Enhancing IoT based Plant Health Monitoring through Advanced Human Plant Interaction using Large Language Models and Mobile Applications

Abstract: This paper presents the development of a novel plant communication application that allows plants to "talk" to humans using real-time sensor data and AI-powered LLMs. Utilizing soil sensors that track moisture, temperature, and nutrient levels, the system feeds this data into the Gemini API, where it is processed and transformed into natural language insights about the plant's health and "mood." Developed using Flutter, Firebase, and ThingSpeak, the app offers a seamless user experience with real-time interaction capabilities. By fostering human-plant connectivity, this system enhances plant care practices, promotes sustainability, and introduces innovative applications for AI and IoT technologies in both personal and agricultural contexts. The paper explores the technical architecture, system integration, and broader implications of AI-driven plant communication.