Project Gallery - JamesGong's Site

 
Hi, I'm Yecheng Gongan Environmental Engineering, AI & Mathematics enthusiast
 

About me
Project FireAIDSS
Project Abstract
Project Gallery
Future plans
Stories from the lab
Project Envision
Project Abstract
IOAI
Other Projects
Rock Band Gallery
Thoughts
Contact
…
- About me
- Project FireAIDSS
  Project Abstract
  Project Gallery
  Future plans
  Stories from the lab
- Project Envision
  Project Abstract
- IOAI
- Other Projects
- Rock Band Gallery
- Thoughts
- Contact

Check out the slides!
These slides reveal how FireAIDSS works, walking through its core technologies and real-world validation. A comprehensive look at the prototype system for next-generation disaster response.
In December 2024, FireAIDSS earned top honors at the National Conference in Wuhan!
These photos capture both the morning Science Fair showcase and my afternoon presentation to the National Committee. Selected among nine projects to represent at the national level, FireAIDSS was ranked top project in the CS track of the China Youth Talent Program, China's ISEF selection program.
Building on our success in Wuhan, FireAIDSS went on to win the Conrad Challenge China in the Energy and Environment track!
These photos showcase our journey to becoming national champions and earning the honor of representing China at the global finals in Houston.
Firing up the engine at the Intelligent Perception Laboratory!
These images and videos showcase the testing process.
Get a glimpse into how we transformed theoretical models into real-world wildfire monitoring technology.
Computer Interface for FireAIDSS
The Control Station can do three things: allow you to configure drone settings and issue flight commands, visualize real-time data and field predictions, and direct the swarm along optimal flight paths.
The swarm in action: a complete experiment
This footage captures a complete FireAIDSS experiment: four drones executing coordinated flight paths while collecting thermal data, successfully reconstructing the simulated physical field with over 94% accuracy in just three minutes.