Sustainable EV charging infrastructure is fragmented by proprietary applications, vendor lock-in, and weakly time-differentiated pricing, blunting its contribution to urban-mobility decarbonisation. This paper asks whether an open-protocol, super-app-mediated photovoltaicâstorage charging architecture can jointly resolve these three fragmentations under deployed field conditions and what its sustainability profile then looks like. We report a campus photovoltaicâstorage microgrid integrating heterogeneous EV chargers under an open, vendor-neutral charging-control protocol with super-app authentication and payment replacing dedicated charging applications and a time-differentiated tariff aligned at the meter-interval level with the underlying utility wholesale rate; the deployment is exercised through a researcher-scheduled commissioning campaign of 13 sessions designed to establish functional correctness across the operating envelope rather than to measure user behaviour. Three results emerge across cross-vendor compatibility, onboarding friction, and grid alignment. First, basic message-level OCPP compatibility is sustained across two charger vendors under a single cloud management systemâin sequential single-vendor sessionsâincluding the full charging profile up to near-rated DC peak power. Second, the super-app-mediated workflow, which requires no charging-specific application installation and no new charger-operator account, structurally eliminates the dedicated application installation and the email/SMS/credit-card verification round-trips of conventional onboarding, compressing measured first-use end-to-end interaction to 31 s; relative to reconstructed commercial-operator baselines, this is, to the best of the authorsâ knowledge, an order-of-magnitude reduction rather than a controlled benchmark. Third, mid-day energy delivery aligns incidentally with the utility off-peak window, not user-driven demand shifting, while PV-displacement and BESS-discharge contributions to charging are bracketed by scenario rather than being separately metered. The paperâs contribution is therefore a replicable, policy-embedded sustainable charging architecture validated at field scale within the New Taipei Net-Zero Carbon Demonstration Site Programme, with no claim of global novelty; the same architecture is structurally positioned to convert the observed incidental grid-friendliness into a deliberate, user-facing benefit via a hardware-free mid-day-discount redesign.
The increasing reliance on centralized ride-sharing structures, and exposes users to risks such as system failures and privacy breaches. manipulation, single points of failure, and privacy violations. In addition, high commission fees imposed by such platforms reduce the net earnings of drivers and compromise fairness within the ecosystem. To address these inefficiencies, this project introduces a decentralized vehicle borrowing system and carpooling, based on Ethereum Compatible blockchain and smart contracts. The proposed platform eliminates intermediaries by allowing KYC-verified drivers, passengers, and vehicle owners to interact directly, thereby building trust and operational transparency. All ride postings, bookings, car borrowing transactions, and agreement verifications are recorded immutably through smart contracts. Identity proofs, vehicle documents are cryptographically signed through MetaMask and uploaded via a decentralized file system (IPFS), ensuring authenticity and wallet-to-user binding. For drivers who borrow cars, temporary verification is enabled after signing a smart-contract-based agreement linked to the vehicle's verified owner. To maintain decentralization without depending on an administrator, the system introduces a Global Dispute Center where only users who fulfill certain predefined conditionsâhaving verified their identityâcan participate in resolving concerns through a voting process. This decentralized decision-making process enhances fairness and trust. Additionally, a structured post-ride rating system builds mutual accountability and trust among participants, while integrated COâ tracking encourages environmentally conscious behavior. Together, these features help minimize traffic load, support conscious travel habits, and build a reliable, user-governed mobility system that is secure, transparent, and environmentally supportiveâfunctioning entirely without any centralized authority or administrative oversight, thereby ensuring long-term sustainability. To address these limitations, this project proposes a blockchain-powered peer-to-peer carpooling and vehicle borrowing system that enables direct interaction between passengers, drivers, and vehicle owners without intermediaries. The platform utilizes smart contracts to automate agreements, MetaMask for secure authentication, and IPFS for decentralized storage of essential records. By shifting operational control to users, the system enhances transparency, fairness, and reliability in transactions. Conventional mobility services also face issues such as opaque processes, inefficient dispute handling, and limited mechanisms for conflict resolution. Drivers often lose a substantial portion of their income to service fees, while users lack trust in centralized decision-making systems. Furthermore, minimal emphasis is placed on promoting environmentally responsible travel practices. Motivated by the need for an open and community-driven mobility platform, this research aims to establish a distributed ecosystem that eliminates third-party dominance and ensures tamper-proof record keeping. The system incorporates KYC-based digital identity verification, smart contract-enforced agreements, decentralized dispute resolution through voting, and COâ emission tracking to encourage sustainable transportation. The scope of the project includes enabling secure ride booking, vehicle borrowing under verified ownership, and democratic dispute resolution among verified users. By leveraging distributed networks and digital wallets, the platform presents a scalable and sustainable alternative to centralized ride-sharing models.
