IoT Datathon 2.0

 The Internet of Things (IoT) Datathon is an interdisciplinary competition where students will be given the opportunity to develop IoT applications to solve real-life industry problems. Students will get to work first-hand with industry experts and apply Artificial Intelligence techniques to develop innovative prototype solutions.

Benefits

Competition winners will get the opportunity to commercialise their solutions through a green-lane process to obtain up to 90% seed co-funding, or employment and sponsorship opportunities with participating companies. This enables them to further develop their solutions after the Datathon.

IoT

Participants will receive training and mentorship at an Artificial Intelligence workshop, where they will learn programming concepts, application development and data analysis.

Partner SMEs

There are experienced solution providers across sustainable and integrated urban solutions, ranging from water, waste and energy management, to urban planning. Small and medium enterprises (SMEs) can play a vital and unique role, channelling new innovations and test-bedding innovative urban solutions.

Evercomm

A home-grown firm founded by Ted CHEN, Forbes 30 Under 30 award winner, that harnesses Internet of Things technology and Big Data to help organisations improve energy efficiency for cost savings

Tritech

A leading one-stop water and environmental solutions provider focusing on advanced technology in waste water treatment and winner of Singapore Enterprise 50 (E50) award (2006)

Datathon Challenges

Singapore’s vision is to be a liveable, sustainable and resilient city of the future, and a vibrant urban solutions hub. To help address these challenges, the IoT Datathon 2.0 will focus on partnerships with small and medium enterprises to develop Urban Sustainability solutions. Participants can select from the following problem statements.

Flood

Forecasting local flood events with weather and sensor data

It is becoming more challenging to manage the impacts of increasingly unpredictable weather. Periods of heavy rain have become more common, resulting in more frequent occurrences of flash floods. This could impact resources and daily life, for instance, runoff contamination, property damage, congestion etc. There is hence a growing need for timely and more accurate weather predictions, prevention and / or mitigation systems.

Through this challenge, participants will develop a system for flood prediction. Such a predictive system could be used as an early warning system for flooding, or to run flooding simulations using artificial rainfall data.

Algae

Forecasting algae blooms in rivers / reservoirs

Algae blooms in our reservoirs can compromise water quality. This may have adverse impacts, for instance, fish kills from oxygen depletion, water treatment processing issues, aesthetic issues etc. By being able to predict algae blooms and their causes, preventive and / or mitigation measures can be carried out more effectively.

Through this challenge, participants will develop tools to predict algae blooms and their likely causes, to serve as preventive measures. 

Weather

Optimising power using weather predictive models

Weather data can be used to predict the energy / power consumption of chiller systems, facilitated by accurate modelling of the correlation.

Through this challenge, participants will develop planning tools for performance optimisation of chillers.

Intelligent System

Developing intelligent system diagnostics

Passive sensor data, for instance, power, flow, devices, temperatures etc. can be used to predict potential chiller or device failure.

Through this challenge, participants will develop predictive diagnostics which will accurately pre-empt potential fault scenarios. This reduces downtime and costs.

Timelines

PART 1: WORKSHOP

Registration

Open now till 8 December, 12pm

IoT Datathon 2.0 Launch

11 December, 10:00 am to 12:00 pm

Artificial Intelligence Workshop 

An intuitive approach to deep learning for timeseries forecasting
11 to 16 December, 1:00 pm to 5:00 pm

PART 2: DATATHON

Solutions Development

18 December to 19 January 2018

Demo Day

20 January 2018, 9:00 am to 4:00 pm

Finals

2 February 2018, 2:00 pm to 5:00 pm

Inaugural Datathon

The inaugural Datathon drew 69 teams comprising 220 participants from the Faculties of Engineering, Science, Business, Arts and Social Sciences, School of Design and Environment and School of Computing.

Participating SMEs

NUS students were mentored by industry experts and seasoned programmers to develop new IoT data-driven applications that solved real challenges faced by small and medium enterprises (SMEs).

JKTech
Energtix
Lotus

The winning team, Sababa, developed an algorithm that automates the predictive maintenance of a solar photovoltaic system by analysing data from the inverters. It flags potential failures in advance by learning to recognise root causes, thereby reducing downtime and costs.

“We learnt to be flexible and adaptable. Our initial model was very different from our final product. After wrangling our datasets, we discovered new insights and improved our models.”

“Working on real-life datasets provided great insights on data analytics work.”

Organisers

NUS Science

Supporting Organisation

Spring Singapore

Technical Partner

Terra Weather

Participating Organisations

Evercomm
Tritech

Address
Block S16, Level 5
6 Science Drive 2
Faculty of Science
National University of Singapore Singapore 117546

Email:
murusethu@nus.edu.sg

Business Hours 
Monday to Thursday:
8.30 am – 6.00 pm
Friday:
8.30 am – 5.30 pm

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