
Artificial Intelligence in Automation
AsK: Entwicklung eines selbst lernenden Assistenzsystems für die ressourceneffiziente Reinigung von Abwasserkanälen
The aim of the project is the development of an assistance system, which supports the operator in such a way to carry out the cleaning of sewer taking into account quality and cost aspects as efficiently as possible. The system should adapt to different environmental conditions and be self-learning. The information gained will be stored for future cleaning operations in a global database and will be available to the vehicles at different locations.
This project is promoted by:
Bundesministerium für Wirtschaft und Energie (BMWi)
Sponsors:
AiF Projekt GmbH
Funding Code: KF2448213KM3
Funding Lines:
Zentrales Innovationsprogram Mittelstand (ZIM)
Stakeholders / Contacts:
Prof. Dr. rer. nat. Oliver Niggemann
Employees:
Dr.-Ing. Peng Li,
Ganesh Man Shrestha, M. Sc.
A Bayesian Predictive Assistance System for Resource Optimization - A Case Study in Industrial Cleaning Process
In: 19th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Sep 2014
Bayesian Predictive Assistance System: An Embedded Application for Resource Optimization in Industrial Cleaning Processes
In: IEEE International Conference on Industrial Informatics (INDIN 2015), Jul 2015
Hybrid Approach Combining Bayesian Network and Rule-based Systems for Resource Optimization in Industrial Cleaning Processes
In: 20th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA2015), Sep 2015
Promoted by

Projektträger
AiF Projekt GmbH