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This AI Smart Agriculture IoT Kit offers a comprehensive educational platform that introduces students and engineers to the principles of smart farming, IoT connectivity, and environmental automation. Built around the powerful ESP32 Wi-Fi + Bluetooth microcontroller, it demonstrates how IoT technology can monitor and control real-world agricultural environments intelligently.

The kit includes multiple sensors to measure key environmental parameters such as soil moisture, temperature, humidity, light intensity, and water level. These sensors feed data to the ESP32, which processes the information and triggers appropriate actions — activating a water pump when the soil is dry, or turning on a fan when the temperature rises.

All data can be uploaded to the cloud using Wi-Fi communication through MQTT, Blynk, or custom WebServer dashboards. Students can visualize live readings and automate environmental responses remotely, simulating a modern smart farm or greenhouse system.

The OLED display module shows real-time sensor readings, while the relay modules control actuators like pumps or fans based on programmed thresholds. This hands-on experience helps students understand feedback systems, automation loops, and control logic — the same technologies used in industrial IoT solutions.

With support for Arduino IDE, MicroPython, and ESP-IDF, the kit allows both beginners and advanced learners to write IoT programs, manage API communication, and design responsive cloud-based systems. It also introduces AI concepts through predictive analysis and sensor-based decision-making.

Designed for classroom and lab use, the kit features a safe 5V/7.4V power system with overcurrent and reverse polarity protection. Its modular wiring and labeled connectors ensure easy setup and reliable performance during repeated experiments.

From soil irrigation to temperature regulation, this kit demonstrates how technology and agriculture merge through IoT and AI, inspiring students to build smarter, more sustainable systems for the future.

Comprehensive Environmental Monitoring System
Includes soil moisture, temperature, humidity, light, and water level sensors to collect real-time environmental data. Students learn how to process, visualize, and respond to changes using IoT principles and cloud dashboards.

Smart Irrigation and Climate Control
Automatically controls a water pump and cooling fan through relays when environmental thresholds are reached. Demonstrates automation feedback loops and sensor-based control systems used in smart greenhouses.

Cloud Connectivity and IoT Learning
Wi-Fi-enabled ESP32 microcontroller connects to Blynk, MQTT, or custom cloud platforms for data visualization and remote management. Teaches how IoT devices communicate through APIs and real-time data exchange.

Programmable AIoT Platform
Supports Arduino IDE, MicroPython, and ESP-IDF, allowing learners to program data-driven decisions and AI-style predictions based on environmental input. Bridges coding and real-world automation.

STEM + AI Education Integration
Ideal for teaching IoT, environmental science, and smart system design. Builds problem-solving, coding, and analytical skills, while encouraging creativity in sustainable technology projects.

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