# Introduction ## About TCI Commencing its journey in 2020 as a student-led initiative at the National University of Management, Faculty of Digital Economy in Cambodia, the Trash Cleaning Incentive (TCI) project was conceived with a paramount focus on addressing multifaceted environmental issues encompassing waste management, societal attitudes, and governmental policies. Recognizing the inadequacy of existing models in tackling challenges stemming from the lack of a robust rewarding mechanism, transparency, and a digital platform, the project discerned a crucial need to redefine the approach. Consequently, the TCI project resolved to forge ahead by leveraging the potential of Web3 and blockchain technology, laying the foundation for a transformative digital platform that not only addresses the deficiencies of the current environmental paradigm but also aims to instill motivation within individuals to actively participate in and contribute to environmental activities. ## What is TCI? TCI is a decentralized sustainability dApp built on the blockchain for incentivizing the community to participate in environmental protection. TCI allows users to earn rewards while contributing to the environment. ## Our Vision Our goal is to create a decentralized application that helps users **Clean & Earn Rewards**. During the process, communities can earn a token by cleaning through a **Task or Event**, which they can later exchange or trade for money and NFTs. Aside from this, TCI has a larger goal of raising environmental awareness and encouraging real-world sustainable action. TCI will be the first step toward social responsibility in establishing a clean society. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://trashcleaningincentive.gitbook.io/token-v2/introduction.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.