N. V. Ravindhar, A. Manju, S. Murugesan, T. K. S. Rathish Babu
Electric Vehicle-to-Grid (V2G) arrangements stand at the center of bidirectional energy exchange in modern smart grids and are, however, challenged by real-time decision-making, load balancing, and the security of transaction validation. This paper has proposed an energy-efficient optimization framework based on a Bio-Inspired Deep Learning Controller using a Monarch Butterfly Optimization (MBO) algorithm with Gated Recurrent Unit (GRU) network for optimizing charging and discharging schedules across EV fleets. GRU networks forecast short-term grid demand and EV battery availability while MBO tunes the controller weights dynamically to adapt to scheduling under varying conditions. Furthermore, in order to maintain the trust over the transaction in a tamper-resistant fashion, a blockchain layer is embedded with the use of smart contracts to keep a track of authentication, pricing, and energy transfer log records for V2G. The proposed system shows charging cost reduction of 19.6%, peak load shaving efficiency of 23.2%, and forecast accuracy of 96.4%, in all mobility scenarios evaluated. The architecture also contributes to improving grid regulation response time by 28% and reducing EV queuing delay by 31%. Simulated by using MATLAB/Simulink, TensorFlow, and Ethereum-based blockchain, the architecture renders a scalable and secure framework for V2G coordination. It is noted that the findings are based on simulation, and co-simulation experiments, and the actual conditions of deployment like latency in communications, non-idealities of the hardware and regulatory factors are not factored into the analysis. Furthermore, the model facilitates real-time adaptation, strengthens grid resilience, and guides EV operation according to concurrent market conditions for energy.
Robots are improving their autonomy with minimal human supervision. However, auditable actions, transparent decision processes, and new human-robot interaction models are still missing requirements to achieve extended robot autonomy. To tackle these challenges, we propose RODEO (RObotic DEcentralized Organization), a blockchain-based framework that integrates trust and accountability mechanisms for robots. This paper formalizes Decentralized Autonomous Organizations (DAOs) for service robots. First, it provides a ROS-ETH bridge between the DAO and the robots. Second, it offers templates that enable organizations (e.g., companies, universities) to integrate service robots into their operations. Third, it provides proof-verification mechanisms that allow robot actions to be auditable. In our experimental setup, a mobile robot was deployed as a trash collector in a lab scenario. The robot collects trash and uses a smart bin to sort and dispose of it correctly. Then, the robot submits a proof of the successful operation and is compensated in DAO tokens. Finally, the robot re-invests the acquired funds to purchase battery charging services. Data collected in a three day experiment show that the robot doubled its income and reinvested funds to extend its operating time. The proof validation times of approximately one minute ensured verifiable task execution, while the accumulated robot income successfully funded up to 88 hours of future autonomous operation. The results of this research give insights about how robots and organizations can coordinate tasks and payments with auditable execution proofs and on-chain settlement.
