Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Digital Carbon Management Platform for Solving the Climate Crisis
The climate crisis is one of the most urgent challenges facing the world today. To address it, accurate measurement of carbon emissions and effective reduction and offsetting efforts based on these measurements are essential.
Without precise accounting of carbon emissions, it is impossible to set reduction targets or verify the effectiveness of offset activities. Therefore, accurate measurement is the first step in combating the climate crisis.
GESIA (Green Earth Social Impact Alliance) is an innovative platform that combines IoT, blockchain layers, AI analysis, and the Net Zero Consensus Algorithm to transparently manage carbon emission data, enabling effective reduction and offset activities.
Accurate carbon emission measurement is at the core of addressing the climate crisis.
Ensuring transparency and reliability Without reliable carbon data, it is impossible to set reduction targets or verify the effectiveness of offset activities, creating significant barriers to addressing climate change.
Foundation for reduction strategies Detailed data serves as the basis for developing concrete plans, such as improving energy efficiency, designing emission reduction pathways, and implementing RE100 initiatives.
Essential for carbon offsetting Offset activities, such as issuing and trading carbon credits, require precise emission data to establish trust, directly impacting the transparency and effectiveness of the global carbon market.
GESIA provides the following digital solutions for measuring carbon emissions:
Real-Time Data Collection with IoT Sensors
IoT sensors are installed in each space to automatically collect energy consumption data such as electricity, gas, and heating.
Data is monitored in real-time and categorized by space and time to provide detailed emission breakdowns.
Space and Fragmentation-Based Measurement
Space-Based Measurement : Emission data is collected at the building, factory, or office level to calculate precise emissions for each space.
Fragmentation : Even within a single space, data is analyzed at a granular level, such as by individual, device, or activity, for detailed insights.
Data Transparency through Blockchain
Ethereum Chain Layer 1 : Ensures the fundamental reliability of carbon emission data.
Net Zero Chain Layer 2 : Connects carbon emission, reduction, and absorption data, and verifies the reliability of offsetting, reduction, and RE100 activity data through the Net Zero Consensus Algorithm.
Emission and Offset Chain Layer 3 : Aggregates and analyzes carbon emission and offset data in real-time, rolling it up to Layer 2 for validation.
AI-Driven Reduction Strategy Proposals
AI analyzes collected data to identify emission patterns and proposes energy efficiency improvements and reduction strategies.
Predictive models suggest the optimal pathways for achieving reduction targets.
Net Zero Consensus Algorithm
Integrates offsetting, reduction, and RE100 goals to develop optimal offsetting strategies.
Continuously verifies the effectiveness of reduction and offset activities, providing actionable guidance for achieving carbon neutrality.
GESIA supports carbon offset activities based on accurate emission measurements, providing a reliable solution for the global carbon market through the issuance and trading of digital carbon credits.
Issuance of Carbon Credits
Digital carbon credits are issued based on reduction and offset activities, ensuring compliance with international standards.
Offsetting and Transparency
The issuance and burning processes of carbon credits are recorded on the blockchain, creating a trustworthy trading environment for all participants.
Carbon SEED is a core component of the GESIA blockchain, representing the digitized fundamental unit for collecting, analyzing, and aggregating carbon emission and offset data.
Digital Tokenization of Data
Carbon SEED is used as a unit to convert actual carbon emission data into digital emission tokens.
Metadata-Based Management
SEED includes metadata that references the storage location of emission or offset data.
Seed_ID: A unique identifier for the data.
Timestamp: The point in time when the data was recorded.
Storage_Location: The URL of the external system where the data is stored.
Source: The device or source from which the data was collected.
Data_Type: The type of data (e.g., Emission, Offset, None).
Substance: Information about the substance.
Type: The type of the substance (e.g., Element, Compound).
Name: The name of the substance (e.g., Lithium).
Symbol: The symbol of the substance (e.g., Li).
Measurement_Unit: The unit of mass used as the basis for the initial substance (e.g., g, kg).
