URNA: Energy Computing Power and Decentralized Physical Infrastructure (DePIN) in the Web3 Era — Whitepaper

The URNA ecosystem is the world's first DePIN (Decentralized Physical Infrastructure Network) to deeply integrate distributed energy and shared power bank services. We aim to tokenize millions of mobile energy terminals and shared power bank nodes, building a resilient, efficient Web3 infrastructure layer with transparent incentives.

Core Innovation: Unified PoSV mining for energy contributions from shared power banks.

Technology Stack: Built on BSC's high-performance L1, using PoSV proof of service, VRF-weighted random block production, zk-SNARKs privacy protection, TEE anti-forgery proofs, and full-stack IPv6.

Economic Model: The URNA token is anchored to energy computing power (Ener), incorporates a deflationary buyback mechanism, and settles in real time every 1 hour.

Vision: Address the high costs, centralized dispatch, and inefficient incentives of traditional energy infrastructure, pioneering a trillion-scale green digital economy.

Building on its existing shared power bank DePIN, Ener energy computing power, PoSV proof of service, and VRF-weighted block production mechanism, URNA further introduces an AI-powered intelligent energy network layer. This brings shared power bank nodes, user behavior, charging sessions, revenue data, device online status, and regional supply and demand data into a unified intelligent analytics framework. Through AI algorithms, the system can dynamically model node earnings, device dispatch, anomalous behavior, regional heatmaps, user demand, and energy computing power contributions. This makes URNA not merely a DePIN mining network, but an AI DePIN energy infrastructure capable of self-learning, self-optimization, and autonomous dispatch.

AI's core roles in the URNA ecosystem include:

· AI Node Earnings Forecasting: Predict the future earning potential of different locations based on regional foot traffic, historical rental volumes, device uptime rates, commercial district types, holiday factors, and charging demand.

· AI Intelligent Dispatch: Assist operators with device deployment, replenishment, maintenance, and relocation to improve shared power bank utilization.

· AI Anti-Cheating Risk Control: Identify risky behavior such as fake rentals, fabricated orders, abnormal revenue, falsified device online status, and mass-account attacks.

· AI PoSV Weight Optimization: Dynamically optimize the component weights of S_i based on real service data, aligning mining rewards more closely with actual business contributions.

· AI User Growth and Recommendation Optimization: Analyze user behavior to optimize recommendation pathways, membership benefits, reward mechanisms, and regional operating strategies.

· AI Energy Computing Power Market Forecasting: Forecast Ener computing power supply and demand, node distribution, regional output, and token release pressure to provide data support for DAO governance.

By integrating AI + DePIN + RWA, URNA will create a new infrastructure network jointly driven by physical devices, real revenue, on-chain incentives, and intelligent decision-making.

URNA aims to address structural challenges in two major sectors: energy and shared power banks:

URNA builds next-generation infrastructure with cutting-edge distributed technology and cryptoeconomic incentives:

DePIN Solution: Tokenize shared power bank energy terminals and use URNA to incentivize users worldwide to voluntarily deploy and operate physical assets (replacing CapEx with OpEx), enabling rapid, low-cost infrastructure expansion.

Core Positioning: A single-track DePIN platform for "energy computing power," focused on shared power bank use cases.

Value Hub: Energy computing power (Ener), the sole quantitative measure of real-world contributions, serves as the link between energy contributions and the URNA token.

The sophistication of URNA's infrastructure lies in its heterogeneous compatibility and native Web3 capabilities:

Heterogeneous Node Compatibility: Support for 23 types of energy nodes with different power ratings and use cases, including multiple shared power bank brands, ranging from small household sites to large shopping mall battery-swapping cabinets, enables unified protocol-level access and recognition of value rights.

Full-Stack IPv6 Architecture Advantages: The URNA network requires nodes to support IPv6 natively. This not only resolves address limitations for global deployment but, more importantly, enables direct end-to-end connections and improves the reliability of real-time charging data transmission.

