Raspberry Pi–Enabled Real-Time Optical Image Enhancement and Compression for Resource-Constrained IoT Cameras
Abstract
Internet of Things (IoT) cameras have resource constraints, which continue to be implemented in smart cities, industrial automation, environmental surveillance, and intelligent surveillance. Nevertheless, the lack of computing power, memory, and network bandwidth has a substantial impact on the realtime image quality and efficiency of transmission. The paper describes a Raspberry Pi-based design of real-time optical image improvement and compression framework specifically tailored to small-power IoT camera nodes. The suggested system combines lightweight image enhancement algorithms, as adaptive histogram equalization and noise admissive filtering, and efficient compression methods, such as JPEG and H.264 coding. The entire pipeline is executed and tested on Raspberry Pi platform version with a camera module attached. The experimental findings show that the visual clarity, compression ratio, transmission latency, and energy consumption significantly increase to make the proposed solution relevant in the edge-based IoT vision applications.