Artificial Intelligence for Digitizing Industry

Risultati finali

Report on HW/SW partitioning and sub-system level key architecture designs (initial report)

T22 Focus is on subsystem level designs and key architectures including AIbased solutions feasible for the use cases Analysis of AI methods and contribution to improve the design flow

Functional requirement and specifications of machinery and industrial equipment

[T1.4] The partners will create a report describing definitions of requirements for a robotic arm, object recognition, sensitive robot skins, and contactless human-machine interaction.

AI for digitizing industry road-mapping requirements

T11 The first report based on the findings from the deliverable D11 presenting the future trends of AI research and innovation and the proposed requirements for roadmap for the AI activities in digitizing industry including analyzing societal and technological challenges trends

Report on IIoT/AI enabled system level platforms

T24 Focus is on system platform integration and interoperability between the underlying platforms Defining conceptual design and interfacing of manufacturing IIoTAI based platforms including integration of AI embedded platforms and AI training platforms integrating the digitizing industry cyberphysical systems CPSs with efficiently use of multiaccess edge computing MEC

Requirements for silicon package fault detection and wafer inspection

[T1.3] In this report, the partners provide a report describing requirements for different approaches on silicon package fault detection and wafer inspection. This includes wafer visual inspection requirements, design of an imaging geometry, an analysis of silicon package fault detection and the AI relevant data structures.

Report on safe and secure end-to-end design methodologies for AI embedded in industrial processes and applications

T25 Reliable communication is required for cooperative functionality Focus is on IIoT low latency communication and distributed sensing and edge computing Environmental aspects for harsh environments will also be covered

Report on HW/SW partitioning and sub-system level key architecture designs (final report)

T22 Focus is on subsystem level designs and key architectures including AIbased solutions feasible for the use cases Analysis of AI methods and contribution to improve the design flow

Requirements for learning systems

[T1.4] In this report the requirements for the implementations of learning systems are described.

Report on hybrid reference system level architecture design for the digitizing industry

T21 Focus is on highlevel AI based system architectures for digitizing industry sectors Different building blocks functions interactions and workflows will be defined based on IIoTAI solutions for seamless integration and scalability

Functional and non-functional requirements for smart robots

[T1.4] The partners will create a report describing definitions of requirements for a robotic arm, object recognition, sensitive robot skins, and contactless human-machine interaction.

Workshop on AI requirements for digitizing industry

[T1.1] Workshop organized with AI stakeholders (ECSEL and external) involved in digitizing industry. The workshop format is organized as a combination of experts’ key notes and brainstorm sessions to discuss the content of AI requirements for digitizing industry, the criteria of selection and present findings from market research reports and questionnaires.

Requirements for autonomous reconfigurable battery systems

[T1.2] A report is created describing the requirements of intelligent energy storage systems.

Final plan and report for use and dissemination of the foreground

T71 T72 Document outlining how the projects aims and results were communicated to the broader public and disseminated within research and industry communities and outlining the path towards commercialization of results after the end of the project

Definition of requirements for AI in transportation

[T1.6] In this report the specifications of AI based AI based MaaS operation concepts and distributed data pipelines are provided.

Report on standardization activities (2nd version)

T73 Document outlining projects standardization strategy and partners standardization efforts in period 2

Report on European ecosystem building and initiatives clustering

T85 This deliverable will provide the achievements in the attempts of making connections with other projects stakeholders and institutions dealing with AI related tasks The synergies as well as complementary tasks will be searched for and monitored so as to provide there clear view on AI roadmapping from the worldwide perspective with the focus on needs of European industry

Definition of real time predictive maintenance

T12 This report will provide data definitions and requirements for realtime predictive maintenance based on knowledge and modelbased reasoning Also a specification for electrical drive diagnostics and requirements for an IoT device enabling humanmachine interaction and change detection are described

Specification of AI supported automotive logistics processes and robotic controlled cell manufacturing

[T1.2] Related to the state of the art and science in this report the specification is presented on the concrete processes of control of logistic systems and robot supporting work systems within the factory. Derived from this, the synergies with other industries and the outlook for the further development of hardware software and method requirements are evaluated.

Final report on standardization activities

T73 Document outlining projects standardization strategy and partners standardization efforts in period 3 This is the final standardization report

Report on standardization activities (1st version)

[T7.3] Document outlining project’s standardization strategy and partners’ standardization efforts in period 1.

Report on requirements and specifications for smarter food and beverage production based on AI-technologies

[T1.5] Defining the requirements and specifications for the food and beverage processing and manufacturing industry use cases. The focus is on exploiting new AI technologies, IIoT devices, and infrastructure to increase quality, productivity, autonomy, safety, etc.

