ESP32-S3-WROOM-1-N16R8：AI

on April 22, 2025

Unlocking new potential of AIoT! ESP32-S3-WROOM-1-N16R8 enables edge AI large model applications, NBTC has sufficient stock, limited time discount!

At a time when artificial intelligence and the Internet of Things (AIoT) are deeply integrated, the demand for local AI computing power on edge devices is exploding. As the flagship module launched by Espressif Technology, ESP32-S3-WROOM-1-N16R8 is becoming an ideal choice for the implementation of lightweight AI large models with its neural network accelerator (NPU), large-capacity storage and dual-mode wireless capabilities.

What’s more exciting is that NBTC (National Broadcasting and Communications Commission of Thailand certification) has sufficient stock and the price has dropped directly, helping developers seize the AIoT opportunity!

ESP32-S3-WROOM-1-N16R8: Edge computing power for large AI models

Built-in NPU, accelerated reasoning: Integrated 384KB SRAM + neural network accelerator, supports TensorFlow Lite Micro framework, local AI model reasoning speed increased by 6~10 times, and lightweight models such as voice wake-up and image classification can be easily run.
Actual test case: In smart camera applications, real-time face detection (QVGA resolution) power consumption is as low as 80mW, and response delay is less than 200ms.
16MB Flash + 8MB PSRAM: Massive model storage and cache. 16MB Flash can store multiple pre-trained models (such as MobileNetV2, TinyYOLO), and supports OTA remote upgrades. 8MB PSRAM expands memory to meet the real-time data buffering needs of complex models (such as speech recognition LSTM).
Dual-core 32-bit CPU, flexible task scheduling: main frequency 320MHz, dynamic frequency modulation technology balances performance and power consumption, and adapts to high-load scenarios such as edge federated learning.

Three major AI model application scenarios, how does ESP32-S3-WROOM-1-N16R8 enable?

Industrial predictive maintenance
Vibration sensor + AI model: deployed in motors, bearings and other equipment, real-time analysis of vibration spectrum, predicting fault accuracy exceeds 92%, avoiding downtime losses.
Advantages: local processing of sensitive data, in line with industrial privacy compliance requirements.
Intelligent voice interaction
Offline voice wake-up: integrated WakeNet model, standby power consumption is only 1.2mW, and supports multi-language commands (such as English and Chinese).
Extended application: combined with Alibaba Cloud IoT platform to achieve cloud semantic understanding and create a low-cost voice assistant.
Retail behavior analysis
Camera + customer flow statistics model: Real-time statistics of the number of people entering the store and the length of stay, data synchronization to the cloud to generate heat maps, and optimize product display.
Highlights: Support Wi-Fi/Bluetooth dual-mode, and push personalized coupons to users’ mobile phones simultaneously.