AI-Powered System for Detecting License Plates of Vehicles in Infraction

About​

"Whistleblower" seeks to construct an on-chain verifiable image recognition system utilizing AI algorithms seamlessly operating within the Cartesi virtual machine. The primary objective is to identify license plates of vehicles violating traffic laws, with the identified information securely stored on the blockchain to provide indisputable evidence of the infringement.

To encourage community engagement and knowledge sharing, we provide comprehensive project documentation, open-source code, and pre-built wheels. Leveraging Cartesi's capabilities, our aim is to address real-world challenges with cutting-edge technology, ensuring accessibility and usability through pre-built wheels for easy software installation within the community.

Our proof of concept (PoC) demonstrates the AI-based traffic violation recognition system's capabilities within the Cartesi Machine. The PoC showcases Cartesi's efficacy in executing a trained model utilizing the YOLO object detection algorithm and character recognition systems, enabling real-time license plate identification while excluding the resource-intensive model training phase.

Additionally, we have developed a user-friendly interface seamlessly integrating image input into the Cartesi Machine. This interface streamlines the process of processing and storing images, along with their associated license plate numbers, on the blockchain. Users can effortlessly access this information through a simple GraphQL query to the list of alerts generated by our DApp, exemplifying Cartesi's role in enhancing data accessibility and management.

Our commitment to transparent documentation empowers developers and enthusiasts within the Cartesi community. By openly sharing our findings and experiences, we aim to foster discussions and knowledge-sharing, highlighting Cartesi's potential for diverse applications beyond traffic violation recognition.

What's next​

Looking ahead, our project roadmap includes key steps to further improve the functionality and efficiency of our system:

• Improving character detection algorithms.
• Notification of violations to competent authorities and violators.
• Integration of smart contracts to manage fine payments and ensure a transparent record of transactions in the chain.
• Implementation of an interactive dispute resolution system to address outcome disputes.

Through these future developments, we intend to create a comprehensive and efficient solution for the detection and management of traffic violations, taking full advantage of Cartesi's innovative technology stack.

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