Location

https://ccse.kennesaw.edu/computing-showcase/cday-programs/fall23program.php

Streaming Media

Event Website

https://sites.google.com/view/explore-local-env-mobile-app

Document Type

Event

Start Date

30-11-2023 4:00 PM

Description

Our team assignment for this project was to create a mobile application that offers informal STEM learning about local biodiversity and environmental issues. Dr. Ying Xie, Professor in the College of Computing and Software Engineering (CCSE) is the owner of this project, who also laid out required features and provided necessary information, guidance, and advice for the project development. The core function of this application is to empower users to explore, identify and gain insights into the plant and animal species native to their region. Leveraging the capabilities of their smartphone’s camera, users can effortlessly scan, record, or locate local wildlife and environmental phenomena. To enrich the user experience, the app incorporates AI, notably ChatGPT, which delivers comprehensive information about the identified species. Our team also integrated a GPS feature. This feature will reveal the zip code and provide an approximate location of the identified species’ origin.

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Nov 30th, 4:00 PM

GC-448 Project Title: Discover, Learn, and Protect: A Mobile App for Informal STEM Learning about Local Biodiversity and Environmental Issues.

https://ccse.kennesaw.edu/computing-showcase/cday-programs/fall23program.php

Our team assignment for this project was to create a mobile application that offers informal STEM learning about local biodiversity and environmental issues. Dr. Ying Xie, Professor in the College of Computing and Software Engineering (CCSE) is the owner of this project, who also laid out required features and provided necessary information, guidance, and advice for the project development. The core function of this application is to empower users to explore, identify and gain insights into the plant and animal species native to their region. Leveraging the capabilities of their smartphone’s camera, users can effortlessly scan, record, or locate local wildlife and environmental phenomena. To enrich the user experience, the app incorporates AI, notably ChatGPT, which delivers comprehensive information about the identified species. Our team also integrated a GPS feature. This feature will reveal the zip code and provide an approximate location of the identified species’ origin.

https://digitalcommons.kennesaw.edu/cday/2023fall/Graduate_Capstone/7