Edge Computing Enablement: Intelligent energy hubs incorporate edge computing modules that process charging session logs and local validation in real time, transforming the shared charging network into a distributed energy computing power network that contributes Ener.

Ener follows a two-way incentive design:

Infrastructure Providers: Receive base computing power for deploying and operating shared power bank nodes.

End Users / Service Users: Receive usage computing power for using shared power banks or participating in charging activities.

This design ensures that both early ecosystem builders and users can fairly share future value returns.

URNA uses PoSV (Proof-of-Service) as its core consensus mechanism. Through a sophisticated weighted algorithm, it ensures incentives are precisely linked to actual service contributions, effectively preventing revenue fraud.

Service score S_i calculation formula (adapted to shared power bank use cases):

Where: E_i is charging energy output, T_i is site uptime, V_i is charging session volume, Q_i is service quality, R_i is actual revenue verification (a key differentiating factor), and P_i is protocol compliance.

Role of DAO Governance Parameters (α, β, …): These parameters are not fixed; Ener holders dynamically adjust them through DAO voting. For example, during peak charging periods, the weight of ε (actual revenue R_i) can be increased to incentivize high-revenue brand nodes; during network expansion, the weight of ζ (IPv6 weight) can be increased to encourage infrastructure upgrades.

Core PoSV Mining Mechanism: PoSV follows the philosophy of "service as proof." Nodes must continuously provide real, verifiable shared power bank services to receive URNA rewards. Mining has no premine whatsoever. In each 1-hour cycle, nodes across the network submit ServiceProof (including their S_i scores), and the system calculates and distributes rewards in real time.

Mining Process:

Nodes collect data in real time and generate ServiceProof through TEE (containing E_i, T_i, V_i, Q_i, R_i, and P_i).

The backend aggregates data every 1 hour to generate a Merkle root, and the Keeper calculates S_i after verification.

VRF performs weighted random block production based on S_i (weight η_i = S_i / Σ S), selecting a Leader node to generate a new block and execute reward distribution.

Rewards are distributed instantly in proportion to each node's S_i (via BEP20 transfers). Nodes with high S_i scores, especially brands with high R_i revenue, receive larger shares.

The entire process is transparent and auditable on-chain, eliminating fabricated activity and operation without real service.

VRF-Weighted Block Production Mechanism: VRF (Verifiable Random Function) generates cryptographic random numbers and verifiable proofs, ensuring fair and unpredictable block production. Nodes with higher S_i have higher probabilities, while randomness prevents monopolization. The 1-hour cycle perfectly matches the rhythm of the charging business, enabling near-real-time micropayment incentives.

Overall PoSV Advantages: Compared with traditional PoW/PoS, PoSV offers significant advantages in energy consumption, anti-fraud capabilities, anchoring to real-world revenue, and multibrand compatibility. It is the core engine distinguishing URNA from other DePIN projects. In the future, Phase III will upgrade to a fully decentralized oracle network and support AI task extensions.

Real-Time Settlement: The block production cycle is strictly maintained at once every 1 hour, forming the foundation for URNA to become a real-time, trustworthy cross-chain settlement asset.

To further improve the accuracy, fairness, and manipulation resistance of the PoSV proof-of-service mechanism, URNA introduces an AI intelligent analytics layer on top of PoSV. AI does not directly replace on-chain rules; instead, it serves as an off-chain intelligent computing and governance recommendation system, assisting with PoSV parameter optimization, anomaly detection, node ratings, and earnings forecasting.

The original PoSV service score formula is retained. The AI-enhanced version additionally introduces an AI dynamic scoring factor A_i to measure a node's intelligent operational quality, anomaly risk level, and future service potential.

Where: A_i is the AI node enhancement factor, representing the node's overall operational quality, regional value, and future earning potential; F_i is the AI risk penalty factor, representing the risk of fabricated activity, false online status, abnormal revenue, or anomalous behavior at the node; λ is the AI enhancement weight, set through DAO governance; μ is the risk penalty weight, set through DAO governance; and S_i^AI is the final AI-enhanced service score.

