This paper develops the prototype of an intelligent detection system of electric vehicles (EV) using the YOLOv8 architecture and Internet of Things (IoT) technology. The system aims to automatically detects EVs from video feeds and integrates this data with a dynamic parking tariff system to incentivize EV usage. It provides real-time data to support carbon emission reduction strategies within the Universitas Indonesia campus. System architecture includes a video acquisition module (camera and Raspberry Pi 5), a YOLOv8-based EV detection algorithm, and Google Sheets/Looker Studio for data storage and visualization. Performance evaluation of the YOLOv8 model achieved an F1-Score of 0.91 at a confidence level of 0.731. The dynamic parking tariff was adjusted based on detected EV counts. The system provides actionable information for university management to optimize parking, formulate ecofriendly vehicle policies, and monitor the impact of emission reduction efforts. © 2025 IEEE.