Page 14 - Crowdsourcing AI and Machine Learning solutions for SDGs - ITU AI/ML Challenges 2024 Report

Crowdsourcing AI and Machine Learning solutions for SDGs

3.2 Geospatial Artificial Intelligence

Applying Machine Learning to Geospatial
Analysis
The Geospatial Artificial Intelligence Challenge
(GeoAI), now entering its third edition in 2024,
addresses real-world geospatial problems by
applying AI/ML. This competition aims to solve
issues related to the UN SDGs using real-world
data. Participants gain practical experience in
applying AI/ML to geospatial data, tackling
problems such as environmental monitoring,
urban planning, and disaster response. The
challenge promotes innovative solutions that
contribute to sustainable development, offering
prizes, recognition, and certificates to the top
performers.

3.3 tinyML

Applying Machine Learning to Edge Devices

The tinyML Challenge, organized in collaboration
with industry partners, explores the application of
machine learning in the domain of tiny devices
and embedded systems. The second edition of
this challenge in 2023 focused on developing
a Next-Gen tinyML Smart Weather Station that
is cost-effective, low-power, reliable, and easy
to install and maintain. This weather station will
measure various weather conditions, particularly
rain and wind, using tinyML technology.
Additionally, the tinyML Challenge includes
projects on scalable and high-performance
solutions for crop disease detection and wildlife
monitoring. This competition encourages
innovation in environmental monitoring and
agriculture, leveraging the capabilities of tinyML.

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