This mechanism allows the system not only to reward service contributions already made, but also to identify high-quality, sustainable nodes with genuine growth.

URNA will create an AI profile for each shared power bank node, including geographic, service capability, earning capability, risk, and growth profiles. Geographic profiles cover different settings such as commercial districts, transport hubs, schools, hospitals, hotels, tourist attractions, and residential communities. Service capability profiles cover device counts, uptime rates, rental frequency, charging duration, and user repeat-purchase rates. Earning capability profiles cover historical revenue, revenue per device, earnings per unit of time, and peak-to-off-peak variations. Risk profiles cover abnormal orders, abnormal accounts, unusual time periods, and abnormal revenue fluctuations. Growth profiles cover regional demand growth, holiday fluctuations, user activity trends, and device expansion potential.

Through AI node profiling, URNA can upgrade traditional "device-connectivity DePIN" into "intelligent-operations DePIN."

One of the core risks of shared power bank mining is the falsification or artificial inflation of device and revenue data. URNA will therefore establish an AI risk control system to identify fake rentals, frequent short-duration rentals, abnormal repeated orders on the same device, mass-account activity from the same address or device, revenue curves inconsistent with regional foot traffic, abnormal online status, devices continuously reporting data despite providing no real service for extended periods, unreasonable earnings spikes, abnormal Keeper data submissions, and abnormal API data from merchants or operators.

The AI risk control system will generate a risk score F_i for each node and use it as an important reference for PoSV mining weights. When a node's risk score is too high, the system can reduce its Ener computing power weight for the current period, suspend its participation in the VRF-weighted block production pool, require resubmission of TEE proofs or higher-level service proofs, submit anomalous snapshots to the DAO or risk control committee for review, and blacklist nodes with severe anomalies.

AI does not alter VRF's randomness or verifiability. Instead, it calibrates node service quality and risk levels before VRF weights are calculated. High-quality nodes with real revenue, low risk, and stable uptime receive more favorable S_i^AI weights; anomalous nodes have their weights reduced or enter a manual review queue. This preserves the fairness of VRF-weighted random block production while improving the alignment between PoSV mining and actual business contributions.

Data flow reliability and trustworthiness are essential to the success of PoSV + VRF:

Zero-Knowledge Proofs (zk): Address commercial privacy challenges. For example, a power bank operator only needs to submit a zk-commitment proving that its service data falls within the S_i range, without exposing precise customer data.

TEE Trust Bonus: Nodes using TEE technology can receive higher weights (such as a 1.2 multiplier on the ε weight), incentivizing hardware upgrades.

Decentralized Data Submission Path: An upgrade path is reserved to transform Keepers into a community-elected decentralized oracle network (for example, compatible with Chainlink/NEST), ultimately enabling trustless data submission.

URNA's AI-powered intelligent energy network layer sits between the device data layer, the PoSV computation layer, and the DAO governance layer, primarily handling data analysis, predictive modeling, anomaly detection, and operational optimization.

The AI system primarily uses shared power bank device online status, rental counts, charging duration and energy output, order revenue data, regional foot traffic and scenario labels, user activity and repeat-purchase data, external data such as holidays, weather, and commercial district events, historical node earnings curves, device maintenance and fault records, on-chain mining rewards, Ener computing power, and URNA release data. After de-identification, aggregation, and privacy protection processing, these data enter AI models for training and inference.

Node Earnings Forecasting Model: Predicts the revenue performance of a location or device group over the next 1 day, 7 days, and 30 days, providing a basis for device deployment and node expansion.

Device Dispatch Optimization Model: Determines which areas lack devices and which have idle devices, assisting operators with replenishment, relocation, and maintenance.

Anomalous Behavior Detection Model: Detects risky behavior such as fabricated orders, fake rentals, abnormal revenue, falsified device online status, and multi-account attacks.

User Demand Forecasting Model: Analyzes user borrowing and return behavior, active time periods, common use cases, and repeat-purchase trends to help the platform optimize marketing and recommendation strategies.