Base_Substance_Amount: The initial mass used as the reference for the substance.
Activity_Category: The type of activity associated with the substance (element/compound).
Per_Unit: The amount of emissions produced per one unit of the substance or energy consumption (e.g., 1 kWh = 424 g).
Verification_Status: The verification status of the data.
Geographic_Location: The geographical location where the data was collected.
Aggregated: Whether the data is individual or aggregated.
Signed_Value: A signature value ensuring the integrity of the data.
{
"Seed_ID": "unique-seed-12345",
"Timestamp": "2024-12-16T10:30:00Z",
"Storage_Location": "https://example.com/data/storage",
"Source": "Sensor-01",
"Data_Type": "Emission",
"Substance": {
"Type": "Element",
"Name": "Carbon",
"Symbol": "C",
"Measurement_Unit": "g"
},
"Base_Substance_Amount": 1000,
"Activity_Category": "Electricity",
"Per_Unit": "424g",
"Verification_Status": "Verified",
"Geographic_Location": "Seoul, Korea",
"Aggregated": false,
"Signed_Value": "abc123signature"
}The SEED token is a digitized fundamental unit token designed for collecting, analyzing, and aggregating carbon emission and offset data.
ERC1155 provides flexibility by enabling a single smart contract to manage both fungible and non-fungible tokens simultaneously, making it highly optimized for managing unit-based token structures.
A voucher token is a data token issued on the blockchain by tokenizing external data. To deploy it on the blockchain, a Notary Oracle is required. The Notary Oracle uses a multi-signature mechanism between the account providing the external data and the account receiving it on the chain to prove the reliability of the data.
ERC1155 provides flexibility by allowing a single smart contract to manage both fungible and non-fungible tokens simultaneously. This makes it highly optimized for managing tokens in a registry format.
An extended token is a newly issued token created by custodializing a voucher token, proving that it is an extension of the voucher token signed with external data.
This token is deployed to repurpose the voucher token for new applications, specifically addressing the prevention of double counting to ensure and demonstrate the reliability and integrity of the external data.
ERC1155 provides flexibility by enabling a single smart contract to manage both fungible and non-fungible tokens simultaneously. It is optimized for managing multiple derivative tokens through its multi-token management capabilities and batch transfer functionality.
Private Node
Aggregates and records carbon emission data.
Connects to a data aggregation system via IoT devices and transmits real-time data to the blockchain.
Private Node
Aggregates and records carbon offset data.
Verifies carbon absorption and reduction data to tokenize carbon credits.
Public Node
Utilizes the Net Zero Consensus Algorithm to achieve net zero by processing carbon emission and credit tokens.
Tracks real-time emission tokens, analyzes the data, and verifies sustainable reduction activities.
The Notary Oracle verifies external carbon emission and offset data through aggregation to ensure data integrity, then brings it to the blockchain for tokenization.
The Process of the Notary Oracle
[ STEP 1 ] Verification Proposal Request a verification proposal from the chain RPC client and receive the corresponding response.
[ STEP 2 ] Aggregation Aggregate carbon emission and offset data to verify its integrity.
[ STEP 3 ] Signature The data provider and the chain RPC client operator sign the data to complete the notarization.
[ STEP 4 ] Verification Completion During data transmission, use the notary signature key to prove the data's integrity on the blockchain.
[ STEP 5 ] Data Token Minting The operator tokenizes the data through a data message.
Current: Professor at Seoul National University, School of Business
Former:
Associate Dean, Seoul National University, School of Business
Associate Dean, Seoul National University, Graduate School of Business
Director, Seoul National University Institute of Labor Relations
President, Korean Academy of Business Ethics
Education: Graduated from the Department of Business Administration, Seoul National University
Current: CFO and Executive Vice President of Management Support, DI Corporation
Former:
Samsung Group, various foreign banks including btc, SK Securities; roles included Manager, Marketing Officer, FX Trader, and Head of International Finance Team
Climo AI is an advanced artificial intelligence system designed to track, quantify, and analyze carbon emissions based on chemical reactions and combustion processes. This system systematically learns elemental symbols, combustion reactions of chemical compounds, mass changes, and environmental factors, enabling precise calculations of carbon emissions.