Rong Zhao, Jiaxiang Sun, Haoran Yin, Lehao Lin ¡ 6 authors
The quest for carbon neutrality in the 21st century has led to the rise of decentralized low-carbon energy systems as a promising solution. Blockchain technology has played a pivotal role in catalyzing this transition, with various Web3 projects exploring decentralized operational models and carbon credit markets. However, there is a notable gap in harnessing blockchainâs potential to integrate electric vehicles (EVs) into low-carbon energy systems effectively. This article addresses this gap by proposing a decentralized low-carbon EV charging system that enables transactions between individual low-carbon energy producers and EV owners. Leveraging blockchain and smart contracts, the proposed system issues low-carbon tokens to certify and incentivize environmentally conscious charging behaviors, while enabling token circulation to further promote low-carbon participation. A blockchain-based double auction mechanism is designed to ensure fair and efficient energy allocation, achieving individual rationality, incentive compatibility, and social welfare maximization. By incentivizing user engagement and ensuring fair transactions, this model paves the way for sustainable EV integration within low-carbon energy systems.
The blockchain technology has attracted more and more interest recently as a reliable and secure platform for a variety of applications. This study presents a comprehensive comparative analysis of monolithic and modular architectural patterns in smart contracts, which have become a revolutionary technology thanks to the integration of blockchain technology. A real-world vehicle purchase and sale system was used as a case study. Two contract structures were used that perform the same function: a modular architecture with five interacting contracts, and a monolithic architecture that combines all these functions in a single contract. An empirical analysis conducted for 100 vehicle sales revealed that while the modular architecture offers advantages such as independent upgradeability, testability, and maintainability, the monolithic approach outperforms it in many metrics, including a 36.7% reduction in transaction costs and a 75% faster deployment time. The findings provide evidence-based architectural guidance for blockchain and smart contract developers in selecting appropriate design patterns, particularly in real-world applications where gas costs are critical. Cite this article as: T. Timu.in and S. BiroÄul, "A comparative analysis of monolithic and modular smart contract architectures: A case study of vehicle trading systems," Electrica, 2026, 26, 0333, doi:10.5152/electrica.2026.25333.
The accelerating adoption of electric vehicles (EVs) is intensifying pressure on urban power grids, particularly during evening peak hours. Existing smart-charging frameworks remain constrained by centralized control, static pricing, and limited integration of predictive intelligence. This study presents SMARGE, a hybrid AIâBlockchain smart charging platform that combines load forecasting, dynamic pricing, and cryptocurrency-based incentives to enhance decentralized EV energy management in Gaziantep Province. An ensemble of forecasting models (SARIMA, LightGBM, N-BEATS, and TFT) predicts 2026 hourly electricity demand, while an adaptive inverse-sigmoid pricing mechanism generates real-time incentives and disincentives for EV charging behavior. A fuzzy logic-based behavioral model simulates both unmanaged and managed charging across three scenarios. Results show that managed charging reduces peak load by 22.43%, shifts 67.45% of energy demand to off-peak periods, and achieves 94.86% charging fulfillment under constrained grid conditions. The blockchain layerâimplemented through a custom ERC-20 token (SMARGE) on the Ethereum Sepolia testnetâenables secure, transparent, and low-cost microtransactions with an average confirmation time of 0.63 s. These findings demonstrate that tightly coupling AI forecasting with tokenized blockchain incentives can improve grid stability, lower operational costs, and enhance user autonomy in a scalable and decentralized manner. While promising, the study is limited by assumptions of synthetic user behavior and ideal communication conditions; future work will validate the platform in real-world pilot deployments and across different urban regions.
The presence of shared micro-vehicles, such as bicycles and e-scooters, has become increasingly common in modern urban environments, enhancing citizensâ access to public transportation by providing an efficient solution to the last-mile problem. In recent years, shared mobility has expanded to include larger vehicles, such as cars and sea vessels, facilitating transportation over longer distances and offering an alternative to private and public modes of transport. However, the seamless integration of these different transportation modes remains a significant challenge, as each type of vehicle has its own advantages and limitations. Furthermore, these transport services are often operated by different organizations that use distinct platforms and ticketing systems, further complicating coordination among them. In this work, we present the proposed approach and the developed system designed to facilitate the adoption and integration of different types of vehicles using AI and blockchain technologies. The system enables users to identify and utilize the most appropriate means of transport through a unified, blockchain-based mechanism. Preliminary evaluation results, based on simulated data, indicate that the system can significantly benefit citizens in a smart city environment and, when combined with appropriate investments in urban infrastructure, can substantially improve daily mobility.
