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 took home an 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 disasters cause more than 15,000 deaths and cost $173 billion annually.
SAS Hackathon participants collaborated online for a month, enhancing their data science skills under the guidance of a SAS mentor. Every team had access to a learning portal and the ability to try SAS technologies such as machine learning (ML), natural language processing, computer vision, data visualization, and Internet of Things (IoT) on SAS Viya, powered by Microsoft Azure.
Over 100 judges recognized international winners across eight industries, six technologies and three regions.
Check out the 2022 SAS Hackathon winners:
The Global Industries Category
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. Record-breaking rain and flooding spurred by climate change battered Sweden last year, fueling Swedbank to create a system that could help.
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 modeling to design an optimization solution that can be implemented just under six minutes and reduce supply issues by more than 90 percent.
Health and Life Sciences:
The Chart Chasers! (US): 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 designed to prevent doctors from being underpaid when mistakes are made in the medical coding process.
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 for the Retail section, Notilyze for Mixed and Manufacturing, and LiveEO for Insurance.
Disaster Response AI (Canada): 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
Internet of Things:
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.
The Positive Thinking Company (Germany/Belgium): Climate change can have an impact on farmers. Additionally, farmers most vulnerable to its impacts can benefit from protective, inexpensive micro-insurance. Using SAS Viya and machine learning technology, The Positive Thinking Company analyzed climate risk in various states in India, then built a tool for at-risk farmers to explore how climate change can affect their livelihoods while looking at how micro-insurance can provide solutions.
Team 4 casting (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-casting deployed ML and visual forecasting to create a system that forecasts expected usage at any given site, potentially saving the telecommunications company millions.
Other winners from the Technologies Category include Funka for Computer Vision, Linktera4Insurance for Decisioning, and The Chart Chasers! for Natural Language Processing.
You can find the full detailed list of winners here.