CaaS (Carbon as a Service) is an innovative platform that enhances the management and transparency of carbon credits. It connects carbon emission and credit data providers, verification agencies, exchanges, and carbon credit retirees, building an ecosystem for carbon emission reduction and sustainability.
Vice President, Korean Academy of Management
Carbon Emission and Credit Data Providers These are entities that generate carbon credits through carbon emission reduction activities. They supply the market with reliable carbon credits based on verified actions.
Verification Agencies Verification agencies ensure the accuracy and trustworthiness of carbon credits. They evaluate the validity of carbon emission reduction activities and verify the quality of the credits.
Carbon Credit Exchanges Carbon credit exchanges act as platforms that connect buyers and sellers of carbon credits. They provide a fair and transparent trading environment and facilitate the distribution of credits.
Carbon Credit Retirees Carbon credit retirees are entities, such as companies or organizations, that retire carbon credits to achieve net-zero emissions. They participate in offsetting carbon emissions by retiring credits.
AI Service (AIaaS: AI as a Service) AIaaS automates carbon credit management and decision-making processes while providing predictive data. This enables market analysis and efficient resource allocation.
Explore Service (EaaS: Explore as a Service) EaaS analyzes and visualizes data to deliver insights and trends in the carbon credit market. It helps users clearly understand the outcomes of carbon reduction activities.
Blockchain Service (BaaS: Blockchain as a Service) BaaS utilizes blockchain technology to securely and transparently record transaction histories. It ensures data integrity and enhances the security of transactions.
IoT Service (IoTaaS: IoT as a Service) IoTaaS collects and manages real-time carbon emission data using IoT devices. This enables data-driven validation of carbon reduction activities.
Platform Service (PaaS: Platform as a Service) PaaS provides a modular platform for developing and deploying custom carbon credit applications. It supports flexible infrastructure to meet diverse user needs.
Transparency and Trustworthiness Blockchain technology ensures the security and immutability of data.
Scalability IoT and AI-based technologies enable a scalable carbon management ecosystem.
Accuracy Real-time data collection and validation support precise records of carbon emission reductions.
Automation AI automates decision-making processes and enhances overall efficiency.
GESIA aims to build an integrated ecosystem that manages the issuance, verification, trading, and retirement of carbon credits on a single platform.
[ 1st Learning Phase ] Calculates chemical reactions and combustion values based on elemental symbols. In the initial stage, the system estimates emissions using the basic composition and reaction equations of the chemicals contained in the fuel.
[ 2nd Learning Phase ] Calculates the combustion reactions and resulting products of chemicals. By analyzing the substances generated during combustion and their masses, the system produces more detailed emission calculations.
[ 3rd Learning Phase ] Learns the relationship between mass and combustion values based on the law of conservation of mass. This phase clarifies the relationship between the input mass of fuel and the total mass of emissions.
[ 4th Learning Phase ] Learns the combustion characteristics according to the state of matter (solid, liquid, gas). The system increases calculation accuracy by reflecting differences in the physical state of the fuel and combustion reaction rates.
[ 5th Learning Phase ] Analyzes changes in combustion values due to external environmental factors (temperature, humidity, altitude, etc.). This phase studies how changes in real-world conditions affect combustion efficiency and emissions, providing more realistic results.
[ 6th Learning Phase ] Learns the variations in emissions based on user habits (e.g., driving patterns, fuel usage methods). This enables the delivery of personalized carbon emission management solutions.
Climo AI goes beyond simple emission factor-based calculations by incorporating the chemical composition of the fuel, combustion conditions, and the mass of the resulting products to precisely calculate emissions.
Example: Combustion of Methane (CHâ‚„)
When 1 mole of methane (16g) combusts, it releases 44g of carbon dioxide (COâ‚‚). Using this, Climo AI accurately determines the relationship between the amount of fuel burned and the actual amount of carbon emitted.
