reveals that while there is no connection between Bitcoin and smart contracts created on the Ethereum platform, a significant connection exists for Ethereum. Blockchain technology, which underpins cryptocurrencies, has garnered significant attention for its potential applications beyond financial transactions, including supply chain management, healthcare, and digital identity verification. We argue that blockchain adoption would increase the application of blockchain in general. We use the growth of smart contracts as a proxy for blockchain adoption. The findings suggest that the volume growth of smart contracts is correlated with the return on Ethereum but not on Bitcoin. This research contributes to understanding blockchain technology's impact on cryptocurrency performance and offers insights for academics and practitioners interested in the evolving landscape of digital assets.
The security requirements of the metaverse are expected to surpass those of conventional methods as it develops into a completely immersive digital ecosystem. With its unmatched computational capacity, quantum computing presents both amazing possibilities and challenging difficulties for metaverse security. The revolutionary potential of quantum technology in creating cybersecurity frameworks specifically for the metaverse is examined in this chapter. We look at the weaknesses in conventional encryption in this future environment, the threats posed by quantum-based assaults, and the rise of quantum-resistant algorithms. This chapter explores significant advancements in distributed ledger technologies, zero-trust architectures, and quantum cryptography to provide a road map for creating a strong, durable metaverse infrastructure. Future-proofing the metaverse will depend heavily on maintaining security through quantum-enabled technologies as digital assets, identities, and interactions become more and more integrated into daily life. The goal of this conversation is to provide stakeholders, legislators, and technologists with the knowledge necessary to successfully negotiate the intersection of next-generation cybersecurity and quantum computing.
This study presents a comparative analysis of trademark protection in the metaverse and the registration of virtual goods and non‐fungible tokens (NFTs) across three distinct legal systems: those of the United States, the United Kingdom, and South Korea. Drawing on recent case law and evolving administrative guidelines, this study examines how traditional trademark doctrines—such as the likelihood‐of‐confusion standard in the U.S. under the Lanham Act, source-identifying function under the UK Trade Marks Act 1994, and proactive legislative reforms implemented by the Korean Intellectual Property Office—are being adapted to address the challenges posed by digital and virtual environments. Specifically, this study analyzes landmark cases such as Hermès International v. Rothschild and Yuga Labs, Inc. v. Ripps , which illustrate the extension of trademark protection to NFTs and other digital assets, as well as the interplay between trademark rights and freedom of expression. It also evaluates recent updates to international classification frameworks—including the 2024 Nice Classification and the Madrid Protocol—and discusses their implications for ensuring uniformity and effective enforcement of trademarks in a borderless digital market. The findings reveal that while each jurisdiction applies its own legal traditions to metaverse trademark disputes, all share a common policy objective: to prevent consumer confusion and safeguard brand integrity in an increasingly digital economy. Ultimately, the study advocates for proactive registration of trademarks as virtual goods and NFTs to streamline enforcement and enhance legal certainty, thereby fostering innovation and facilitating global trade in virtual environments.
Nahid Ebrahimi Majd, Andres Hinojosa, Calvary Fisher, Fernando Landeros · 5 authors
Sui and Aptos are two rapidly growing blockchains. They get millions of transactions per day, and their DeFi TVLs (Total Value Locked) are among top ranked blockchains. They provide strong security, scalability, reliability, and verifiability comparing to other popular blockchains like Ethereum. They both use the Move smart contract language, but each one has added a different set of features and models to this language. While both Sui Move and Aptos Move introduce objects to store collections of data, Sui Move supports a variety of object-centric models, such as wrapped objects, dynamic fields, and dynamic collections, which are not introduced in Aptos Move. These strong features provide extensive scalability and endless possibilities for innovations. Due to all these facts, the Sui’s technology is being widely adopted by top-tier developers and leading projects. However, there is no research that analytically compares the performances of smart contracts developed in these two blockchains. In this research, we mainly focus on the features that are shared between Sui Move and Aptos Move. We introduce optimization patterns that save transaction fees in both blockchains and analyze their efficiencies in both Sui and Aptos. Our analysis showed that our introduced optimization patterns can effectively reduce the transaction fees on both Sui and Aptos. We also evaluated the performances of Sui and Aptos on object and non-object models. Our results demonstrated that the Sui object models efficiently reduce the transaction fees by 40-69% comparing to non-object models but equivalent Aptos Move object models perform less efficient.
Najmus Sakib Sizan, Md. Abu Layek, Khondokar Fida Hasan
To improve crop forecasting and provide farmers with actionable data-driven insights, we propose a novel approach integrating IoT, machine learning, and blockchain technologies. Using IoT, real-time data from sensor networks continuously monitor environmental conditions and soil nutrient levels, significantly improving our understanding of crop growth dynamics. Our study demonstrates the exceptional accuracy of the Random Forest model, achieving a 99.45\% accuracy rate in predicting optimal crop types and yields, thereby offering precise crop projections and customized recommendations. To ensure the security and integrity of the sensor data used for these forecasts, we integrate the Ethereum blockchain, which provides a robust and secure platform. This ensures that the forecasted data remain tamper-proof and reliable. Stakeholders can access real-time and historical crop projections through an intuitive online interface, enhancing transparency and facilitating informed decision-making. By presenting multiple predicted crop scenarios, our system enables farmers to optimize production strategies effectively. This integrated approach promises significant advances in precision agriculture, making crop forecasting more accurate, secure, and user-friendly.
Iulia Cristina Iuga, Raluca Andreea Nerişanu, Larisa-Loredana Dragolea
This study investigates the risk spillover between clean and dirty cryptocurrencies and their impact on green finance indexes (solar, wind, and nuclear energy) and regional economic indexes (Baltic Dry Index and CRB Index), with data processed using the diagonal BEKK model. The results identify several dirty cryptocurrencies such as: Ethereum Cash (ETC), Litecoin (LTC), and Bitcoin (BIT) as potential diversifiers and hedges with specific green energy and economic indexes. Our findings show that news from the cryptocurrency markets predominantly have a positive, significant effect on the covariance with green finance indices. The study also presents the covolatility spillover effect, showcasing the impact of a return shock in one market, such as the cryptocurrency market or the green finance market, on the co-volatility between markets, including regional economic indices like the Baltic Dry Index and CRB Index. The analysis reveals differential spillover patterns between clean and dirty cryptocurrencies and various green finance indices, highlighting the complexity of their interactions and the varying degrees of influence on regional economic indicators.
Blockchain-enabled smart contracts have revolutionized secure, automated, and decentralized transaction handling across various industries. However, they face limitations in complex decision-making due to their rigid execution and predefined rules. This paper explores the integration of a hybrid deep learning model with blockchain-enabled smart contracts to enhance their functionality and decision-making capabilities. By embedding deep learning layers within the smart contract framework, this approach enables real-time data analysis, predictive analytics, and adaptive decision-making, fostering a more robust and dynamic contract execution. Through this integration, the hybrid model can analyse transaction data, external conditions, and contextual parameters, improving contract outcomes in applications like finance, supply chain management, and healthcare. Experimental evaluations demonstrated that the proposed model achieved 98% accuracy, with a precision of 97.65%, a recall of 97.4%, and an F1-score of 97.5%, significantly enhancing smart contract flexibility and resilience while maintaining security and transparency.
This paper examines how blockchain technology and the Metaverse can address persistent challenges in corporate compliance, with a focus on mitigating criminogenic asymmetries—such as regulatory arbitrage and opacity in cross-border transactions—through decentralized, transparent solutions. By contrasting the U.S. and Italian legal frameworks, we highlight the limitations of retrospective compliance evaluations and propose blockchain-enabled innovations, including immutable audit trails, smart contracts for automated enforcement, and Decentralized Autonomous Organizations (DAOs) to decentralize governance and embed compliance into protocol design. The Metaverse offers a simulated environment for stress-testing compliance protocols against emerging risks, while criminological theories (e.g., global anomie, legal-illegal interfaces) contextualize regulatory gaps in digital economies. We argue that DAOs, as digital-native entities, could revolutionize compliance by replacing hierarchical oversight with algorithmic governance, though challenges like jurisdictional fragmentation and identity verification persist. The study underscores the need for adaptive regulatory frameworks to harness these technologies while balancing transparency, accountability, and privacy.