Sathwik Narkedimilli, Tejas Sathish, Mounira Msahli, Abdul Wahid
Blockchain technology has emerged as a promising enabler for the Internet of Vehicles (IoV). It offers decentralized coordination, immutable data sharing, programmable smart contract logic, and adaptive consensus mechanisms to meet stringent vehicular requirements. This comprehensive review reviews the state-of-the-art blockchain-IoV systems from 2019 to 2025, systematically classifying them into five dimensions: architectural models & smart contracts, consensus & scalability, security & privacy, federated learning & decentralized AI, and data dissemination with digital twin integration. We analyze lightweight consensus variants (e.g., PBFT extensions, DAG and sharding designs) that achieve millisecond-scale latencies and thousand-transactions-per-second throughput, as well as cryptographic frameworks (ring/group signatures, zero-knowledge proofs, TEEs) that preserve anonymity and secure key material. We highlight anchored-on-chain federated learning workflows to incentivize collaborative model training under non-IID data, 5 G/6G-enabled digital twins for provenance-aware simulation, and massive heterogeneity in edge-cloud architectures. Our comparative evaluation underscores advantages including resilience to Byzantine faults, privacy-preserving data exchange, energy-efficient consensus, and scalable deployments. Finally, we identify open challenges, including dynamic consensus tuning, cross-domain interoperability, real-world testbeds, and postquantum resilience, and outline a research roadmap toward robust, production-grade blockchain-enabled IoV ecosystems.
Vehicle-to-Everything (V2X) communication is at the center of autonomous mobility, as it enables vehicles to exchange real-time information with infrastructure, other vehicles on the road, including pedestrians, and the network. V2X has the potential to improve navigation, traffic flow, and safety but also brings with it the associated governance risks of data integrity, privacy, and cybersecurity. These risks are amplified by the interconnected nature of V2X networks, which handle sensitive data like vehicle locations and driver identities, necessitating robust security solutions. This systematic review considers blockchain as a remedy, with its decentralized architecture, cryptographic security protocols, and automation through smart contracts. A review of peer-reviewed literature from 2018 to 2025 highlights blockchain's role in tamper-proof communication, privacy preservation through Zero-Knowledge Proofs and Ring Signatures, and secure transaction automation. For instance, blockchain ensures data immutability by distributing trust across nodes, reducing vulnerabilities like data spoofing, while smart contracts streamline processes like toll payments. Challenges such as scalability, latency, and regulation are addressed with proposals such as 5G, edge computing, and governance frameworks. Hybrid blockchain systems, either public or private are examined in this study to obtain a trade-off between scalability and security in V2X networks. In addition, interoperability is proposed to facilitate the seamless exchange of data between V2X systems. Emerging consensus mechanisms like proof of stake and directed acyclic graphs are proposed to enhance scalability, while federated learning integrations bolster privacy. Pilot projects, such as those in Dubai and Singapore, demonstrate blockchainâs practical efficacy in securing V2X ecosystems. The review positions blockchain as a leading enabler of secure, efficient, and privacy-aware intelligent transport systems. Future research should focus on standardizing governance and addressing latency to ensure global adoption.
The application of Distributed Ledger Technology in Intelligent Transportation Systems ensures a secure and decentralized mechanism for data sharing among vehicles and infrastructure. However, DAG based protocols such as the IOTA Tangle when applied to autonomous vehicular systems face significant challenges in ledger consistency, transaction confirmation, and convergence due to the highly dynamic and intermittently connected nature of vehicular networks. To address these limitations, this paper proposes a Connectivity Aware Intelligent Distributed Ledger Construction Model tailored for autonomous vehicular environments. The proposed framework integrates a connectivity aware tip selection mechanism with a reinforcement learning strategy based on sliding window bias thompson sampling to dynamically select optimal ledger construction actions under non-stationary network conditions. Vehicular connectivity is modeled using an alternating renewal process, and transaction arrivals by a nonstationary Poisson process. Extensive simulation results demonstrate that CA-IDLCM outperforms URTS, MCMC, and Biased-TS approaches by achieving confirmation rate of 95.8%, and maintaining the orphan fraction well below 2%, with tip counts stabilizing near 1.0. highlighting its robustness, adaptability, and suitability for next generation Intelligent Transportation Systems.