Climo AI integrates IoT sensors, vehicle data, and environmental data to calculate and predict emissions in real-time. This enables users to immediately check emissions under specific conditions and take necessary actions when required.
Key Data It utilizes data such as driving distance, speed, RPM, fuel consumption, temperature, humidity, and altitude. This allows for emission calculations that reflect actual operating environments.
Application of Results Climo AI analyzes emissions by incorporating changes in combustion conditions and external environmental factors. For instance, it accounts for reduced combustion efficiency caused by lower oxygen levels in high-altitude areas.
Climo AI evolves through self-learning based on accumulated data, improving its calculation accuracy and reliability over time. It starts with a simple model but gradually integrates precise chemical reaction models and AI-based analysis to address complex combustion conditions and their relationship with emissions.
Current:
Chief Visionary Officer (CVO) at Gesia Platform
Co-Chief Executive Officer at Green Social Wave
Outside Director at On The Border
Former:
President at Taemujin Investment Korea
President at HS Venture Capital
President at Il Mare
Current:
Currently studying at Columbia University in the USA
Fashion Model
Engaged in social activities related to fashion and the environment
Current:
Co-founder and Vice President at ITSEN Group
Former:
CEO at Open Communication
Carbon neutrality is an essential goal in addressing climate change and one of the most pressing challenges for the global community. As industrialization and urbanization accelerate, greenhouse gas emissions continue to rise, necessitating innovative approaches to manage and reduce them.
Climate change, driven by greenhouse gas emissions, is accelerating global warming and causing severe impacts on ecosystems and humanity.
Former:
Hosted exhibitions at Saatchi Gallery in London and Lotte Gallery
CEO at M31 Andromeda
CEO at The TUC
Key Sources of Emissions: Industrial activities, energy consumption, agriculture, and transportation.
Key Issues: Accurate measurement of carbon emissions, certification of reduction activities, and lack of transparency in credit trading.
The international community has established carbon reduction targets through the Paris Agreement and strives to enhance sustainability through global initiatives like RE100. However, existing systems still face significant limitations in terms of transparency and reliability.
Blockchain is an innovative technology that provides data transparency and traceability, maximizing the effectiveness of carbon emission management and reduction activities.
Data Transparency: Carbon emission, reduction, and burning activity data are recorded on the blockchain, preventing any manipulation.
Traceability: The issuance, trading, and burning of all carbon credits can be tracked in real-time.
Burn Data Management: The burning of carbon credits is recorded on the blockchain to ensure permanent removal, serving as proof of Net Zero achievement.
GESIA is developing a Layer 3 blockchain platform designed to efficiently manage carbon emission data and revolutionize the trading and burning of carbon credits.
The key objectives are as follows:
Transparent Carbon Management : Record and disclose carbon emissions, burning, and reduction data in real-time.
Carbon Credit Burning : Permanently retire carbon credits used through trading and absorption activities by burning them, preventing double usage and providing proof of Net Zero achievement.
Net Zero Consensus Algorithm Application : Ensure the reliability of carbon emission data and achieve carbon neutrality through reduction and burning activities.
Integration with RE100 Projects : Verify and manage renewable energy-based reduction activities on the blockchain.
Carbon credit burning is a critical process for achieving carbon neutrality.
Burning provides the following benefits:
Permanent Carbon Credit Retirement: When a credit is burned, its rights are permanently revoked, and it is recorded as proof of Net Zero.
Enhanced Transparency: Burning records are registered on the blockchain, ensuring the reliability of carbon neutrality activities.
GESIA optimizes the carbon credit burning process through a consensus algorithm, recording all burning data on the blockchain to maximize the transparency of Net Zero achievements.
GESIA Layer 3 platform goes beyond a simple carbon emission management system, offering a comprehensive ecosystem that includes carbon credit trading, burning, and reduction. GESIA key roles are as follows:
Environmental Protection: Deliver tangible carbon neutrality effects through the burning of carbon credits.
