Summary of Enhancing Iot Based Plant Health Monitoring Through Advanced Human Plant Interaction Using Large Language Models and Mobile Applications, by Kriti Agarwal et al.
Enhancing IoT based Plant Health Monitoring through Advanced Human Plant Interaction using Large Language Models and Mobile Applications
by Kriti Agarwal, Samhruth Ananthanarayanan, Srinitish Srinivasan, Abirami S
First submitted to arxiv on: 24 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed novel plant communication application enables plants to “talk” to humans by leveraging real-time sensor data and AI-powered language models. A soil sensor tracks moisture, temperature, and nutrient levels, feeding this data into the Gemini API for natural language insights on plant health and “mood.” Developed with Flutter, Firebase, and ThingSpeak, the app offers seamless user experience and real-time interaction capabilities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This innovative system fosters human-plant connectivity, enhancing plant care practices, promoting sustainability, and introducing AI and IoT applications in personal and agricultural contexts. The paper explores technical architecture, system integration, and broader implications of AI-driven plant communication. |
Keywords
» Artificial intelligence » Gemini » Temperature
