Apreetam integrated a FastCV-based hardware abstraction layer for the Canny edge detection API in the espressif/opencv repository, focusing on accelerating image processing for constrained devices. The work involved defining the API surface, specifying kernel size and normalization type support, and establishing constraints for multi-channel input and decimal threshold values. By implementing the HAL-facing function declarations and definitions in C and C++, Apreetam enabled offloading of edge detection to FastCV, reducing CPU usage and increasing throughput for computer vision pipelines. This feature laid the foundation for downstream integration, aligning with performance goals for hardware-accelerated image processing in embedded environments.