Token Release Pressure Forecasting Model: Forecasts URNA mining releases, node earnings, secondary-market liquidity, and buyback-and-burn pressure at different stages, providing data references for DAO governance.

DAO Parameter Recommendation Model: Uses network-wide operating conditions to recommend PoSV parameter adjustments to the DAO, such as whether to increase the R_i revenue weight, increase the T_i uptime weight, or reduce node weights in anomalous regions.

URNA's AI system will not directly control on-chain assets or bypass smart contracts to make centralized distributions. AI's role is to provide intelligent auxiliary scoring for PoSV, risk alerts for Keepers, parameter adjustment recommendations for the DAO, device dispatch recommendations for operators, and earnings forecasts and participation recommendations for users. Final reward distribution, VRF block production, URNA transfers, Merkle root recording, and DAO governance remain governed by on-chain rules, ensuring transparency, auditability, and immutability.

URNA will provide AI Agent operations assistants for different ecosystem participants, upgrading the platform from passive data display to proactive decision recommendations.

Through the AI Agent, node operators can query device uptime rates and anomalous devices, forecast future earnings, obtain recommendations for device deployment areas, receive reminders for device replenishment, maintenance, and relocation, analyze investment payback periods at different locations, assess whether a node warrants further expansion, and automatically generate daily and weekly operations reports and earnings analysis reports.

For example, an operator can directly ask: "Among my 300 devices in Shenzhen's Nanshan District, which locations have the lowest earnings? Should they be relocated?" The AI Agent will generate actionable recommendations based on device uptime rates, historical rental volumes, revenue data, and regional trends.

Through the AI earnings assistant, ordinary users can understand their current Ener computing power holdings, their expected daily/weekly/monthly URNA earnings, the earnings health of the nodes they participate in, risk levels across nodes, URNA mining releases and buybacks and burns, and whether continued node participation, reinvestment, or exit is suitable for them. The AI earnings assistant makes complex DePIN mining logic easier for ordinary users to understand, lowering the barrier to Web3 participation.

Through the AI decision assistant, DAO members can access network-wide node operating status, regional Ener computing power distribution, risk rankings of anomalous nodes, PoSV parameter adjustment recommendations, token release and buyback pressure analysis, simulated outcomes of different governance proposals, and analysis of ecosystem fund utilization efficiency. AI does not replace DAO voting, but can improve governance quality and prevent governors from making poor decisions with insufficient information.

The total issuance of URNA is 210,000,000 tokens, of which 70% is allocated to PoSV mining output, while 30% is initially allocated through preminting, circulation reserves, and vesting plans. Mining follows a halving every two years and block production every 1 hour.

Mining Output Schedule (PoSV: 70%, totaling 147,000,000 tokens, calculated with 1-hour cycles and halvings every 2 years; the first two years comprise 17,520 cycles, with an exact first-cycle reward of 4195.205479 URNA and subsequent rewards dynamically allocated under the halving rules):

Front-Loaded Release: A larger share is released early to ensure sufficient URNA is available to incentivize rapid infrastructure deployment and kick-start network effects.

Vested allocations follow two sets of rules: certain allocations release 20% upon receipt, with the remainder released in 60-day cycles; team and advisor allocations release monthly following a long-term lockup.

RWA-URNA is a dedicated rights-based sub-token representing 5% (10.5 million tokens). Its core objective is token-equity rights parity: deeply linking blockchain tokens to the economic rights of equity in real-world listed companies, allowing holders to enjoy economically equivalent participation in returns (dividends and disposal proceeds) to that of stockholders.

Return Calculation Formula:

Technical Implementation: An independent BEP20 sub-token supporting snapshots, Timelock multisignature controls, and voting delegation; off-chain agreements on rights to returns are signed with listed companies.

Interaction with PoSV/VRF: Ener computing power bonuses can be obtained through the DAO, forming a dual-return closed loop.

