Artificial Intelligence and IoT Development Module

Buy Now

AI & IoT Development and Trainer Kit

The AI & IoT Development and Trainer Kit is a comprehensive learning, prototyping, and research platform designed for students, faculty, researchers, startups, and product developers working in the fields of Artificial Intelligence (AI), Internet of Things (IoT), Embedded Systems, Robotics, Industrial Automation, and Smart Agriculture.

The kit integrates both Raspberry Pi Zero 2 W and ESP32 controllers on a single board, enabling users to develop edge AI, machine learning, computer vision, cloud-connected IoT applications, and real-time embedded control systems without requiring multiple development boards. A wide range of onboard sensors, actuators, communication modules, displays, motor drivers, and signal-conditioning circuits are integrated into the trainer kit, allowing users to experiment with real-world engineering applications through a plug-and-play environment.

The kit is ideal for academic laboratories, engineering projects, industrial training programs, hackathons, product development, and research activities involving AI, IoT, and embedded intelligence.

Key Features

Dual-controller architecture with Raspberry Pi Zero 2W and ESP32
Supports AI, Edge AI, TinyML, IoT, Robotics, and AI Agent development
Integrated 20+ onboard sensors and actuators
Built-in Wi-Fi and Bluetooth connectivity
Onboard 0.96-inch OLED display for real-time monitoring
Supports voice AI applications with INMP441 microphone and MAX98357A audio amplifier
Multiple motor control interfaces: DC, Servo, and Stepper Motors
Integrated RFID, RTC, ADS1115, INA219, and Solid-State Relay
Onboard 5V and 3.3V regulated power supplies with LED status indicators
Plug-and-play platform for rapid prototyping and experimentation
Supports cloud platforms, dashboards, and remote monitoring
Compatible with Python, MicroPython, Arduino IDE, and AI frameworks
Ideal for AI Agents, ESP-Claw, AIoT, and Embedded Intelligence applications
Supports 200+ hands-on experiments and projects

Advantages

Combines AI, IoT, and Embedded Systems on a single platform
Eliminates the need for multiple external development boards
Accelerates learning, research, and product development
Suitable for beginners, researchers, and industry professionals
Supports both cloud-based and edge-based AI applications
Cost-effective solution for academic and industrial laboratories
Scalable architecture for advanced projects and research
Enables hands-on learning through real-world applications
Compact, robust, and easy-to-use design
Future-ready platform for next-generation AIoT innovations.

Applications of the Kit

Artificial Intelligence (AI) and Edge AI Development
Internet of Things (IoT) and AIoT Applications
Voice Assistants and Conversational AI Systems
AI Agent and ESP-Claw-Based Projects
Smart Home and Building Automation
Robotics and Autonomous Systems
Smart Agriculture and Precision Farming
Industrial Automation and Industry 4.0 Solutions
Healthcare and Remote Patient Monitoring
Environmental and Weather Monitoring Systems
Energy Monitoring and Smart Grid Applications
Research, Innovation, and Product Prototyping
Engineering Education and Laboratory Training
Startup Product Development and Rapid Prototyping
Embedded Systems and Real-Time Control Applications

Experiments Included with AI & IoT Development and Trainer Kit

The AI & IoT Development and Trainer Kit supports 80+ hands-on experiments covering Embedded Systems, Artificial Intelligence, Internet of Things (IoT), Robotics, Smart Agriculture, Industrial Automation, Cloud Computing, and Edge AI applications. The experiments are structured from beginner to advanced levels, enabling users to progressively build practical skills. The experiment structure is inspired by the Advanced IoT Trainer Kit curriculum available on the PKM SusTech website, and has been updated to match the hardware available in this kit.

A. Raspberry Pi & ESP32 Fundamentals

Setting up Raspberry Pi OS and ESP32 development environment.
GPIO programming using Raspberry Pi and ESP32.
LED blinking and digital output control.
Reading active-high push buttons.
Reading active-low push buttons.
PWM generation using ESP32.
RGB LED color control using PWM.
Analog input measurement using a potentiometer.
Controller-to-controller communication between ESP32 and Raspberry Pi.
Serial debugging and data monitoring.

