A A A+ A++

AI Data Wizard – How Many Landslides?

In last year’s AI Challenge, students made use of machine learning/deep learning in AI for weather forecast, where they experienced how to use technology to solve real-life problems. In Master Code 2019, Hong Kong Education City (HKEdCity), Microsoft, Hong Kong Observatory, Hong Kong Meteorological Society and Civil Engineering and Development Department (CEDD) jointly organise the 'AI Data Wizard - How Many Landslides?’ for Secondary school students. Participants will learn how to select suitable data and analyse using machine learning platforms in order to estimate the number of landslides in certain periods.

Objectives

  1. To empower teachers and secondary school students to make use of machine learning/deep learning in AI
  2. To let students experience how to solve real-life problems using AI
  3. To enhance students’ awareness of the environment and climate change

Target

  • Secondary School Students

 


registration deadline: 25/11

 


Submission deadline: 28 Nov 12:00 Noon

 

Updates

  • The Gear-up Workshop of “AI Data Wizard – How Many Landslides?” Competition is completed. Please go to the "Useful Information" Tab to watch the video review and download the presentation slides
  • The training data set and estimation data set are now available. Please go to the "Useful Information" Tab to view and download.
  • Submission deadline will be postponed to 12:00 Noon, 28 November. Please CLICK HERE to submit your work after registration.

 

Rules & Regulations

  • Each school can form two participating teams maximum, and each team should consist of two to five students. Each student can only participate in one team.
  • The participating teams need to made use of machine learning/deep learning in AI to estimate the total number of landslides in Hong Kong during a few rainstorms in the previous time.
  • Participating teams need to submit the following on or before 12:00 Noon, 28 November:
    • Estimation, AND
    • an introductory PowerPoint (within ten slides) AND
    • an introductory video (within three minutes)
    • to elaborate on how machine learning / deep learning of AI is used in deducing the estimation.
  • Each team can submit once only, no changes can be made after the submission.
  • Submission of any entry indicates that the participant has read and accepted the Rules & Regulations of the competition.
  • The Organisers own the copyright of the awarded entries.
  • The Organisers reserve the right to amend and/or cancel the activities as well as the Rules & Regulations without prior notice.
  • In case of any dispute, the Organisers reserve the right of final decision.

 

Online Gear-up Workshop

  • Target: Teachers and Secondary school students who are interested in joining the Challenge
  • Date & Time: 21 Oct (Sat) 3:30 pm – 5:30 pm
  • Content:
    • Introduction of the Challenge
    • Basic concepts on landslides, slope safety with related meteorological knowledge and data
    • Introduction of Machine Learning and hands-on exposure to Azure ML Studio

Link to the Webinar:

CLICK HERE to join the Webinar on 21 October (Mon) at 3:30 pm. (either computer or mobile devices can be used).
 

**Please create the required account and download the related data before the Webinar. Details as follows:

  1. Create an account

Please CLICK HERE to download and read the Guideline carefully, it includes:

  • Login Guide; participants can choose either way to login:
    1. Guide to activate O365 for education
    2. Guide to activate Teams using personal email
  • How to join Microsoft Teams meeting for the Webinar
  • How to activate ML Studio
  1. Download the data

Please CLICK HERE to download the historical data provided by Hong Kong Observatory Headquarter and Civil Engineering and Development Department (CEDD). Please read the instruction file before the workshop, a detailed explanation will be provided during the Webinar.

 

Co-organisers

Microsoft          香港天文台          

 

The judging panel is formed by professionals from coorganisers and follows the below criteria to carry out the judging:

1 Forecast Accuracy 50%
  • The submitted estimation will be compared with the official record. The closer to the official record, the higher mark one will get.
  • The final score of each team will be obtained after normalisation with all other teams' submissions
2 Application of Data analysis and Computational Thinking 20%
  • Select and use suitable data for analysis, adopt mathematical methods to estimate, e.g. average values, maximum and minimum values, etc.
  • Explain the reason of data chosen.
3 Application of Machine Learning 20%
  • Demonstrate the application of machine learning algorithms, e.g. regression, cluster analysis, etc.
  • Explain the use of algorithms in the work
4 Team Collaboration and Communication 10%
  • Clearly show how the team works together by listing the division of labor, etc.

 

 

1. Available Data

Training Data

Please CLICK HERE to download the historical data provided by Hong Kong Observatory Headquarter and Civil Engineering and Development Department (CEDD) for model training.

Please read the instruction file (AI_data_wizard_training_data_Readme.pdf) carefully for a better understanding of the data. The instruction file is also included in the zipped file.

 

** Estimation Data

Please CLICK HERE to download the estimation data provided by Hong Kong Observatory Headquarter and Civil Engineering and Development Department (CEDD).

Please read the instruction file (AI_data_wizard_estimation_data_Readme.pdf) carefully for a better understanding of the data. The instruction file is also included in the zipped file.

 

Participants can also use other data from HKO and CEDD website, Newspaper, or any other open data or information from the Internet.

 

2. Learning Kit - Landslides and Slope Safety

Please click here to download

 

3. Simple Guide of Machine Learning Studio

Please click here to download

 

4. Gear-up Workshop - Video Review (21 October)

Please click here for the presentation slides of Part 1(Knowledge of Landslides and the introduction of competition data sets) 

Please click here for the presentation slides of Part 2(Machine Learning Studio Hands-on)

 

5. Introductory Workshop - Video Review (28 June)

Part 1

 

Part 2

 

Part 3

 

Awards for 'AI Data Wizard – How Many Landslides?':  

Awards Quantity Prizes
Champion 1 TBC
First Runner-up 1 TBC
Second Runner-up 1 TBC
Merit Awards 5 TBC

 

  • Each participating student who has completed the competition (submitted all the required works) will be presented a certificate
  • Winners will also be presented relative certificates

Winners

Awarded schools will be invited to join the award ceremony held in Learning & Teaching Expo at Hong Kong Convention and Exhibition Centre at 1 p.m. on 12 December 2019.

Award Title School Name Team Members
Champion LPLSS Team 1 GCCITKD Lau Pak Lok Secondary School 李俊華、曾文迪、蘇正樂
First Runner-up The Three Lasallians La Salle College Chio Shing To, Chong Hon Tsun, Cheung Chun Lok, Kwok Long Fung
Second Runner-up St. Mark's Team 1 St. Mark's School Tsang Yi Tung, Ng Hei Wai, Choy Wing Kwan, Wong Ka Yin
Merit Awards 可道AI團隊 Ho Dao College (Sponsored by Sik Sik Yuen) 歐陽文基、黃裕寬、梁恩銘
BHJS Team 1 Bishop Hall Jubilee School Lau Wai Ming, Cheung Kin Ho, Wong Tak Ming Damien, Ng Cheuk Ting, Tong Yee Nam
BHJS Team 2 Bishop Hall Jubilee School Chu Allison Nga Man, Chan Yee Man, Wong Sze Kiu, Wong Yi Huen
Carmel Divine Grace Foundation Secondary School Carmel Divine Grace Foundation Secondary School 林朝暉、劉綽軒、田宇森、蔡承軒