Report on hybrid intelligent system and sub-system level modelling and simulation for integration of AI methods

T23 Focus is on simulation analysis tools identification and concept solution for integration of AI methods on modelling simulation and design across different applications and industries Exploring various ways to combine and integrate different AI technologies by exploiting their strengths to produce hybrid solutions which are more robust flexible and exhibit more desired qualities than the one using either technology alone

Management and Quality Assurance Handbook

[T8.1, T8.2, T8.3] This deliverable will define management processes and rules for the involved partners for the duration of project solution. It will be useful mainly for administrative personnel inside of the project.

Definition of AI technologies and their specific solution requirements to bring it in the industry use

T12 This report shows the different approaches to the use of AI technologies across the different industries which have a demonstrator contribution in the project A new method for evaluating functional requirements for AI solutions is shown and implemented In particular the specific requirements are assessed and presented qualitatively and quantitatively On the one hand for the respective industry and overall industries

Draft plan for use and dissemination of the foreground

T71 T72 Document outlining how the projects aims and results will be communicated to the broader public and disseminated within research and industry communities and outlining the path towards commercialization of results

Specification of FMEA generator and materials simulation algorithms

[T1.3] The partners will define specifications for an AI based FMEA generator and materials simulation algorithms and provide a report.

Network building and AI ECSEL engagement workshop

[T8.5] AI4DI workshop and Webinars to support the network building and creating a dynamic ecosystem of ECSEL AI stakeholders that cooperate closely and support the European dimension of the project.

European AI Conference

[T8.5] AI European Conference organised with the support of AI4DI that will bring together the electronic components and systems, AI, connectivity, IoT/IIoT, edge computing communities to discuss and exchange ideas about challenges, barriers, adoption, best practices on use cases/solutions for digitising industry across industrial sectors.

Project website

[T7.1] Official project’s website with main information about the project, the consortium, and a separate password-protected members data-share section.

Pubblicazioni

Analysis of Randomization Effects on Sim2Real Transfer in Reinforcement Learning for Robotic Manipulation Tasks

Autori: Josifovski, J.; Malmir, M.; Klarmann, N.; Zagar, B.L.; Navarro Guerrero, N.; Knoll
Pubblicato in: IEEE/RSJ International Conference on Intellig ent Robots and Systems (IROS ), 2022
Editore: IROS

ECBA-MLI: Edge Computing Benchmark Architecture for Machine Learning Inference

Autori: Mathias Schneider, Ruben Prokscha, Seifeddine Saadani, and Alfred Höß
Pubblicato in: 2022 IEEE International Conference on Edge Computing and Communications (EDGE), 2022
Editore: IEEE
DOI: 10.1109/edge55608.2022.00016

Acceptance of mobility as a service by car users

Autori: Risto Öörni
Pubblicato in: 14th ITS European Congress, 2021
Editore: ITS European Congress

A Tile-based Fused-layer CNN Accelerator for FPGAs

Autori: F. Indirli, A. Erdem, C. Silvano
Pubblicato in: 2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 2021
Editore: IEE Explore
DOI: 10.1109/icecs49266.2020.9294981

State of Charge Estimation using Recurrent Neural Networks with Long Short-Term Memory for Lithium-Ion Batteries

Autori: Bockrath, S., Rosskopf, A., Koffel, S., Waldhör, S., Srivastava, K., & Lorentz, V. R.
Pubblicato in: 2019
Editore: IEEE
DOI: 10.1109/iecon42759.2019

Interturn short circuit modelling in dual three-phase PMSM

Autori: KOZOVSKÝ M., BUCHTA L., BLAHA P.
Pubblicato in: Proceedings of IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, Numero 2022, 2022, Pagina/e 1 - 6, ISBN 978-1-6654-8025-3
Editore: IEEE
DOI: 10.1109/iecon49645.2022.9968364

Effective Use of BERT in Graph Embeddings for Sparse Knowledge Graph Completion

Autori: Xinglan Liu, Hussain Hussain, Houssam Razouk, Roman Kern
Pubblicato in: SAC '22: Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing, 2021
Editore: SAC

S2ORC-SemiCause: Annotating and analysing causality in the semiconductor domain

Autori: Xing Lan Liu, Eileen Salhofer, Anna Safont Andreu, Roman Kern
Pubblicato in: International Workshop on Edge Artificial Intelligence for Industrial Applications, 2021
Editore: River Publishers

A BERT-Based Report Classification for Semiconductor Failure Analysis

Autori: Corinna Grabner; Anna Safont-Andreu; Christian Burmer; Konstantin Schekotihin
Pubblicato in: 2022
Editore: ISTFA 2022 - International Symposium for Testing and Failure Analysis
DOI: 10.31399/asm.cp.istfa2022p0028

