Farming the Future: AI and Automation in Environmental Monitoring

Abstract: The research paper introduces a novel method for monitoring environmental conditions in agricultural environments by integrating AI technologies with IoT infrastructure. It utilizes data from a variety of sensors including those that measure soil moisture, gas levels, and other environmental parameters to provide real-time condition tracking. The system uses an Arduino microcontroller, an ESP module for communication, and the ThingSpeak platform to gather, upload, and manage data from environmental sensors effectively. One of the system's core functionalities is its weather prediction module, developed in Python using a Convolutional Neural Network (CNN) to enable AI-driven forecasting. This module delivers valuable weather insights, supporting informed and proactive farm management. Additionally, the system includes an intuitive web interface that displays real-time sensor readings and predictive analytics, empowering farmers to optimize resource usage and respond effectively to environmental changes.

Artificial Intelligence (AI), Cloud Service Platforms (Thing Speak), Environmental Sensor, Internet of Things (IoT), Smart Farming, Predictive analytics

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