Social Responsibility: Strengthen global partnerships by fostering a transparent and reliable ecosystem.
Economic Value Creation: Enhance market value by streamlining carbon credit trading and burning processes.
GESIA leverages blockchain layer technology to accurately manage carbon emission and reduction data while supporting transparent trading and the permanent retirement of credits.
Emission authentication is the process of verifying entities that provide emission data and those who evaluate emission reduction data.
Data Provider Authentication
Verifies and validates the identity of the entity providing emission data.
Grants verified providers the authority to submit emission data.
Emission Reduction Evaluator Authentication
Verifies and validates the identity of the evaluator reviewing submitted emission data.
Evaluators objectively review and approve the accuracy and effectiveness of the submitted reduction data.
Offset authentication is the process of verifying entities that provide offset data and those who evaluate offset data.
Data Provider Authentication
Verifies and validates the identity of the entity providing offset data.
Grants verified providers the authority to submit offset data.
Offset Data Evaluator Authentication
Verifies and validates the identity of the evaluator reviewing submitted offset data.
Evaluators objectively review and approve the accuracy and carbon absorption data provided.
Transaction authentication is the process of verifying entities involved in issuing or transacting carbon credit token ( extended token ).
Issuer Authentication
Verifies and validates the identity of the entity responsible for issuing and distributing carbon credit tokens.
Grants verified issuers the authority to issue and distribute carbon credit tokens.
Transaction Authentication
Verifies and confirms the identity of entities involved in carbon credit token transactions.
Grants authenticated entities the authorization to carry out carbon credit token transactions.
GESIA technology and research drive digital innovation in carbon management and reduction activities, integrating blockchain, artificial intelligence (AI), and Internet of Things (IoT) technologies to build a unified platform focused on creating a sustainable future.
Blockchain-Based Carbon Management
GESIA leverages Carbon SEED to convert carbon emission data into digital tokens, enabling recording, verification, and tracking on the blockchain.
Smart contracts are utilized to automatically verify emission and offset activities, streamlining the issuance of carbon credits.
AI-Powered Carbon Data Analysis
Predictive modeling will be employed to analyze emission data and forecast the effectiveness of reduction activities.
A real-time decision-making support system will be developed to allow AI algorithms to recommend optimal reduction strategies and resource allocation.
Pattern recognition functions will be applied to automatically detect inefficiencies in carbon emission activities.
IoT and Real-Time Data Integration
IoT devices will be utilized to collect real-time carbon emission data, which will be synchronized with the GESIA blockchain.
By combining IoT and AI, the system will automatically process and analyze the collected data in real time, establishing a comprehensive and efficient analysis framework.
Development of AI-Powered Carbon Reduction Models
GESIA is researching AI-based carbon reduction models to quantitatively evaluate the correlation between offset activities and emission data.
Machine learning has been utilized to predict the feasibility of achieving net-zero and to design optimized reduction strategies.
Research on Global Standard Compliance
GESIA plans to develop processes for verifying carbon data and issuing credits based on international standards, such as UNFCCC and ISO.
Net-Zero Algorithm Research
GESIA is designing a net-zero algorithm that integrates AI and blockchain to manage emissions and offsets comprehensively.
Through data-driven analysis, the system has been implemented to enable companies and governments to assess and manage their carbon-neutral status in real time.
Building an Integrated Carbon Management Ecosystem
GESIA has designed an integrated platform that connects emission data providers, verification agencies, carbon credit exchanges, and offset activity managers.
Enhancing Data-Driven Decision-Making with AI
GESIA plans to utilize AI technology to automatically analyze collected data, enabling companies and governments to make efficient and informed decisions.
Developing Technologies for Sustainability
By integrating blockchain, AI, and IoT technologies, GESIA has enhanced the efficiency and reliability of carbon reduction activities.