B. Display and User Interface Experiments

OLED display interfacing.
Displaying sensor data on OLED.
Scrolling text and graphics on OLED.
Creating a menu-driven system using keypad.
Real-time clock display on OLED.
Digital notice board implementation.
Interactive user interface using OLED and keypad.
Displaying cloud data on OLED.

C. Environmental Monitoring Experiments

Temperature and humidity monitoring using DHT11.
Ambient light monitoring using LDR.
Precision light measurement using BH1750.
Soil moisture measurement.
Gas leakage detection using MQ2.
Multi-sensor environmental monitoring station.
Smart weather station with cloud logging.
Environmental data visualization dashboard.

D. Motion, Distance and Position Sensing

MPU6050 accelerometer interfacing.
Gyroscope measurement using MPU6050.
Tilt detection system.
Motion tracking applications.
Ultrasonic distance measurement.
IR obstacle detection.
VL53L0X Time-of-Flight distance measurement.
Smart proximity sensing system.
Gesture-based control applications.

E. Healthcare and Biomedical Experiments

Heart rate monitoring.
SpO₂ measurement.
Real-time health monitoring dashboard.
Cloud-based health data logging.
Wearable health monitoring prototype.

F. Audio and AI Experiments

Audio recording using INMP441 microphone.
Sound intensity monitoring.
Voice command recognition.
Speech-to-text applications.
Audio streaming using Raspberry Pi.
AI-based voice assistant development.
Voice-controlled appliance switching.
Audio classification using Edge AI.
Wake-word detection applications.
Human-machine interaction projects.

G. RFID and Security Applications

RFID card reading.
RFID-based authentication system.
Smart attendance monitoring system.
RFID-enabled access control system.
Cloud-connected attendance system.

H. Motor Control and Robotics

DC motor control using L293D.
PWM speed control of DC motors.
Direction control of DC motors.
Servo motor position control.
Stepper motor control.
Obstacle-avoiding robot.
Line-following robot.
RFID-controlled robotic system.
Smart robotic platform using multiple sensors.

I. Industrial Automation Experiments

Solid-state relay control.
Automated load switching.
Hall sensor-based speed measurement.
Current and power monitoring using INA219.
High-resolution analog acquisition using ADS1115.
Industrial monitoring dashboard.
Predictive maintenance data acquisition.
Smart machine monitoring system.

J. IoT and Cloud Connectivity Experiments

Wi-Fi communication using ESP32.
Bluetooth communication using ESP32.
MQTT-based IoT communication.
Node-RED dashboard development.
ThingSpeak cloud integration.
Google Firebase integration.
AWS IoT integration.
Remote monitoring using web dashboards.
Mobile app-based IoT control.
Real-time sensor cloud logging.

K. Integrated Smart Applications

Smart home automation system.
Smart agriculture monitoring system.
IoT-based weather station.
Smart street lighting system.
Smart parking assistance system.
Air quality monitoring system.
Voice-controlled smart home.
Smart irrigation controller.
Energy monitoring and analytics platform.
AI-enabled surveillance and monitoring system.

L. Advanced AI & Edge Computing Projects

Edge AI deployment on Raspberry Pi.
Sensor fusion using multiple sensors.
Intelligent anomaly detection system.
AI-based predictive monitoring.
Voice-enabled IoT gateway.
Multi-sensor smart decision-making system.
Industrial IoT edge node development.
End-to-End AIoT System: Sensor → ESP32 → Raspberry Pi → Cloud → Dashboard.

AI and AI Agent-Based Experiments

AI Fundamentals and Edge AI

AI-based object classification using Raspberry Pi.
Edge AI inference using TensorFlow Lite.
Image classification using pre-trained neural networks.
Human presence detection using AI models.
Gesture recognition using AI.
AI-based anomaly detection from sensor data.
Predictive maintenance using machine learning.
Activity recognition using MPU6050 data.
AI-based environmental condition prediction.
TinyML deployment on ESP32.

