AI-Driven IoT-Enabled Precision Agriculture: Optimizing Resource Usage with LoRaWAN and Drone-Based Monitoring

To maximize the use of resources and increases crop productivity, this research proposes an end-to-end IOT-based precision agriculture system with real-time data gathering with the assistance of smart sensors, monitoring with drones, and analytics with AI. The system collects data regarding crop health, weather, and soil moisture through LoRaWAN, a low-power long-range network technology. Such information facilitates predictive decision-making regarding pest control, fertilization, and irrigation. Field trials show a 15% increase in crop yield, a 20% decrease in the application of pesticides, and a 25% decrease in water usage, which demonstrates the effectiveness of the system in resolving critical agricultural problems and ensuring sustainability. This research demonstrates how IoT and AI can revolutionize farming practices today.