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Comparison of Different Mobile Applications for the Identification of FJWU Flora
Author(s)
Laraib Abbas Khan Department of Biotechnology, Fatima Jinnah Women University,Rawalpindi,Pakistan
Hafsah Bint Ilyas Department of Biotechnology, Fatima Jinnah Women University,Rawalpindi,Pakistan
Laraib Ali Khan Department of Biotechnology, Fatima Jinnah Women University,Rawalpindi,,Pakistan
Anam Nayab Department of Biotechnology, Fatima Jinnah Women University,Rawalpindi,,Pakistan
Naila Safdar Department of Biotechnology, Fatima Jinnah Women University,Rawalpindi,,Pakistan
Azra Yasmin Department of Biotechnology, Fatima Jinnah Women University,Rawalpindi,,Pakistan
Hira Iqbal Department of Biotechnology, Fatima Jinnah Women University,Rawalpindi,,Pakistan
Abstract
-Plant identification is essential for the conservation of biodiversity and satisfaction of the curiosity among people to know about the species in their surroundings. Various mobile applications (apps) have been developed for plant identification. These artificial intelligence-based apps are used by researchers as well as by the general public. Some apps have their database while others store the data of users. This study aimed to compare widely used mobile apps for the identification of Fatima Jinnah Women University (FJWU) diverse flora. Five different apps were compared with Google lens which was used as a standard. Android system and iOS system were the study instruments. A total of 100 different plants including fruits, vegetables, ferns, herbs and trees from different parts of the university were studied using mobile apps. One-way ANOVA was applied to analyze the data for this comparative study. Only one app showed the highest accuracy (90%) of plant identification, and it is the most recommended plant identification app but still, it should be used cautiously and after consultation with the experts. Non-significant results of statistical analysis showed that all the apps were equally effective in plant identification. Hence, all other apps can also be used for plant identification.
Publication Details
Page(s) 0-0
DOI DOI not available
Published Journal: First International Conference on Revamped Scientific Outlook of 21st Century (Abstract Book), Volume: 0, Issue: 0, Year: 2022
Keywords
Artificial Intelligence ANOVA Flora Mobile Applications Plant identification Google lens
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