Lee Jongsub
Current:
Professor, Seoul National University School of Business
Director, Korean Securities Association / Korean Finance Association
Fiscal Policy Advisory Committee Member, Ministry of Economy and Finance
Member, Public-Private Joint Task Force on Digital Assets
Asset Management Committee Member, Government Employees Pension Service
Shin Myungho
Current: Specialist, Hyundai Motor Securities
Former:
Head of Investment Banking, Yuanta Securities
Executive Director, Hana Financial Investment
Director, DB Financial Investment
Director, Hyundai Motor Securities
Yoon Seokbin
Current:
Professor, Sogang University Graduate School of Information & Communications
Director, Korean Blockchain Society
Blockchain Technology Advisor, NIPA
Chief Legal Consultant, D’Light
Current: Partner, Nautic Capital Korea
Former:
Managing Director, Alchemist Capital Partners Korea/L&S Venture Capital Korea
Partner / Head of Investments, Lighthouse Combined Investment Korea
Advisor, Financing & Business Development, AnaPass, Inc. Korea
MBA Graduate, Yale University
Jin Hyunmi
Current:
Chairman, Artmia Foundation
Vice Director, Korean Peninsula Research Center, Peking University
Committee Member, Beijing Forum Organizing Committee
Minting Chain
Ethereum Mainnet
Smart Contract Address
0x719DeB67fEC9b4C7233B0cF6415F5dC80b6c62d3
Total Supply
5,000,000,000
Full Name
Net Zero Climate
Symbol
NZC
Decimals
18
Ecosystem Reserve
50%
2,500,000,000
Founder & Team
10%
500,000,000
Marketing
5%
250,000,000
Partnership
Current : CEO, Gesia Platform
Former
CEO, Spectrum Company
Vice President, JOH Inc.
Director, Seumi & Toos
Director, Il Mare Inc.
Bachelor in Oriental Painting, Ewha Womans University, Gana Art Center
Current : Vice Chairman , Gesia Platform
Former
Representative of the Korea Branch, China Light Industry Enterprises Association
Representative of the Korea Branch, China Plastic Surgery Association, China Medical Group
Current : CMO, Gesia Platform
Former
CEO, Treeit Jeju Inc.
CBO - Head of ESG, Hancom Frontis Inc.
Current
Ambassador, Tokyo
CRO, DESAVO (Global)
Former
Current : CKO, Gesia Platform
Former
Advisor, Seoul Blockchain Governance Team (2019)
Winner, Binance SAFU Hackathon (2019)
Current : Lead Researcher, Gesia Platform
Former
Developer, Vehicle Infotainment Systems, LG Electronics (2019-2020)
Developer, Vehicle Cluster Applications, LG Electronics (2017-2019)
Current : Senior Researcher, Gesia Platform
Former
Senior Researcher, Backend and Infrastructure Development, Synaptic Wave
Supervisor, Full-stack Development, TechCode
Current : Supervisor, Gesia Platform
Former
Developer, Wafflestay Wallet
Developer, Golf Membership NFT
Current : Supervisor, Gesia Platform
Former
Developer, Reservation and Search API, Wafflestay
Developer, Web Services, Wafflestay
Developed smart contracts for:
ANIVERSE NFT Market (2021)
ARTKOREA NFT Market (2021)
Paygete KYC Blockchain Wallet (2022)
Backend development for:
ANIVERSE NFT Market (2021)
ARTKOREA NFT Market (2021)
Paygete KYC Blockchain Wallet Backend (2022)
A mechanism designed to transparently manage carbon reduction and offset processes. It verifies and records carbon credits, reduction activities, and offset actions within a blockchain environment.
Carbon Data Collection Each participant collects data on carbon emissions from various sources such as energy consumption and industrial activities, carbon reductions achieved through renewable energy use or energy efficiency improvements, and carbon absorption through natural or artificial carbon sequestration activities.
Carbon Data Verification Carbon emission, reduction, and absorption data undergo an automated notarization process through a notarization engine before being recorded on the blockchain. This process ensures accuracy, removes incorrect or invalid data, and only records verified data in the system. This enables transparent access for all participants and serves as the foundation for forming consensus.
