It is Design to search avaliable plants by Scienefic name, common name and in four Ethiopian languages
(Amharic, Afan Oromo, Tigrigya, Somali).
To search a plant wright the name in search engine and hit search butten. it will display the result
No such name found.
Scientific Name
Common Name
Amharic
Afan Oromo
Tigrinya
Somali
Image
Location
Introduction
Ethiopia is one of the most biodiverse countries in the world, home to a vast range of endemic and native plant species. However, accessing accurate and reliable plant identification tools remains a challenge. To bridge this gap, the Flora of Ethiopia Online Identification System aims to provide a digital platform for plant identification using scientific names, common names, and local names. Over time, this platform will evolve into an AI-based plant identification system, enhancing accessibility and accuracy in Ethiopian flora documentation and conservation.
Objectives
Develop an Online Plant Identification System – A web-based tool where users can search for Ethiopian plants by scientific name, common name, or local name.
Build a Comprehensive Flora Database – A well-organized, structured database with taxonomic details, images, and descriptions of Ethiopian plant species.
Enable Multilingual Search – Support plant identification through local Ethiopian languages alongside scientific and common names.
Integrate AI-based Plant Identification – In the long term, incorporate an artificial intelligence system to identify plant species from images.
Support Conservation and Research – Provide accurate data to researchers, students, conservationists, and policymakers.
Enhance Public Awareness – Promote knowledge-sharing about Ethiopia’s rich botanical heritage through an accessible online portal.
Implementation Plan
Phase 1: Database Development & Web Platform Setup
Organize and structure plant data, including taxonomy, images, conservation status, and ethnobotanical uses.
Develop a web-based search interface for scientific, common, and local names.
Implement a user-friendly design for researchers, students, and the public.
Phase 2: AI-Based Identification System
Train an AI model using Ethiopian plant image datasets.
Develop an API for automated plant identification.
Allow users to upload plant images for instant AI-based recognition.
Phase 3: Expansion & Community Engagement
Continuously update the database with newly documented species.
Collaborate with botanical institutions, universities, and conservation organizations.
Enable crowdsourced contributions to improve the plant dataset.
Expected Outcomes
A reliable, user-friendly online plant identification tool for Ethiopia.
Improved documentation and accessibility of Ethiopian flora.
Increased public engagement and awareness of plant biodiversity and conservation.
A foundation for AI-driven plant identification and research in Ethiopia.
Call for Collaboration
We welcome partnerships with researchers, conservationists, universities, and technology experts to contribute data, research, and technical expertise for developing and expanding the Flora of Ethiopia Online Identification System.