Exploring Local Environment - Mobile App
A Solution to Explore Local Georgia Biodiversity
University: Kennesaw State University
Department: CCSE Information Technology
Course: Capstone IT 7993
Instructor: Dr. Ying Xie
Semester: Fall 2023
C-Day Identifier: IT GC-448
Group G01-10 | 10
Team DEZOA members:
Elvin McCray - Team Leader & Image Recognition Lead
Adedunmola Banu – Image capture & processing Lead
David Appah – UI Lead
OV Tran – ChatGPT Lead
Zenya Tucker – Graphical designer & technical writer
Project Introduction
Artificial Intelligence (AI) has emerged as a powerful force in the realm of technology, offering innovative solutions and capabilities across various industries. As it relates to the xNature app, AI plays an essential role in redefining how we interact with and learn from the natural world. This revolutionary technology is connected to enable users with the ability to seamlessly identify and gain insights into the various plant and animal species found in their local environment. By integrating AI, specifically ChatGPT, xNature provides users with a seamless and informative experience, offering widespread details about the species they encounter through the lens of their smartphone camera.
Mission of the project
Our team’s project involved developing a mobile app for informal STEM learning on local biodiversity and environmental issues. Spearheaded by Dr. Ying Xie, a Professor in the College of Computing and Software Engineering (CCSE), the app empowers users to explore and identify native plant and animal species. Utilizing their smartphone cameras, users can seamlessly scan, record, and locate local wildlife. The app integrates AI, including ChatGPT, to provide detailed information about the identified species. Following Dr. Xie’s guidance, a GPS feature has been incorporated, revealing both zip codes and approximate locations of identified species, enhancing the depth and context of user discoveries.
Objective
Our objective is to develop a user-friendly and immersive app to educate users on the rich biodiversity of our planet, offering a seamless experience for identifying and learning about various plant and animal species. We aspire to forge a connection between users and the fascinating world of nature through informative and engaging educational content. The goal is to provide a comprehensive tool that enhances understanding and appreciation for the abundance diversity of life on earth.
Societal Benefits
Empowering local communities, a mobile app promotes informal STEM discovery learning, enhancing climate change awareness. Offering insights into local biodiversity and environmental issues, it cultivates a sense of responsibility. Fostering collaboration, the app transforms users into citizen scientists, contributing to conservation efforts. Ultimately, it empowers locals to protect their environment, creating informed and resilient communities in the face of climate challenges.
Materials and Technologies
OS: Android
Languages: Python 3.10 (KivyMD)
Services: Figman, ChatGPT 3.5 | OpenAI, LangChain | Salesforce - BLIP
IDE: Visual Studio Code
Library: OpenCV2
Project Achievement
App Flow
Image Capture & Recoginition
AI Integration for Knowledge Provision
Graphic Design
by OV Tran
Image Capture Module
Home page
by OV Tran
Image Library Module
Home page
by OV Tran
by OV Tran
by OV Tran
Image Recognition Module
AI Knowledge Module - powered by OpenAI Chat GPT
Home page
by OV Tran
Knowledge Module
AI Chat Module
Deliverables
Weekly status
Weekly status reports from week 3 - week 13
Milestones
Milestone #1
Milestone #2
Milestone #3
Final
Comprehensive system for Minimal Viable Product Roll Out
KSU C-Day showcase
Extended Documentation
Project Plan
Gantt Chart
Weekly status reports
Milestone reports
C-Day Showcase
YouTube Presentation
Team Presentation
App Demo
Conclusion
The app core functions to facilitate user’s discovery of nature include image capturing and processing, image recognition, species identification, related bio-diverse and environmental information in an engaging and friendly manner with learning status and notifications.
Acknowledgment
Dr. Ying Xie, Professor of Computing Science, Kennesaw State University College of Computing and Software Engineering