Report Classification for Semiconductor Failure Analysis

Autori: Frederik Platter; Anna Safont-Andreu; Christian Burmer; Konstantin Schekotihin
Pubblicato in: 2021
Editore: Electronic Device Failure Analysis Society ASM International

Integrating multiple observation sets into consistency-based diagnosis

Autori: Franz Wotawa
Pubblicato in: International Workshop on Principles of Diagnosis (DX), 2021
Editore: HSU-HH

Using Ontologies in Failure Analysis

Autori: Anna Safont-Andreu; Christian Burmer; Konstantin Schekotihin
Pubblicato in: 2021
Editore: Electronic Device Failure Analysis Society ASM International

Detection of the Interturn Shorts of a Three-Phase Motor Using Artificial Intelligence Processing Vibration Data

Autori: DOSEDĚL M., KOPEČNÝ L., KOZOVSKÝ M., HNIDKA J., HAVRÁNEK, Z.
Pubblicato in: Proceedings of the 2022 20th International Conference on Mechatronics - Mechatronika (ME), Numero 2022, 2022, Pagina/e 234 - 238, ISBN 978-1-6654-1040-3
Editore: IEEE
DOI: 10.1109/me54704.2022.9982824

On the Use of Available Testing Methods for Verification & Validation of AI-based Software and Systems

Autori: Franz Wotawa
Pubblicato in: Proceedings of the Workshop on Artificial Intelligence Safety 2021 (SafeAI 2021) co-located with the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), Numero February 8, 2021, 2021, Pagina/e 6
Editore: CEUR Workshop Proceedings (CEUR-WS.org)

Graph Neural Networks for Relational Inductive Bias in Vision-based Deep Reinforcement Learning of Robot Control

Autori: Oliva , M., Banik, S., Josifovski, J., & Knoll,
Pubblicato in: International Joint Conference on Neural Networks (IJCNN) 2022, 2022
Editore: IJCNN

A Fully Automated Process for Semiconductor Technology Identification

Autori: Matthias Ludwig, Bernhard Lippmann, Ann-Christin Bette, Claus Lenz
Pubblicato in: 2021
Editore: Research Gate

Impact of Training Instance Selection on Domain-Specific Entity Extraction using BERT

Autori: Eileen Salhofer, Xing Lan Liu, Roman Kern
Pubblicato in: North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop, 2022
Editore: NAACL

Deploying Deep Neural Networks on Edge Devices for Grape Segmentation

Autori: Roesler, M., Mohimont, L., Alin, F., Gaveau, N., Steffenel, L.A. (2021). Deploying Deep Neural Networks on Edge Devices for Grape Segmentation. In: Boumerdassi, S., Ghogho, M., Renault, É
Pubblicato in: International Conference on Smart and Sustainable Agriculture, 2021, ISBN 978-3-030-88258-7
Editore: Springer
DOI: 10.1007/978-3-030-88259-4_3

Continual Learning on Incremental Simulations forReal-World Robotic Manipulation Tasks

Autori: Josip Josifovski, Mohammadhossein Malmir, Noah Klarmann, Alois Knoll
Pubblicato in: 2020
Editore: Semantic Scholar

Speed Control of PMSM with Finite Control Set Model Predictive Control Using General-purpose Computing on GPU

Autori: Michal Kozubik, Pavel Vaclavek
Pubblicato in: IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society, 2020, Pagina/e 379-383, ISBN 978-1-7281-5414-5
Editore: IEEE
DOI: 10.1109/iecon43393.2020.9254381

AI-Based Edge Acquisition, Processing and Analytics for Industrial Food Production

Autori: Ovidiu VERMESAN, Ronnie Otto BELLMANN, Roy BAHR, Jøran Edell MARTINSEN, Anders KRISTOFFERSEN, Torgeir Hjertaker , John Breiland, Karl Andersen , Hans Erik SAND and David LINDBERG
Pubblicato in: 18th International Conference on Intelligent Environments IE2022, 2022
Editore: IE2022

Towards the knowledge reuse in the semiconductor manufacturing industry AI Approaches: pitfall and tips

Autori: Razouk H. and Kern R.
Pubblicato in: European apc|m Conference, 2022
Editore: -

Automated Diagnosis of Cyber-Physical Systems

Autori: Franz Wotawa, Oliver Tazl, and David Kaufmann
Pubblicato in: The 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE), 2021
Editore: Springer Nature
DOI: 10.1007/978-3-030-79463-7_37

DDMin versus QuickXplain – An Experimental Comparison of two Algorithms for Minimizing Collections

Autori: Oliver A. Tazl, Christopher Tafeit, Franz Wotawa, and Alexander Felfernig
Pubblicato in: Proceedings of the International Conference on Software Engineering and Knowledge Engineering (SEKE), 2022
Editore: KSI Research Inc.