The adoption of emerging transport technologies-such as autonomous vehicles, electric charging infrastructure, and hyperloop systems-increasingly depends not only on regulatory approvals and corporate investment but also on the collective sense-making and knowledge validation that occurs within informal digital spaces. Online communities, including forums, social media groups, and specialized platforms, have become influential arenas where early adopters, enthusiasts, developers, and policymakers co-construct technical knowledge, debate safety standards, and shape public perceptions. However, the governance of these virtual spaces remains critically under-examined. While organizations traditionally rely on formal, top-down mechanisms for technology dissemination and risk management, online communities operate through decentralized, peer-driven dynamics that can accelerate or hinder adoption trajectories. This research investigates the governance structures-both emergent and designed-that enable or constrain knowledge exploitation within transport-focused online communities. Specifically, it examines how community mediators, platform design features, and participant norms influence the credibility, accessibility, and translation of technical knowledge into actionable insights for adoption decisions. Employing a qualitative case study approach, this study analyzes two contrasting transport technology communities: an enthusiast-driven forum for electric vehicle charging standards and a professionally oriented group discussing autonomous freight logistics. Findings are expected to contribute a governance framework that transportation organizations can leverage to engage constructively with online communities, transforming them from peripheral chatter into strategic assets for technology adoption. The research further offers practical recommendations for community managers and transport policymakers on fostering productive knowledge ecosystems that balance openness with accountability.
This paper applies public choice theory to the governance of proof-of-work (PoW) blockchain systems, treating consensus mechanism design as constitutional political economy. The argument proceeds in two stages. The first establishes a feasibility constraint: under four conditions characterising permissionless systems-anonymity, permissionlessness, Sybil resistance, and oracle independence-identity-based governance is structurally infeasible, and any viable mechanism must weight participation by a costly, rivalrous signal (Propositions 1 and 2). The second establishes the normative content of that constraint. Through five constitutional axioms derived from Buchanan and Tullock (1962) and Brennan and Buchanan (1985), we prove that dynamic legitimacy-governance authority proportional to current productive commitment-is the uniquely required standard (Proposition 3). In a scaled PoW system, governance authority is structurally inseparable from productive participation: a miner cannot govern the network without running it. Proof of stake violates the temporal non-persistence axiom at the protocol level, creating the rent-seeking structure Krueger (1974) identifies, which regulatory capture dynamics documented by Stigler (1971), Peltzman (2022), and Fitzgerald (2024) then entrench endogenously. The paper derives five testable predictions and situates PoW governance within the constitutional economics and rent-seeking traditions of public choice theory.
Sarim Zia, Saleha Qureshi, Muhammad Zulfiqar, Arfa Ijaz
The paper discusses the economic and infrastructural challenges preventing the adoption of Electric Vehicles (EVs) in Pakistan.It focuses on key factors such as affordability, consumer preferences, and the overall readiness of the market.Based on a segment-wise comparison, the analysis reveals that four-wheeler EVs carry an initial price premium of 20 to 64 percent over internal combustion engine (ICE) vehicles, with payback periods ranging from 11 to 25 years, placing them out of reach for most middle-income consumers.In contrast, electric two-and three-wheelers-comprising more than 90 percent of registered vehicles-offer a significantly more practical and affordable pathway for mass adoption.These vehicles exhibit minimal upfront cost differences, annual operational savings exceeding PKR 62,000, and short payback periods of just 4 to 6 months, making them highly feasible in the local context.The study adopts a mixed-methods approach using national price data, vehicle registration records, and international case studies from India, Kenya, and Norway.It evaluates financing innovations such as battery leasing, concessional green loans, and carbon-credit-linked microfinance, and outlines a consumer-focused policy framework that emphasizes financial inclusion, decentralized infrastructure development, and phased implementation strategies.By aligning global lessons with Pakistan's socioeconomic and infrastructural realities, the paper offers a scalable and inclusive roadmap for accelerating EV adoption through targeted, consumer-driven solutions.
