Challenge: Use Lidar data of Puerto Rico (after hurricane Maria, 2017) and write an algorithm using AI to find and label on an image (more the better):
- Damaged roads and buildings
- Areas with high risk of landslide
- Areas that are isolated (with no roads connection available in/out)
- Areas in need of communication networks
- Crops and relevant damage to agriculture
- Other relevant features
Requirements
The final submission will be a report containing:
- Approach: the methods you used to identify different items on the lidar data;
- Results: the final images with the labeled features;
- The Script: a Github link to the code you developed and instructions on how to run it;
- Teamwork: the logistics you used to work together while remote;
- Team Composition: the members of your team and their university affiliations.
We will explain the submission with more details during the welcoming session on July 31st.
Prizes
1st Place
$1,200
2nd Place
$1,000
3rd Place
$500
Devpost Achievements
Submitting to this hackathon could earn you:
Judges
Francesca Scire-Scappuzzo
Chair - IEEE GRSS Boston
Paolo Gamba
Professor - Universita di Pavia
Chad Council
Technical Staff - MIT Lincoln Lab
Susan Meerdink
Professor - University of Iowa
Nick Feuer
CTO & Co-Founder - Project Owl
Aaron Greenblatt
Founder & CEO - Westlight AI
Carlos Lopez Martinez
Associate Professor - Universitat Politecnica de Catalunya
Daniela Giordano
Professor of Computer Engineering - Universita’ di Catania, Italy
Veraldo Liesenberg
Ass. Prof. Universidade do Estado de Santa Catarina
John Kerekes
Professor - Rochester Institute of Technology, NY, USA
Rafael Lemos Paes
IEEE GRSS YP Representative, Brazil
Joshua Peeples
PhD Candidate, University of Florida
Dieter Schuldt
Associate Staff - MIT Lincoln Laboratory
Sean Anklam
Research Scientist - MIT Lincoln Laboratory
Judging Criteria
-
Approach - 40%
-
Results - 30%
-
Teamwork - 20%
-
Team Diversity - 10%
Questions? Email the hackathon manager
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