DORY: Lightweight memory hierarchy management for deep NN inference on IoT endnodes - work-in-progress

Autori: Alessio Burrello, Francesco Conti, Angelo Garofalo, Davide Rossi, Luca Benini
Pubblicato in: Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis Companion, 2019, Pagina/e 1-2, ISBN 9781-450369237
Editore: ACM
DOI: 10.1145/3349567.3351726

Comparison of Machine Learning and Deep Learning Methods for Grape Cluster Segmentation

Autori: Mohimont, L., Roesler, M., Rondeau, M., Gaveau, N., Alin, F., Steffenel, L.A. (2021). Comparison of Machine Learning and Deep Learning Methods for Grape Cluster Segmentation. In: Boumerdassi, S., Ghogho, M., Renault, É.
Pubblicato in: International Conference on Smart and Sustainable Agriculture (SSA'2021), Numero Communications in Computer and Information Science, vol 1470, 2021, ISBN 978-3-030-88258-7
Editore: Springer, Cham
DOI: 10.1007/978-3-030-88259-4_7

Optimizing 3D object detection for embedded systems in automated vehicles using sensor data fusion and CUDA computing

Autori: Topi Miekkala, Matti Kutila, Mathias Schneider and Alfred Höß
Pubblicato in: 2022
Editore: the 2022 IEEE 18th International Conference on Intelligent Computer Communication and Processing (ICCP 2022)

synthetic data of randomly piled, similar objects for deep learning-based object detection

Autori: Janis Arents, Bernd Lesser, Andis Bizuns, Roberts Kadikis, Elvijs Buls and Modris Greitans
Pubblicato in: 2022
Editore: Springer

DORY: Automatic End-to-End Deployment of Real-World DNNs on Low-Cost IoT MCUs

Autori: A. Burrello, A. Garofalo, N. Bruschi, G. Tagliavini, D. Rossi, F. Conti
Pubblicato in: IEEE Transactions on Computers, 2021
Editore: IEEE Xplore
DOI: 10.1109/tc.2021.3066883

Robust Sim2Real Transfer by Learning Deep Inverse Dynamics Model of Simulation

Autori: Mohammadhossein Malmir, Josip Josifovski, Noah Klarmann, Alois Knoll
Pubblicato in: 2020
Editore: Semantic Scholar

foxBMS-free and open BMS platform focused on functional safety and AI

Autori: Waldhoer, S., Bockrath, S., Wenger, M., Schwarz, R., & Lorentz, V. R.
Pubblicato in: PCIM Europe digital days 2020; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, 2020
Editore: IEEE

AI-Based Edge Acquisition, Processing and Analytics for Industrial Food Production

Autori: Ovidiu VERMESAN, Ronnie Otto BELLMANN, Roy BAHR, Jøran Edell MARTINSEN, Anders KRISTOFFERSEN, Torgeir Hjertaker , John Breiland, Karl Andersen , Hans Erik SAND and David LINDBERG
Pubblicato in: IEEE INTERNATIONAL CONFERENCE ON EDGE COMPUTING & COMMUNICATIONS, 2022
Editore: IEE
DOI: 10.3233/aise220033

Benchmarking Automotive LiDAR Performance in Arctic Conditions

Autori: Matti Kutila, Pasi Pyykönen, Maria Jokela, Tobias Gruber, Mario Bijelic, Werner Ritter
Pubblicato in: 2020
Editore: IEEE
DOI: 10.1109/itsc45102.2020.9294367

A TinyML Platform for On-Device Continual Learning with Quantized Latent Replays

Autori: Leonardo Ravaglia; Manuele Rusci; Davide Nadalini; Alessandro Capotondi; Francesco Conti; Luca Benini
Pubblicato in: IEEE Journal on Emerging and Selected Topics in Circuits and Systems 11.4 (2021), Numero 21563365, 2021, Pagina/e 789-802, ISSN 2156-3365
Editore: IEEEE
DOI: 10.1109/jetcas.2021.3121554

Improving the Consistency of the Failure Mode Effect Analysis (FMEA) Documents in Semiconductor Manufacturing

Autori: Houssam Razouk, Roman Kern
Pubblicato in: Applied Sciences, Numero 20763417, 2022, ISSN 2076-3417
Editore: MDPI
DOI: 10.3390/app12041840

