AI-based Bonsai Species Classification and Care Recommendation System using YOLO
Bonsai, an ancient art form that blends horticultural precision with artistic expression, poses unique challenges to both beginners and seasoned practitioners due to its species-specific care requirements and intricate maintenance processes. This research introduces an innovative AI-based solution combining YOLOv8, an advanced object detection model, and Google Gemini LLM, to simplify bonsai species classification and care recommendations. The system is designed to accurately identify bonsai species and provide personalized, context-aware guidance on essential care aspects such as watering, pruning, and pest management, while dynamically adapting to environmental and seasonal variations. Featuring an intuitive interface with sub-100ms response times, the proposed solution enhances accessibility and engagement for users of all expertise levels. Testing affirms its capability to improve understanding, usability, and appreciation of bonsai cultivation. Beyond its application in bonsai care, this hybrid AI integration demonstrates the potential for broader adoption in fields requiring precise classification and tailored insights, showcasing a seamless blend of tradition and technology.
Authors
- S Shirly
- K. Ramalakshmi
- Ramarathnam Venkatesan
- Saravana Kumar C S
- Devi Priya V S (ORCID: https://orcid.org/0000-0002-0230-9779)
- G. Naveen Sundar
Institutions
- Karunya University (IN)
- Alliance University (IN)
- Robert Bosch (Taiwan) (TW)
Publication Details
- Published
- 2025-03-19
- DOI
- https://doi.org/10.1109/iciccs65191.2025.10985589
- Primary Topic
- Identification and Quantification in Food
- Type
- article
- Field-Weighted Citation Impact
- 0.00