The integration of blockchain technology into smart city governance frameworks is revolutionizing the way urban management systems are structured, enabling secure, transparent, and decentralized decision-making processes. This chapter explores the transformative potential of blockchain-enabled decentralized governance models in enhancing accountability, reducing bureaucratic inefficiencies, and promoting citizen participation. The application of smart contracts and distributed ledgers is examined as a means to automate governance functions, facilitate real-time resource distribution, and ensure trust among stakeholders. Through detailed case studies and critical analysis, the chapter highlights practical implementations of blockchain in local governments, such as energy trading, public service automation, waste management, and participatory budgeting. In addition, the challenges of citizen engagement, legal compliance, and technological integration are addressed with forward-looking strategies for overcoming these barriers. This chapter contributes a comprehensive understanding of how blockchain can reshape urban governance ecosystems, offering scalable, resilient, and inclusive solutions for future smart cities.
Fintech 4.0 integrates Artificial Intelligence (AI) with Blockchain technology to enhance smart accounting systems in Industry 4.0, ensuring transparency, automation, and security. Traditional accounting methods face challenges such as data manipulation, lack of real-time verification, and inefficiencies in auditing processes. To address these issues, the proposed Blockchain-assisted Decentralized Ledger System (BC-DLS) leverages AI-powered smart contracts and distributed ledgers for automated auditing, ensuring real-time validation and fraud detection. This method enhances accuracy, reduces human intervention, and streamlines financial transactions with enhanced security and compliance. The proposed approach ensures secure, immutable, and transparent financial records, minimizing discrepancies and improving trust in financial systems. Experimental results demonstrate that BC-DLS significantly enhances efficiency, reduces operational costs, and strengthens fraud prevention mechanisms, making it a robust solution for modern financial ecosystems.
As a Secure Payment and IoT Cloud Cryptography Architect for Banking Systems, to specialize in designing and implementing cryptographic security solutions for smart cards, contactless payments, and IoT -driven banking infrastructures. Leveraging advanced cryptographic techniques, For data protection and authentication, this paper proposes integrate AES, RSA, ECC, SHA-3, and HMAC while making sure that industry standards like PCI DSS, EMV, ISO 27001, and NIST are followed. Post-quantum cryptography (CRYSTALS-Kyber, Dilithium), zero-knowledge proofs (ZKPs), It should be fluent in cutting-edge technologies such as blockchain-based security for decentralized identification and IoT payments, secure multi-party computing (MPC), and fully homomorphic encryption (FHE). Additionally, this study focus on AI-driven fraud detection, confidential computing, and hardware security modules (HSM, TPMs) to enhance banking cybersecurity resilience. With a commitment to innovation, this research work develop quantum-resistant, privacy-preserving cryptographic frameworks to safeguard financial ecosystems against evolving cyber threats.
Apr 23, 2025·2025 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI)
N Kirubakaran, Goutam Sahana, S Chandrahasini, Sara Harsini · 6 authors
The use of blockchain technology in land management systems provides a new way of meeting the inefficiencies and challenges associated with conventional land administration. This research is based on a collection of research papers that shed light on several facets of blockchain and allied technologies, such as distributed ledgers, smart contracts, and predictive analytics. These technologies promise to advance land registration and property transactions through greater transparency, security, and efficiency. The papers discuss subjects including digitizing land records through methods, enabling real-time access to data, and novel applications utilizing platforms such as Hyperledger, Ethereum, and IPFS. Comparative studies show the vast potential of blockchain to settle land conflicts, decrease administrative turnaround time, and establish trust among parties. In addition, the articles study the convergence of blockchain and artificial intelligence (AI) and the Internet of Things (IoT), providing evidence of innovation in land titling and property verification. They also study the use of machine learning in creating predictive systems in land management. These studies validate the use of blockchain in the modernization of land systems, opening doors to its further use in governance and property management in countries.