Drone delivery services are encountering issues related to transparency, authenticity, and safeguarding privacy, highlighting the urgent need for an innovative approach that incorporates blockchain technology. This innovation aims to solidify the permanence of records, enable instantaneous verification, and streamline data handling in these intricate, self-operating transactions. In this paper, we use of blockchain for creating Non-Fungible Tokens (NFTs), which act as unalterable logs of purchase within the realm of delivery logistics. Our method adopts a distinctive two-fold strategy that places equal emphasis on both tangible goods and information. When integrating our solution with the Polygon network, we have achieved a substantial reduction in the costs associated with transactions while simultaneously enhancing the speed at which these transactions are processed. Our work not only addresses the existing challenges faced by unmanned aerial vehicle (UAV) communication systems but also sets a new standard for efficiency and security in the delivery logistics sector, paving the way for more reliable and transparent UAV-based delivery services.
This research explores the future synergy between quantum computing (QC) and non-fungible tokens (NFTs) as a tool to revitalize urban transport systems through optimized improvement techniques as well as decentralized governance. Utilizing a conceptual approach combined with thematic analysis, this research provides an integrative framework that combines insights from quantum computing, blockchain governance, and transport geography. Key results include the observation that the integration of these technologies holds the potential to address enduring issues regarding efficiency, sustainability, and equity within transport through exemplary spatial optimization as well as open, participatory governance strategies. However, significant challenges do remain, including energy consumption, the digital divide, as well as regulative uncertainties, requiring careful design, equity-focused protections, as well as effective governance infrastructure. This paper suggests that the actualization of the full potential of these future technologies requires interdisciplinary collaboration as well as a focus on the public good rather than technological advancement alone.
Effective supply chain management under high-variance demand requires models that jointly address demand uncertainty and digital contracting adoption. Existing research often simplifies demand variability or treats adoption as an exogenous decision, limiting relevance in e-commerce and humanitarian logistics. This study develops an optimization framework combining dynamic Negative Binomial (NB) demand modeling with endogenous smart contract adoption. The NB process incorporates autoregressive dynamics in success probability to capture overdispersion and temporal correlation. Simulation experiments using four real-world datasets, including Delhivery Logistics and the SCMS Global Health Delivery system, apply maximum likelihood estimation and grid search to optimize adoption intensity and order quantity. Across all datasets, the NB specification outperforms Poisson and Gaussian benchmarks, with overdispersion indices exceeding 1.5. Forecasting comparisons show that while ARIMA and Exponential Smoothing achieve similar point accuracy, the NB model provides superior stability under high variance. Scenario analysis reveals that when dispersion exceeds a critical threshold (r > 6), increasing smart contract adoption above 70% significantly enhances profitability and service levels. This framework offers actionable guidance for balancing inventory costs, service levels, and implementation expenses, highlighting the importance of aligning digital adoption strategies with empirically observed demand volatility.
With the gradual shift towards the use of electric vehicles (EV), electricity demand is expected to increase especially in energy communities. Therefore, it is important to investigate how energy is generated as the provenance of electricity supply is directly linked to climate change. There are only a few studies that investigated the internet of energy and energy provenance, but this area of research is important to prevent the rebound effect of CO2 emission due to the lack of a transparent approach that verifies the source of electricity consumed for charging EVs. The energy system is a complex network, which results in difficulty verifying the source of electricity as related to the generation of energy. Identifying the provenance of electricity is challenging since electricity is a non-physical element. Moreover, the volatility of a Renewable Energy Source (RES), such as solar and wind power farms, in relation to the complex electricity distribution system makes tracking and tracing challenging. Disruptive technologies, such as Distributed Ledger Technologies (DLT), have been previously adopted to trace the end-to-end stages of products. Likewise, artificial intelligence (AI) can be adopted for the optimization, control, dispatching, and management of energy systems. Therefore, this study develops a decentralized intelligent framework enabled by AI-based DLT and smart contracts deployed to accelerate the development of the internet of energy towards energy provenance in energy communities. The framework supports the tracing and tracking of RES type and source consumed for charging EVs. Findings from this study will help to accelerate the production, trading, distribution, sharing, and consumption of RES in energy communities.