Consensus Formation Verified carbon data is tokenized and issued as data tokens, forming reduction and offset consensus through a consensus algorithm.
The burn consensus refers to the process of using carbon credit tokens to burn carbon emission tokens. This process is only possible using carbon credit tokens issued based on verified carbon absorption data.
Carbon Emission Tokens Carbon emission tokens are issued as verified tokens based on notarized data through a notarization engine.
Purchasing Carbon Credit Tokens To offset carbon emission tokens, participants purchase carbon credit tokens.
Carbon Burning
Carbon emission tokens can only be burned using carbon credit tokens.
The carbon reduction consensus is a process for designing and implementing strategies to reduce carbon emissions. This consensus enables reducers to determine practical methods for decreasing emissions and ensures their effective implementation.
Identifying Emission Sources Emission sources that provide carbon emission data are identified, and the emissions from various sources, such as energy consumption, industrial processes, and transportation, are measured.
Setting Reduction Pools Based on the analysis, pools are established to efficiently reduce carbon emissions. If the amount of emission tokens exceeds the target during the designated period, the pool is considered to have failed in its reduction efforts.
Tracking and Verification When reduction targets are met, all transactions from the creation of the reduced emission tokens to the present are tracked and verified. Subsequently, these tokens are issued as carbon credit tokens. Reducers are rewarded for these activities by becoming the owners of the issued carbon credit tokens.
Representative of the Korea Branch, China Private Chinese Medicine Association
Vice Chairman, China Zhongnan / Taqian Franchise Group
Korea Representative, China Central Enterprise Defense - QR, NFC
Representative, Hong Kong LOGOS & Huain Media
Chairman of the Korea Organizing Committee, World Entrepreneurs Federation
Korean Representative, China's Belt and Road International Youth Corps
Korean Representative, UN China Branch Youth Leader
President of Minghui, Asia Wisdom Women's Association
Representative of the Korea Branch, China Asia-Pacific Film Research Institute
Former Vice Principal of the International Department, Peking University Affiliated Primary, Middle, and High School
Former Deputy Director, Cultural Industry Research Institute, Peking University
Founding President, Korea Federation of Chinese Students and Scholars Associations (9th in Beijing)
CSO, MIJ Inc.
K Diaspora Alliance
Specialist Member, Korea Digital Wellness Association
Director, Companion Family Enjoyment Social Cooperative
Director, Deutsche Bank (New York)
Vice President, Credit Suisse (New York)
AB in Government and International Political Economics, Harvard University (1996)
JD, Columbia Law School (2003)
MBA, Columbia Business School (2003)
Designer, Oracle Perceptron (2020)
Designer, Multi-Cross Chain (2020)
Winner, Binance Hackathon (2021)
Winner, Netflix NFT, Chainlink Hackathon (2021)
Participant and Winner, Dcentral Miami (2021)
Developer, Vehicle Cluster Middleware, LG Electronics (2014-2017)
Developer, Mobile (GSM) Applications, LG Electronics (2006-2013)
Supervisor, Full-stack Development, Hivelab
Developer, Accommodation Voucher NFT
Maintenance, KASKO Steel System
VIW NFT Authentication Smart Contract (2022)
VIW NFT Authentication Backend (2022)
Participants requesting the burn act as carbon emission proof proposers and initiate the verification process. During the verification, all transactions from the creation of the carbon emission tokens to the present, as well as all transactions from the issuance of carbon credit tokens to the present, are reviewed.
Once verification is complete, the carbon emission tokens and their corresponding carbon credit tokens are burned.
Burned carbon credit tokens are recognized as achieving carbon neutrality, and this status is rolled up from the L2 chain to the L1 chain for recording.
Deploy Type
ERC20
Github URL
10%
500,000,000
Foundation & Ecosystem Operations
5%
250,000,000
Advisor
5%
250,000,000
Token Sales
15%
750,000,000
