Modernization And Restoration of Old Herbarium Collections in Colleges Using Artificial Intelligence Tools

Herbarium collections serve as vital archives of plant diversity, taxonomy, and ecological history. However, in many colleges, these collections have deteriorated over time due to poor preservation, outdated documentation, and limited accessibility. The integration of Artificial Intelligence (AI) tools offers a promising approach to modernize and restore old herbarium collections. AI-driven techniques such as image recognition, machine learning, and Optical Character Recognition (OCR) can automate specimen identification, enhance digitization, and recover valuable label information from aging records. By converting physical specimens into digital formats, AI facilitates efficient data management, improved accuracy, and linkage with global biodiversity databases. Moreover, predictive analytics supported by AI can extract ecological and biogeographical insights from historical specimens, contributing to climate change and conservation studies. In educational contexts, this technological integration fosters interdisciplinary learning and research, bridging botany with data science. The study highlights the transformative potential of AI tools in preserving botanical heritage, promoting accessibility, and revitalizing traditional herbaria as modern centers of research and education.