Voice AI Experiments

Wake-word detection using Raspberry Pi.
Speech-to-text conversion using local AI models.
Text-to-speech generation.
Voice-controlled home automation.
Voice-controlled robotic system.
AI voice assistant using Raspberry Pi.
Multi-language voice interaction.
Offline voice command recognition.
Voice-based attendance system.
AI-powered smart speaker development.

AI Agent Experiments

Local AI Agents

Build a personal AI assistant using Raspberry Pi.
AI agent for answering sensor-related queries.
AI agent for controlling connected devices.
AI-powered troubleshooting assistant.
AI laboratory assistant for students.
AI tutor for electronics and programming.
AI-based project recommendation system.
AI-powered documentation assistant.
Local LLM deployment on Raspberry Pi.
AI agent with memory and context awareness.

ESP-Claw Based Experiments

Installation and configuration of ESP-Claw.
Voice-controlled ESP32 using ESP-Claw.
Sensor data access through natural language.
AI agent controlling LEDs and relays.
AI agent controlling DC motors.
AI agent controlling servo motors.
AI agent reading environmental sensors.
AI agent performing actuator automation.
AI-powered smart agriculture controller.
AI-enabled industrial monitoring node.

AI + IoT (AIoT) Experiments

AI-based smart irrigation system.
AI-powered gas leakage detection.
Smart energy monitoring with AI.
Predictive fault detection using sensor data.
Intelligent room occupancy detection.
AI-powered environmental monitoring.
AI-assisted smart greenhouse.
AI-based water tank monitoring.
AI-driven appliance control.
AI-powered smart city monitoring node.

Vision AI Experiments

(Requires USB Camera with Raspberry Pi)

Face detection system.
Face recognition-based access control.
Human detection using AI.
PPE detection for industrial safety.
Object counting applications.
QR code and barcode recognition.
License plate detection.
AI-based attendance monitoring.
Smart surveillance system.
Intruder detection and alert system.

Multimodal AI Experiments

Voice + Sensor Query System.
Voice-controlled dashboard.
AI agent with voice and sensor inputs.
Smart home assistant with speech interaction.
AI-powered industrial monitoring assistant.
Voice-enabled agriculture assistant.
AI chatbot integrated with real-time sensors.
Natural language querying of IoT devices.
AI-powered digital twin demonstration.
Conversational IoT platform.

Generative AI Experiments

ChatGPT-style local assistant on Raspberry Pi.
AI-based report generation from sensor data.
Automatic experiment documentation generation.
AI-generated maintenance reports.
AI-powered troubleshooting chatbot.
Sensor-to-natural-language conversion.
AI-assisted coding helper.
AI-generated IoT dashboard summaries.
Voice-to-action automation using LLMs.
AI-based engineering knowledge assistant.

Advanced AI Agent Systems

Multi-agent smart home system.
AI agent communicating with ESP32 nodes.
Autonomous monitoring and alert system.
AI-based fault diagnosis assistant.
Agentic industrial automation system.
AI-powered laboratory management assistant.
Intelligent energy management agent.
AI-enabled predictive maintenance agent.
Autonomous greenhouse management agent.
End-to-End AI Agent System: Voice → LLM → ESP32 → Sensors/Actuators → Feedback.

Industry 4.0 and Agentic AI Projects

AI-powered SCADA prototype.
Intelligent machine condition monitoring.
AI-driven digital factory demonstration.
Autonomous industrial inspection system.
Predictive maintenance dashboard with LLM.
Industrial AI copilot.
Smart manufacturing assistant.
AI-enabled remote monitoring platform.
Agentic AI for industrial decision support.
Autonomous AIoT ecosystem using Raspberry Pi and ESP32.

Supports 200+ Experiments in Embedded Systems, IoT, AI, Edge AI, TinyML, Voice AI, Generative AI, AI Agents, ESP-Claw, Robotics, Industrial Automation, and AIoT Applications.

Page updated

Google Sites

Report abuse