plant dedector

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  Scan. Diagnose. Heal. Your plant’s personal doctor — now with voice!”

About the Project: Plant Detector

Inspiration As a nature lover and science communicator, I’ve always been fascinated by the diversity of plants around us. I wanted to create a simple, accessible tool that helps people identify plants instantly and learn how to care for them — whether they’re students, gardeners, or just curious minds. How I Built It I built this project using CodePen, combining HTML, CSS, and JavaScript with AI-powered APIs. The interface allows users to upload or describe a plant, and the system returns its name, characteristics, and care tips. I used GPT-based prompts to generate descriptions and Perplexity AI for research support.

What I Learned

• How to integrate AI tools into a front-end project
• How to structure user-friendly interfaces for quick interaction
• How to use Markdown and LaTeX to format technical documentation Challenges Faced
• Ensuring accurate plant identification with limited data
• Designing a clean UI that works well on both desktop and mobile
• Managing API responses and formatting them clearly for users

Bonus: Sample Math Logic To calculate optimal watering frequency, I used a simple formula: [ \text{Watering Interval} = \frac{\text{Humidity Factor} \cdot \text{Soil Type Index}}{\text{Temperature (°C)}} ]

Built With

• css
• html
• javascript
• languages: