Machine Learning for sustainability
Machine Learning is a field of Artificial Intelligence that uses statistical techniques to give computers the ability to “learn”. It is a game changing technology, already being applied in many areas including Video & Serious Gaming, Medical Diagnosis, Fraud Detection, Driverless Vehicles and Security Surveillance. For all its benefits, some are also saying it could be a huge threat – with calls for regulation to protect humanity against AI running out of control. We believe it is an important area for the Atos IT Challenge to explore.
We are seeking how Machine Learning can be applied to the topic Sustainability, in which the exploitation of resources, the direction of investments and the orientation of technological development are all in harmony.
The 3 finalists
Farmero
Technische Universitat Berlin
Farmero is an innovative and easy-to-use Application for small farms which delivers up-to-date and reliable disease-risk-assessments.
Sunubus/Weego
Ecole Supérieure Polytechnique de Dakar
Sunubus/Weego is a predictive bus localization app that relies on crowdsourced data and Maching Learning techniques to give its users accurate bus localization and travel times without any formal AVL infrastructure.
binSight
Universidad de Cantabria
binSight aim to reduce food waste and make supply chains smart through various cloud-based services tailored to the needs of catering companies, governments, social entities and compost companies.