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Wartungs- und infrastrukturarme Objektlokalisierung zur Steigerung von Effizienz und Transparenz in industriellen Logistikprozessen mithilfe des maschinellen Lernens in eingebetteten Sensorsystemen

Project Description

WinOSens aims to research and develop ways to combine microcontroller-based sensor modules with machine learning for object localization and self-awareness. Simultaneously, the data read by the sensor nodes and the localization information are transferred to the cloud backend for further processing using Artificial Intelligence. The targeted use-cases include inventory tracking in in-house logistic systems and facilitating Enterprise Resource Planning (ERP) systems.

In this project, The Institute of Telematics primarily focuses on researching and developing machine learning models for low power, low-performance devices such as microcontrollers.

Sponsered by the Federal Ministry of Education and Research

Project Partners