SAS Hackathon 2022 Winners Decode Real-World Problems Using Data
This week, SAS announced the winners of its 2022 SAS Hackathon. Among 70 qualified teams from around the world and 50 business case submissions, SAS highlighted 13 teams for innovation using cloud-native SAS Viya artificial intelligence, Microsoft Azure and other technologies.
Teams were tasked with tackling a real-world problem, and the winning teams’ projects ranged from optimizing disaster response to reducing food waste.
A Canadian team won a prize. Team Disaster Response AI from Deloitte Canada won the Visual Analytics award for its interactive map visualization rich in disaster information 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 a year.
SAS Hackathon participants collaborated online for a month, improving their data science skills under the guidance of a SAS mentor. Each team had access to a learning portal and the opportunity to try SAS technologies such as machine learning (ML), natural language processing, computer vision, data visualization and the Internet of Things (IoT) on SAS Viya, powered by Microsoft Azure.
More than 100 judges recognized international winners in eight sectors, six technologies and three regions.
Discover the winners of the SAS Hackathon 2022:
The category of global industries
Green Swedbank (Sweden): Team members from Swedbank and KPMG created a dashboard in SAS Visual Analytics to assess property flood risk – and assess potential losses – for 100-, 200-, and 1,000-year flood scenarios . Record rains and flooding caused by climate change hit Sweden last year, prompting Swedbank to create a system that could help.
Innova Data Hub (Spain): Madrid was looking to prioritize green transport and 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 in less than six minutes and reduce supply issues by more than 90%.
Health and life sciences:
Card hunters! (WE): Team members from InformedHC and Pinnacle Solutions built an automated system to uncover lost revenue for medical providers due to errors in the use of 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): StarCore’s Jakstat team applied SAS and Python to map and optimize the disbursement of COVID-19 financial relief for small and medium enterprises, which make up nearly 100% 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 that allows website owners to evaluate the accessibility of their forms and automatically apply solutions to the problems indicated. simply by entering the URL of their site.
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, Deloitte’s Disaster Response AI has created an interactive map visualization rich with disaster information and predictions to advise the Canadian government on how best to to allocate relief funds
Oges (Singapore/India): Oges Solutions team members integrated SAS Visual Data Mining, ML and Python libraries to create a hyper-accurate AI-based oil reservoir model ready for integration by any oil company and gas.
The Positive Thinking Company (Germany/Belgium): Climate change can impact farmers. In addition, farmers most vulnerable to its impacts can benefit from protective and inexpensive microinsurance. Using SAS Viya and machine learning technology, The Positive Thinking Company analyzed climate risk in various states in India and then created a tool for at-risk farmers to explore how climate change can affect their livelihoods while examining how microinsurance can provide solutions.
Team 4-kasting (Norway): To maintain its position as the fastest mobile network in the world, Telenor Norway needs enough network capacity to be fast while trying to avoid falling into costly and unsustainable overcapacity. The 4-kasting team deployed ML and visual forecasting to create a system that predicts expected usage at a given site, which could save the telecommunications company millions.
Other winners in the Technologies category include Funka for Computer Vision, Linktera4Insurance for Decision Making and The Chart Chasers! for natural language processing.
You can find the complete and detailed list of winners here.