[Announcements] SHL Activity Recognition Challenge @HASCA/Ubicomp 2020 (third edition)

[Daniel Roggen]

Dear colleagues,

The Wearable Technologies Lab at the University of Sussex is glad to 
inform you
about the third SHL Activity Recognition Challenge
(http://www.shl-dataset.org/activity-recognition-challenge-2020/).

This follows on our very successful 2018 and 2019 challenges, which saw the
participation of more than 40 teams.

This 2020 edition focuses on recognising 8 modes of locomotion and 
transportation
(activities) in a user-independent manner with an unknown phone 
position. The
goal is to recognize the user activity from data coming from the phone 
of a test
user. The location of that phone is not specified. Training data is 
provided for
a train user, with all the 4 phone positions available. One of these 
position will
be identical to that of the test user.

The dataset used for this challenge comprises 59 days of training data, 
6 days
of validation data, and 40 days of test data.

The participants will have to develop an algorithm pipeline that will 
process the
sensor data, create models and output the recognized activities.

All teams will receive a certificate of participation, and the best 
three teams
will also receive a prize (800£, 400£ and 200£)!

The participants should also write a technical paper explaining their 
methods
and development process, which will be presented at a special session at 
the
HASCA Workshop at Ubicomp 2020 (http://hasca2020.hasc.jp/), and included 
in the
adjunct proceedings.


The timeline of the challenge:

- Registration via email: as soon as possible, but not later than 15.04.2020
- Challenge duration: 05.04.2020 – 15.06.2020
- Submission of predictions deadline: 15.06.2020
- HASCA paper submission: 19.06.2020
- HASCA Workshop presentation: 12. or 13.09.2020 in Cancun, Mexico 
@UbiComp <http://ubicomp.org/ubicomp2020/>/ISWC 
<http://iswc.net/iswc20/> conference


Organizers:
- Prof. Daniel Roggen, University of Sussex (UK)
- Prof. Hristijan Gjoreski, Ss. Cyril and Methodius University (MK)
- Dr. Lin Wang, Queen Mary University of London (UK)
- Mathias Ciliberto, University of Sussex (UK)
- Dr. Kazuya Murao, Ritsumeikan University (JP)
- Dr. Tsuyoshi Okita, Kyushu Institute of Technology (JP)
- Paula Lago, Kyushu Institute of Technology  (JP)

Contact:
All inquiries should be directed to: shldataset.challenge at gmail.com 
<mailto:shldataset.challenge at gmail.com>


-- 
Prof Daniel Roggen
Head of the Wearable Technology Lab
Director of the Sensor Technology Research Centre
University of Sussex, UK

@: daniel.roggen at ieee.org
http: www.sussex.ac.uk/strc/research/wearable | danielroggen.net
skype: droggen

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