SAS Hackathon 2022 winners decode real-world problems using data

The teams were tasked with tackling a real-world problem, and the winning teams’ projects ranged from optimizing disaster response to reducing food waste.

One Canadian team was awarded the award. Team Disaster Response AI from Deloitte Canada won the Visual Analytics award for its interactive map visualization rich with disaster insights and predictions to advise the Canadian government on the best ways to allocate relief funds. Globally, natural catastrophes are responsible for more than 15,000 deaths each year and cost $173 billion annually.

SAS Hackathon participants worked together online for a month under the guidance and support of SAS mentors. Each team had access the SAS Viya, powered with Microsoft Azure, learning portal, and the opportunity to test SAS technologies like machine learning (ML), data visualization, natural language processing, and Internet of Things.

Over 100 judges awarded international winners in eight industries and six technologies.

Check out the 2022 SAS Hackathon winners:

The Global Industries Category

Banking:

Green Swedbank, Sweden Team members from Swedbank and KPMG created a dashboard in SAS Visual Analytics to assess flood risk to properties — and price potential losses — for 100-, 200- and 1,000- year flooding scenarios. Swedbank was inspired by the flooding and record-breaking rainfall that hit Sweden last year due to climate change to create a system that could assist.

Energy:

Innova Data Hub (Spain): Madrid was looking to prioritize green transportation and to  improve BiciMAD, the city’s bike service, Innova Data Hub from Innova-tsn compiled datasets on bike usage. The team used predictive modelling and optimization to devise an optimization solution that could easily be implemented in six minutes, and reduce supply issues by more then 90 percent.

Health and Life Science:

The Chart Chasers (U.S.): Team members from InformedHC and Pinnacle Solutions built an automated system to uncover lost revenue for medical providers due to mistakes in the use of the International Classification of Diseases codes. This system was created to prevent doctors being underpaid if mistakes are made during the medical coding process.

Public Sector:

Jakstat (Indonesia): Team Jakstat from StarCore applied SAS and Python to map and optimize the disbursement of COVID-19 financial aid for small to medium-sized businesses, which make up almost 100 per cent of Jakarta’s economy.

Telecom & Media:

Funka (Sweden). To improve the accessibility of web forms for people with and without disabilities, Funka used computer vision, optical character recognition, ML, and test automation to create a solution for website owners to evaluate the accessibility of their forms and automatically apply solutions to any indicated problems just by inputting their site’s URL.

Other winners include Team TrendsPro, Notilyze, Mixed and Manufacturing, and LiveEO, Insurance.

Technologies 

Visual Analytics:

Canada: Disaster Response AI On SAS Viya, a cloud-enabled, in-memory analytics engine that provides analytical insights, Disaster Response AI from Deloitte built an interactive map visualization rich with disaster insights and predictions to advise the Canadian government on how best to allocate relief funds

IoT:

Oges (Singapore/India): Team members from Oges Solutions incorporated SAS Visual Data Mining, ML and Python Libraries to create a hyper-accurate AI-based oil reservoir model, ready to be incorporated by any oil and gas company.

Machine Learning:

The Positive Thinking Company (Germany/Belgium). Climate change can have an impact on farmers. Also, micro-insurance is affordable and can provide protection for farmers most affected by climate change. The Positive Thinking Company, which used SAS Viya, machine learning technology, and machine learning technology, created a tool for farmers at risk to explore how climate changes could impact their livelihoods. It also looked at how micro-insurance could help.

Forecasting:

Team 4-kasting (Norway). To keep its ranking as the fastest mobile network in the world, Telenor Norway requires enough network capacity to be fast while trying to avoid falling into expensive and unsustainable overcapacity. Team 4-kasting used visual forecasting and ML to create a system that forecasts the expected usage at each site. This could potentially save the telecom company millions.

Funka for Computer Vision and Linktera4Insurance Decision Making are some of the other winners in the Technologies Category. Natural Language Processing

You can find the full detailed list of winners here.