Compliance Process: KYC → Snapshot → Multisignature Approval → Execution → Annual Audit, aligned with mainstream RWA regulatory frameworks.

Risk Prevention and Control: The DAO can make dynamic adjustments, establish minimum-guarantee mechanisms, and disclose audits publicly.

RWA-URNA deeply integrates Web3 liquidity with the stability of traditional capital markets and is a core differentiating design of URNA.

The URNA ecosystem fund, which will gradually come under DAO control, primarily uses its funds for:

Compliance and Legal Affairs: Ensure the Ener computing power model is compatible with the international legal environment for virtual asset transactions, especially compliance in shared charging settlement.

Technology R&D: Invest in next-generation PoSV algorithms, zk/TEE integration optimization, and the development of AI-driven energy routing algorithms.

Market and Ecosystem Expansion: Subsidize early node deployment, developer incentive programs, and cross-chain integration costs.

In addition to the original uses of funds, the URNA ecosystem fund will further cover AI data governance, AI model R&D, and AI SaaS tool development. In compliance and legal affairs, the foundation will focus on compliance requirements related to the Ener computing power model, shared charging settlement, RWA-URNA rights mapping, AI data use, and privacy protection. In technology R&D, the foundation will continue investing in next-generation PoSV algorithms, zk/TEE integration optimization, AI-driven energy routing algorithms, AI risk control models, AI node earnings forecasting models, AI Agent operations assistants, and decentralized oracle network development.

For AI data and model infrastructure, URNA will establish a shared AI data platform to unify the governance of device data, order data, earnings data, on-chain data, and user behavior data, forming an AI model training framework capable of sustained iteration. For market and ecosystem expansion, foundation funds may subsidize early node deployment, developer incentive programs, cross-chain integration costs, AI tool ecosystem development, and the provision of AI SaaS operations tools to device operators.

The value of URNA is underpinned by its scarcity as a gateway to digital energy:

Energy Service Fee Settlement: All premium services within the URNA ecosystem, such as shared charging dispatch fees and enterprise charging services, can be paid for with URNA.

Buyback and Burn: The foundation will use 20% of the ecosystem's net earnings over the long term to continuously buy back and burn URNA, and may combine this with RWA-URNA returns to further strengthen deflationary momentum.

In addition to URNA token mining, ecosystem service fees, and the buyback-and-burn mechanism, URNA will build an AI SaaS revenue model for shared power bank operators, merchants, agents, and node investors.

URNA can provide ecosystem partners with AI services including location earnings forecasts, device deployment recommendations, regional heatmap analysis, device fault prediction, daily operations reports and financial analysis, abnormal order risk control, user growth analysis, agent team earnings analysis, node ROI calculations, and token mining earnings simulations.

AI SaaS services can use subscription fees paid in URNA, enterprise service fees paid in stablecoins, charges based on node counts, charges based on API call volumes, charges based on the number of AI reports generated, and customized deployment services for large operators. The portion of AI SaaS service fees paid in URNA may enter the buyback-and-burn pool under DAO rules, enhancing URNA's long-term value capture capacity.

AI SaaS will create new sources of demand for URNA: node operators need URNA to use advanced AI analytics, merchants need URNA to view location earnings forecasts, the DAO needs URNA to call governance simulation models, users need URNA to generate personalized earnings reports, and enterprise customers need URNA to access API data services. This makes URNA not merely a mining reward token, but also a service payment asset within the AI DePIN network.

I. Launch and Validation (2026 Q2 - Q4): Launch AI Node Earnings Forecasting V1; establish an AI data platform for device data, order data, earnings data, and on-chain data; launch basic AI risk control models to identify abnormal orders, devices, and earnings; provide AI operations reports to node operators; complete limited-rollout testing of the AI + PoSV scoring model.

II. Scaling Up (2027): Launch the AI intelligent dispatch system; support regional heatmaps, device relocation recommendations, and replenishment recommendations; integrate zk-commitment and TEE proof data into AI risk control models; launch AI SaaS tools for operators; establish the AI node profiling system.