David King Boison, Musah Osumanu Doumbia, Ahmed Antwi-Boampong, Frank Senyo Loglo ¡ 5 authors
This study explores the application of blockchain (BC) technology in enhancing terminal operations at West African seaports, with a specific focus on Tema Port in Ghana. The purpose is to address inefficiencies in cargo processing, traceability, and data integrity that often impede port performance. Using a multi-layered qualitative approach, including observation and value stream mapping, the study examines current operational challenges at Tema Port and proposes a BC adoption model tailored to ship operations, quay transfers, yard management, container freight stations, and receipt/delivery processes. The findings suggest that BC technology significantly improves transparency, operational efficiency, and data security across port processes, offering a unified ledger system accessible to all stakeholders. Based on these findings, the study recommends a phased BC implementation, beginning with targeted pilot programs to mitigate technological and infrastructural constraints common in developing regions. Implications for port managers, policymakers, and academics underscore BCâs potential to reduce operational costs, enhance real-time visibility, and improve compliance in port logistics. This study is limited by its focus on terminal operations at a single port; future research could explore BCâs impact on other areas of the maritime supply chain across multiple ports. The originality of this study lies in its contextualized BC model for West African ports, addressing specific challenges faced by developing regions and offering a foundational framework for future BC applications in logistics.
As intelligent transportation systems (ITSs) evolve rapidly, the increasing computational demands of connected vehicles call for efficient task offloading. Centralized approaches face challenges in scalability, security, and adaptability to dynamic network conditions. To address these issues, we propose a blockchain-based decentralized task offloading framework with network-aware resource allocation and tokenized economic incentives. In our model, vehicles generate computational tasks that are dynamically mapped to available computing nodes-including vehicle-to-vehicle (V2V) resources, roadside edge servers (RSUs), and cloud data centers-based on a multi-factor score considering computational power, bandwidth, latency, and probabilistic packet loss. A blockchain transaction layer ensures auditable and secure task assignment, while a proof-of-stake (PoS) consensus and smart-contract-driven dynamic pricing jointly incentivize participation and balance workloads to minimize delay. In extensive simulations reflecting realistic ITS dynamics, our approach reduces total completion time by 12.5-24.3%, achieves a task success rate of 84.2-88.5%, improves average resource utilization to 88.9-92.7%, and sustains >480 transactions per second (TPS) with a 10 s block interval, outperforming centralized/cloud-based baselines. These results indicate that integrating blockchain incentives with network-aware offloading yields secure, scalable, and efficient management of computational resources for future ITSs.
Introduction Decentralized Autonomous Organizations (DAOs), digital organizations governed by code and community, offer new paradigms for collective governance; yet many early examples have reproduced the power asymmetries, exclusionary participation models, and inefficiencies found in traditional systems. This study examines how DAO governance can evolve to support fair, inclusive, and regenerative capital flows across distributed ecosystems, particularly in contexts where traditional coordination infrastructure is limited. Methods A qualitative case study was conducted on Hypha, an organisation that evolved from a classic DAO to a Decentralized Human Organization (DHO) and subsequently to an Adaptable Organization, or DAO 3.0. Data was collected through semi-structured interviews and document analysis, then interpreted using a PeopleâProcessâTechnology framework to identify governance design principles. This was supported by a comparative taxonomy mapping the evolution from DAO 1.0 to DAO 3.0. Results Findings show a progression from early token-weighted DAO 1.0 models, through protocol-optimized DAO 2.0 structures, to DAO 3.0âs modular, relational, and context-adaptive designs. Hyphaâs governance innovations include multi-layer modular voting, âleadership without controlâ protocols, real-time capital flow mechanisms, and trust-based safeguards that address fairness failures, enhance adaptability, and enable governance to respond dynamically to human complexity and local contexts. Discussion The Hypha case study positions DAO 3.0 as a prototype for regenerative coordination infrastructure where governance operates as a living system, balancing technological automation with human-centered design. This research expands DAO governance theory by clarifying conceptual boundaries, integrating recent literature, and providing practical guidance for policymakers, developers, and capital providers seeking to design equitable, regenerative governance and coordination systems.
