Mobile Flora System

• Main Author: Yew, Chow Sheng
• Format: Final Year Project Report
• Language: English
• Published: Universiti Malaysia Sarawak, (UNIMAS) 2019
• Subjects: QA76 Computer software
• Online Access: http://ir.unimas.my/id/eprint/33974/2/Yew%20Chow%20Sheng.pdf; http://ir.unimas.my/id/eprint/33974/

Sarawak is full of biodiversity. Flora and fauna often play an essential role in developing industry and medical products in Sarawak. To promote the flora industry, natural science like plant science has become one of the basic courses for FSTS, UNIMAS. Although face to face training is provided, the students are facing some difficulties to identify plant species. Hence, support is needed to complement the face to face teaching in plantation study. In this thesis, mobile flora system is proposed to assist students from FSTS, UNIMAS in identifying the plant species in more natural and faster way. With this system, the students can scan and view the plant species without the need for an Internet connection. Students can also view detailed information about the plants being detected. The object detection model will be implemented in the development of system using Tensor Flow Lite. Furthermore, the mobile flora system is integrated with pre-trained database using supervised learning method which means lots of plant’s photos will be uploaded and trained. With this system, it is aimed to allows the students to have a high accuracy in identifying plants.