III. Decentralization and TEE Enablement (2028): Integrate AI risk control scores into DAO governance; use the AI parameter recommendation model to assist the DAO in dynamically adjusting PoSV weights; launch AI Agents for users, node operators, and the DAO; support AI task extensions, allowing selected edge nodes to participate in lightweight AI inference tasks; establish a decentralized AI data verification mechanism.

IV. Globalization and Ecosystem Maturity (2029 - 2031): Establish a global AI DePIN energy computing power network; enable AI models to support operations across multiple countries, languages, and scenarios; open AI SaaS APIs to operators worldwide; form an integrated AI + DePIN + RWA network for digitizing physical assets; develop URNA into an intelligent dispatch and earnings settlement protocol for mobile energy devices worldwide.

URNA is more than a token issuance. Its strategic objective is to become a "programmable API interface" for green energy in the Web3 era. By deeply coupling individual energy behaviors with macro-level ecosystem goals, URNA is advancing the first clean energy future in human history jointly owned by its users.

Over the long term, URNA's value comes not only from scaling shared power bank devices, but also from AI's continuous improvement of operational efficiency in physical energy networks. The core problems of the traditional shared power bank industry are scattered devices, fragmented data, unsophisticated operations, and unpredictable earnings. Through AI, URNA transforms these scattered data into an energy computing power network that can be analyzed, predicted, optimized, and governed.

URNA's long-term positioning can therefore be further elevated to: an AI DePIN energy infrastructure protocol for the Web3 era. It is not only a settlement protocol for energy computing power, but also an intelligent operations system, AI risk control system, earnings forecasting system, and DAO governance support system for shared power bank devices.

URNA's core team combines capabilities in Web3 infrastructure, DePIN ecosystems, AI data intelligence, cross-border growth, tokenomics, and real-world operations. Together, team members will drive URNA's evolution from a shared power bank mining network into an AI DePIN energy infrastructure protocol serving global markets.

Kaz Zamri

Chief Strategy Officer

HEMAN

Head of Growth & Community

Ethan Lee

Chief Technology Officer

Sophia Chen

Head of AI & Data Intelligence

Daniel Wong

Head of Tokenomics & Treasury

Aisha Rahman

Head of Ecosystem & Operations

Kaz Zamri

Chief Strategy Officer

A Web3 leader with over 25 years of experience in technology and international business, and a computer science graduate of Singapore Institute of Technology. Since 2017, he has been deeply involved in blockchain and fintech, focusing on Web3 infrastructure, ecosystem partnerships, and cross-border growth. He has led multiple international collaborations spanning Southeast Asia, Hong Kong, and Eurasian markets, and served as COO of a fintech company, driving the global implementation and scaling of Web3 projects.

HEMAN

Head of Growth & Community

Active in blockchain since 2019, with a focus on Layer 1 and Metaverse ecosystems and extensive hands-on experience in community, growth, and marketing management. He has long been responsible for community building and growth at scale, integrated marketing campaigns, and cross-project joint promotions, maintaining close relationships with leading KOLs on YouTube, X (Twitter), Reddit, Telegram, and other platforms. He is also deeply involved in ecosystem collaborations, strategic partnerships, online and offline events, and regional expansion, with an active presence in Southeast Asia's Web3 market. He holds a master's degree in remote sensing and GIS and is fluent in English, Thai, and Hindi. In 2024, he served as a judge at the BNB Hackathon in Thailand, engaging and collaborating closely with leading Web3 teams from Taiwan, Singapore, and other regions.

Ethan Lee

Chief Technology Officer

With over 12 years of experience in distributed systems and blockchain R&D, he specializes in smart contract architecture, DePIN infrastructure, on-chain data systems, oracle integration, and platform security design. He is responsible for URNA's core technical architecture, PoSV computation framework, on-chain contract system, Keeper/oracle mechanism, and overall technical delivery.