Ângela Filipa Oliveira Gonçalves, Shafik Faruc Norali, Clemens Bechter
The paper investigates current and future pricing models in the European healthcare sector. European countries follow a universal healthcare system, whereas the United States rely on a mix of private insurers, government programmes, and private payments. It is becoming obvious that the European “free” healthcare systems are not sustainable in the long run. The authors propose a private Buy-Now-Pay-Later (BNPL) alternative. BNPL is common practice in retailing but highly unusual in healthcare. The authors suggest to enhancing BNPL further by adding AI and blockchain/crypto technology. However, there are three hurdles to overcome, namely, cryptocurrency volatility, regulatory uncertainty, and adoption barriers. Our field research investigated the acceptance barriers especially whether European medical service providers would accept cryptocurrency payments and the BNPL model in general. Our survey is based on 366 European medical service providers, mainly medical doctors. The results show that there is willingness to accept cryptocurrencies. As recommendation we outline how a fully integrated AI-powered BNPL model with cryptocurrency payments and smart contracts including BNPL Tokenisation in a decentralised financial market could work to the benefit of all stakeholders.
The integration of artificial intelligence (AI) into Internet of Things (IoT) systems has outpaced the development of mechanisms to explain and audit automated decisions, creating a transparency gap. This paper addresses the research problem of establishing immutable audit trails for AI-driven IoT decisions to enhance trust, accountability, and regulatory compliance. We propose a blockchain-based framework that logs each AI inference and its provenance data (inputs, model parameters, and outputs) on a tamper-proof distributed ledger, ensuring every decision is traceable and auditable. The technical method- ology centers on a permissioned blockchain ledger deployed alongside IoT infrastructure. IoT devices and edge nodes commit decision records via smart contracts, producing an im- mutable, timestamped log resistant to manipulation. This approach leverages blockchain’s decentralization and cryptographic integrity to guarantee non-repudiation and data integrity. We detail how the system design balances transparency with privacy (e.g. hashing personal data) to remain compliant with data protection norms. The solution aligns closely with emerging regulatory frameworks such as the EU AI Act’s mandate for automated decision logs and traceability, and GDPR’s accountability and transparency requirements (e.g. maintaining audit logs of AI decisions for explainability). We demonstrate the frame- work’s applicability across domains: healthcare IoT, to log diagnostic AI recommendations for accountability; and industrial IoT, to track autonomous control actions - showing that our approach generalizes to diverse high-stakes environments. The paper’s contributions include a novel architecture for AI decision provenance in IoT, a detailed implementation on a blockchain ledger to securely record AI decision-making processes, and an evaluation of its performance and compliance benefits. By providing a reliable, immutable audit trail for AI in IoT, this work enhances transparency and trust in autonomous systems and offers a timely solution for auditable AI in an era of increasing regulatory scrutiny.
Under the “dual carbon” background, consumer electronics consumption has become deeply ingrained in people’s minds. However, consumers often distrust the sustainability claims of consumer electronics products. Artificial intelligence (AI) and blockchain technology can address this trust deficit through transparency and traceability mechanisms. This study integrates blockchain technology into traditional consumer electronics supply chains, considering consumers’ preferences and trust in these products. An AI-based game model is proposed to analyze the interactions among supply chain members before and after implementing blockchain technology, under varying Edge Computing-based power structures. This model quantitatively evaluates emission reduction and pricing strategies, aiming to optimize consumer surplus and total social welfare. By leveraging Lightweight AI and blockchain, smart wholesale and cost-sharing contracts are designed to establish reasonable ranges for wholesale prices and optimal cost-sharing ratios, enhancing enterprise operational efficiency and achieving supply chain coordination. Results demonstrate that when consumers exhibit a stronger preference for consumer electronics products, the adoption of Lightweight AI and blockchain delivers greater benefits across the supply chain. Furthermore, as consumer willingness to purchase these products increases, the advantages become more pronounced. Numerical analysis highlights that smart contracts can better coordinate the supply chain, particularly in retailer-dominated scenarios. Finally, empirical cases