Hafsteinn Hjartarson, FjĂślnir Thrastarson, Anna SigrĂĂ°ur Ăslind, GĂsli HjĂĄlmtĂ˝sson
Abstract Permissioned blockchains have gained prominence as a means of decentralizing trust while retaining controlled access, particularly in enterprise settings and regulated peer-to-peer environments. These systems offer advantages in scalability, performance, and security; however, challenges persist in effectively managing membership and its interaction with consensus protocols. Ethereumâs transition to Proof-of-Stake has also been a transition to managed membership, where validators are actively monitored and penalized for non-performance. This paper examines the dynamic tension between membership management and consensus protocols in permissioned blockchains, as well as the benefits of active management in improving overall system performance. In this paper, we propose a framework for dynamic membership management that includes actively admitting, monitoring, and ejecting members. Our approach decouples membership management from the underlying blockchain construction process. Our simulations confirm the potential benefits of managed membership, in part to facilitate lightweight mechanisms for improved performance and reliability. Our findings suggest that dynamic membership management is a critical area of study with significant implications for the future design of permissioned blockchains. Our contributions provide a conceptual foundation for designing dynamic membership protocols in permissioned blockchains, filling a gap in the literature and offering practical solutions to enhance blockchain performance in controlled environments.
Rayhan Ferdous Srejon, M. Fahim, Sk. Md. Shadman Ifaz, Md. Kamrul Hasan ¡ 6 authors
Ride-sharing platforms have revolutionized urban mobility, offering millions of users convenient and costeffective transportation. However, mainstream centralized platforms such as Uber and Lyft continue to face pressing concerns including data privacy breaches, high service charges, security vulnerabilities, and a lack of transparency due to centralized control. To address these limitations, this research proposes a semipublic blockchain-based ride-sharing platform integrating Hyperledger Fabric for secure and permissioned data management with Ethereum smart contracts for transparent ride booking, fare calculation, and payments. The platform leverages the InterPlanetary File System (IPFS) for immutable, decentralized storage and uses the Cosmos SDK to enable seamless interoperability between public and private blockchains. A user-centric pay-as-you-drive model is introduced to ensure fair and distance-based billing. Preliminary evaluations show that our system outperforms traditional blockchain consensus methods (PoW, PoA) in throughput, latency, and resource usage. At the same time, it remains economically viable with an operational cost of under 33,000 BDT per node. Future improvements include benchmarking with Hyperledger Caliper, transitioning from Vagrant to Docker for better scalability, and implementing backend services using Node.js or Golang with MongoDB for efficient metadata handling. Together, these enhancements support a secure, decentralized, and scalable alternative to existing ride-sharing systems.
Asst. Prof. Panchami M Hegde, Asst. Prof. Swetha M
Carpooling has emerged as one of the most practical strategies for reducing the growing challenges of traffic congestion, fuel consumption, and environmental pollution, yet conventional carpooling systems that are operated through centralized platforms continue to face numerous issues that restrict their effectiveness and adoption. Existing solutions largely depend on intermediaries to coordinate between drivers and passengers, creating a system that lacks transparency, suffers from high service costs, and exposes user data to privacy risks and security breaches. Moreover, traditional systems are often criticized for inefficient dispute resolution, a reliance on single points of failure such as central servers, and the absence of mechanisms that foster accountability and long-term trust among users. These weaknesses make centralized carpooling platforms vulnerable to manipulation, biased practices, and technical outages, thereby limiting their scope as sustainable mobility solutions. To address these persistent challenges, blockchain technologyâspecifically the Ethereum ecosystemâoffers a transformative alternative. Ethereum supports the development of decentralized applications (dApps) driven by smart contracts, which are self-executing agreements coded directly onto the blockchain. By embedding business logic into these contracts, processes such as ride creation, ride booking, payment settlements, user verification, and rating are automated, ensuring that interactions remain tamper-proof, transparent, and immune to third-party manipulation.