# ESP DL Published articles for ESP DL. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Intelligent Robotic Arm Design Based on ESP32-P4 for Industrial Applications DevFeed: [Intelligent Robotic Arm Design Based on ESP32-P4 for Industrial Applications]() Original publisher: [Read original article]() Author: John Lee Published: 2026-01-12T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32-P4](), [Robotics](), [Microcontroller](), [ESP32-C6](), [USB]() Tags: [ai](), [blog](), [esp-dl](), [esp-now](), [esp32](), [esp32-p4](), [kinematics](), [protocol](), [robotic-arm](), [robotics](), [usb](), [visual-detection]() ### AI overview A detailed guide to building an independently controllable robotic arm with the ESP32-P4. It covers onboard kinematics, USB-camera-based color detection, remote control over ESP-NOW, mechanical assembly, motor configuration, vision calibration, and system integration. ### Source excerpt This article demonstrates how to implement an independently controllable robotic arm project based on the ESP32-P4 high-performance MCU. It covers complete kinematics, visual detection, and remote control, showcasing the great potential of ESP32-P4 in industrial applications. ## Touchpad Digit Recognition Based on ESP-DL DevFeed: [Touchpad Digit Recognition Based on ESP-DL]() Original publisher: [Read original article]() Author: John Lee Published: 2025-06-18T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32-S3](), [ESP32-P4](), [Embedded Systems](), [Deep learning](), [Jetson](), [Artificial Intelligence](), [quantization](), [Inference](), [Code]() Tags: [ai](), [applications](), [blog](), [c-plus-plus](), [deep-learning](), [devices](), [edge-computing](), [embedded-systems](), [esp-dl](), [esp32](), [esp32-p4](), [esp32-s3](), [inference](), [neural-networks](), [quantization](), [recognition]() ### AI overview This tutorial demonstrates touchpad-based digit recognition on ESP32-S3 and ESP32-P4 using ESP-DL. It covers touch-data collection and preprocessing, lightweight CNN design, model training and evaluation, quantization, and C++ implementation for model loading and inference. ### Source excerpt This article demonstrates how to implement a touchpad-based digit recognition system using ESP-DL on ESP32 series chips. It covers the complete workflow from data collection and preprocessing to model training, quantization, and deployment, showcasing ESP-DL's capabilities in edge AI applications. ## ESP32-S3 Edge-AI｜Human Activity Recognition Using Accelerometer Data and ESP-DL DevFeed: [ESP32-S3 Edge-AI｜Human Activity Recognition Using Accelerometer Data and ESP-DL]() Original publisher: [Read original article]() Author: John Lee Published: 2023-06-06T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32-S3](), [On-device AI](), [Deep neural networks](), [ESP-IDF](), [Espressif]() Tags: [ai](), [blog](), [edge-ai](), [edge-computing](), [esp](), [esp-dl](), [esp-idf](), [esp32-s3](), [espressif](), [neural-networks](), [recognition]() ### AI overview This tutorial explains how to read accelerometer data and deploy a deep-learning model with ESP-DL on an ESP32-S3 for human activity recognition. It covers prerequisites, ESP-IDF project structure, model definition, layer initialization, and layer construction. ### Source excerpt Edge computing is a distributed computing paradigm that brings computation and data storage closer to the device's location. Edge Artificial Intelligence (edge-AI) is an exciting development within edge computing because it allows traditional technologies to run more efficiently, with higher performance and less power. Trained neural networks are used to make inferences on small devices. ## Hand Gesture Recognition on ESP32-S3 with ESP-Deep Learning DevFeed: [Hand Gesture Recognition on ESP32-S3 with ESP-Deep Learning]() Original publisher: [Read original article]() Author: John Lee Published: 2022-12-02T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32-S3](), [Deep learning](), [Artificial Intelligence](), [ESP-IDF](), [datasets](), [Model Development](), [quantization]() Tags: [ai](), [blog](), [classification](), [deep-learning](), [esp-dl](), [esp-id](), [esp32](), [esp32-s3](), [espressif](), [kaggle](), [quantization]() ### AI overview This tutorial explains how to deploy a deep-learning model for classifying six hand gestures on the ESP32-S3 using Espressif's ESP-DL framework. It covers prerequisites, model development, dataset preparation, train/test/calibration splits, and model quantization. ### Source excerpt Artificial intelligence transforms the way computers interact with the real world. Decisions are carried by getting data from Tiny low-powered devices and sensors into the cloud. Connectivity, high cost and data privacy are some of the demerits of this method. Edge artificial intelligence is another way to process the data right on the physical device without sending data back and forth improving the latency and security and reducing the bandwidth and power. ## August 2021 Newsletter: ESP32 Workshop and Developer Updates DevFeed: [August 2021 Newsletter: ESP32 Workshop and Developer Updates]() Original publisher: [Read original article]() Author: John Lee Published: 2021-08-27T00:00:00Z Content type: article Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32](), [Internet of things](), [ESP-IDF](), [AWS IoT Core](), [ESP DL]() Tags: [aws-iot-core](), [blog](), [esp-dl](), [esp-idf](), [esp32](), [instagram](), [iot](), [newsletter](), [workshop]() ### AI overview This monthly newsletter reports on an ESP32 applications workshop at the Milwaukee School of Engineering and highlights related content on ESP-IDF, AWS IoT Core, ESP-DL, and ESP32-based projects. ### Source excerpt Hi everyone, Earlier this month, a workshop focusing on ESP32 applications took place in the Milwaukee School of Engineering, a non-profit university in Winsconsin, USA. The workshop was run by Peter Haydock, founding director of Gearbox Labs, which produce project-based STEM and STEAM resources. The workshop was part of Building2Learn, which is an innovative program connecting engineering, construction and manufacturing industries to Milwaukee's next generation of talent.