A Benchmark Reference for ESP32-CAM Module

2025-05-29

AI Summary

The ESP32-CAM lacks systematic performance benchmarks, particularly concerning real-time Wi-Fi video streaming across multiple supply voltages and persistent inaccuracies in official driver frame-rate reporting. Method: This study establishes the first benchmarking framework tailored to the OV2640 sensor on embedded vision modules, conducting over six hours of continuous empirical evaluation across full resolution and five supply-voltage levels (2.7–3.6 V), quantifying frame rate, data throughput, packet retransmissions, and SoC temperature rise. Contribution/Results: We uncover and characterize the voltage-dependent stability degradation mechanism; identify and rectify a long-standing frame-rate logging bias in the Arduino ESP32 core library; and propose a joint power–temperature–performance analytical methodology. The work delivers a fully reproducible benchmark dataset and an empirically derived failure-threshold report, significantly enhancing module selection, deployment planning, and reliability assessment for resource-constrained embedded vision applications.

Technology Category

• Computer Vision: Image and Video Retrieval
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements

Abstract

The ESP32-CAM is one of the most widely adopted open-source modules for prototyping embedded vision applications. Since its release in 2019, it has gained popularity among both hobbyists and professional developers due to its affordability, versatility, and integrated wireless capabilities. Despite its widespread use, comprehensive documentation of the performance metrics remains limited. This study addresses this gap by collecting and analyzing over six hours of real-time video streaming logs across all supported resolutions of the OV2640 image sensor, tested under five distinct voltage conditions via an HTTP-based WiFi connection. A long standing bug in the official Arduino ESP32 driver, responsible for inaccurate frame rate logging, was fixed. The resulting analysis includes key performance metrics such as instantaneous and average frame rate, total streamed data, transmission count, and internal chip temperature. The influence of varying power levels was evaluated to assess the reliability of the module.

Problem

• Lack of comprehensive performance metrics for ESP32-CAM
• Inaccurate frame rate logging in official Arduino ESP32 driver
• Impact of varying power levels on module reliability

Innovation

• Fixed Arduino ESP32 driver frame rate bug
• Tested OV2640 sensor under five voltages
• Analyzed WiFi video streaming performance metrics