Sophia Chen

Head of AI & Data Intelligence

Focused on AI, data modeling, and intelligent decision-making systems, with experience in edge computing, predictive analytics, risk control algorithms, operational optimization, and shared data platform development. She is responsible for building URNA's capabilities in AI node profiling, earnings forecasting, anomalous behavior detection, intelligent dispatch, AI Agents, and data governance.

Daniel Wong

Head of Tokenomics & Treasury

With extensive experience in Web3 economic models, liquidity strategies, fund management, and DAO governance, he is responsible for URNA's tokenomics design, mining release model, buyback-and-burn mechanism, ecosystem fund management, RWA-URNA rights mapping, and long-term financial strategy.

Aisha Rahman

Head of Ecosystem & Operations

With years of experience in platform products, merchant operations, and cross-regional ecosystem partnerships, she specializes in channel development, business implementation, partner management, and standardized operations. She is responsible for URNA's expansion and operations framework development across shared power bank operators, channel partners, regional agents, ecosystem partners, and overseas markets.

• Technology and Protocol Layer: Led by the technology head, covering PoSV, VRF, Keepers, BSC contracts, on-chain data submission, and system security architecture to ensure real shared power bank service data can be credibly measured, aggregated, and settled.

• AI and Data Layer: Led by the AI and data head, covering node profiling, earnings forecasting, intelligent dispatch, anomaly detection, and risk control model development to upgrade URNA from a device connectivity network to an intelligent operations network.

• Growth and Community Layer: Led by the growth and community head, covering Southeast Asian and global Web3 community building, KOL collaborations, regional events, ecosystem communications, and user growth.

• Ecosystem and Operations Layer: Led by the ecosystem and operations head, connecting shared power bank operators, agents, merchants, regional partners, and overseas markets to drive physical device integration at scale.

• Tokenomics and Treasury Layer: Led by the Tokenomics and Treasury head, designing mining releases, buybacks and burns, the ecosystem fund, RWA-URNA rights mapping, and long-term fund management strategies.

• Global Strategy Layer: Led by the strategy head, coordinating cross-border partnerships, business implementation, compliance pathways, international market expansion, and capital partnerships to ensure URNA can expand globally.

With this team composition, URNA can cover six key dimensions simultaneously: real device integration, trustworthy on-chain settlement, AI-powered intelligent operations, global market growth, tokenomics design, and ecosystem business implementation. This makes the project not merely a conceptual DePIN, but an AI DePIN energy infrastructure with real business execution capabilities and long-term ecosystem expansion capacity.

The innovative dual-layer value capture mechanism built by the URNA ecosystem successfully transforms the value of physical energy infrastructure into highly liquid, composable digital assets. Through the deep integration of technologies including PoSV proof of service, VRF-weighted random block production, and zk/TEE, we provide a transparent, secure, and highly scalable solution, perfectly suited to revenue differences across shared power bank brands and the RWA-URNA token-equity rights parity mechanism.

We warmly invite developers, energy operators, and end users worldwide to join the URNA ecosystem, jointly build this infrastructure with long-term growth potential, and share the green digital dividends of the trillion-scale energy transition.

With the introduction of AI technology, URNA will evolve from a standalone DePIN mining network into an AI DePIN network capable of intelligent analytics, intelligent dispatch, intelligent risk control, and intelligent governance. AI will help the ecosystem identify real service contributions more accurately, prevent false data and fabricated activity more effectively, improve device utilization and node earnings more efficiently, and provide data-driven decision support for DAO governance.

Starting with shared power banks, URNA will gradually expand to more mobile energy terminals, energy storage devices, edge computing nodes, and real-world asset use cases, ultimately forming a new digital energy ecosystem jointly driven by real devices, real services, real revenue, on-chain incentives, and AI-powered intelligent decision-making.

URNA is an AI DePIN energy infrastructure network that uses shared power banks as its physical entry point, Ener energy computing power as its value anchor, PoSV proof of service as its mining mechanism, and AI-powered intelligent dispatch and risk control as its growth engine.