Advanced Applications of Industrial Robotics: New Trends and Possibilities

Autori: Andrius Dzedzickis, Jurga Subaciute-Žemaitiene, Ernestas Šutinys, Urte Samukaite-Bubniene and Vytautas Bucinskas
Pubblicato in: Applied Sciences, 2021, ISSN 2076-3417
Editore: Applied Sciences

XpulpNN: Enabling Energy Efficient and Flexible Inference of Quantized Neural Networks on RISC-V based IoT End Nodes

Autori: Angelo Garofalo, Giuseppe Tagliavini, Francesco Conti, Luca Benini and Davide Rossi
Pubblicato in: IEEE Transactions on Emerging Topics in Computing, 2021, ISSN 0890-8044
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tetc.2021.3072337

Traitement d’Images et Apprentissage Automatique pour la Viticulture de Précision

Autori: Lucas Mohimont; Amine Chemchem ; Marine Rondeau ; Mathias Roesler ; François Alin ; Nathalie Gaveau ; Luiz Angelo Steffenel
Pubblicato in: Revue Ouverte d'Intelligence Artificielle, 2021, ISSN 0992-499X
Editore: Lavoisier

An Intelligent Real-Time Edge Processing Maintenance System for Industrial Manufacturing, Control, and Diagnostic

Autori: Ovidiu Vermesan, Marcello Coppola, Roy Bahr, Ronnie Otto Bellmann, Jøran Edell Martinsen, Anders Kristoffersen, Torgeir Hjertaker, John Breiland, Karl Andersen, Hans Erik Sand and David Lindberg
Pubblicato in: Frontiers in Chemical Engineering, 2022, ISSN 2673-2718
Editore: Lausanne: Frontiers Media SA
DOI: 10.3389/fceng.2022.900096

A review on AI Safety in highly automated driving

Autori: Wäschle, Moritz and Thaler, Florian and Berres, Axel and Pölzlbauer, Florian and Albers, Albert
Pubblicato in: Frontiers in Artificial Intelligence, Numero 26248212, 2022, ISSN 2624-8212
Editore: www.frontiersin.org
DOI: 10.3389/frai.2022.952773

State of Health Estimation using a Temporal Convolutional Network for an Efficient Use of Retired Electric Vehicle Batteries within Second-Life Applications

Autori: Journal of Applied Energy
Pubblicato in: Journal of Applied Energy, 2022, ISSN 0306-2619
Editore: Pergamon Press Ltd.

Intelligent Agents Diagnostics—Enhancing Cyber‐Physical Systems with Self‐Diagnostic Capabilities

Autori: David Kaufmann, Iulia Nica, Franz Wotawa
Pubblicato in: Advanced Intelligent Systems, Numero 3/5, 2021, Pagina/e 2000218, ISSN 2640-4567
Editore: Wiley
DOI: 10.1002/aisy.202000218

Accurate First-Principles Treatment of the High-Temperature Cubic Phase of Hafnia

Autori: Sebastian Bichelmaier,Jesús Carrete,Michael Nelhiebel,Georg K. H. Madsen
Pubblicato in: Wiley Online Library, Numero 18626254, 2022, ISSN 1862-6254
Editore: Wiley - VCH Verlag GmbH & CO. KGaA
DOI: 10.1002/pssr.202100642

CMix-NN: Mixed Low-Precision CNN Library for Memory-Constrained Edge Devices

Autori: Alessandro Capotondi, Manuele Rusci, Marco Fariselli, Luca Benini
Pubblicato in: IEEE Transactions on Circuits and Systems II: Express Briefs, Numero 67/5, 2020, Pagina/e 871-875, ISSN 1549-7747
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tcsii.2020.2983648

Runtime Design Space Exploration and Mapping of DCNNs for the Ultra-Low-Power Orlando SoC

Autori: Ahmet Erdem, Cristina Silvano, Thomas Boesch, Andrea Carlo Ornstein, Surinder-Pal Singh, Giuseppe Desoli
Pubblicato in: ACM Transactions on Architecture and Code Optimization, Numero 17/2, 2020, Pagina/e 1-25, ISSN 1544-3566
Editore: Association for Computing Machinary, Inc.
DOI: 10.1145/3379933

Smart Industrial Robot Control Trends, Challenges and Opportunities within Manufacturing

Autori: Janis Arents and Modris Greitans
Pubblicato in: Applied Sciences, 2021, ISSN 2076-3417
Editore: Applied Sciences

Improving Industrial Robot Positioning Accuracy to the Microscale Using Machine Learning Method

Autori: Vytautas Bucinskas, Andrius Dzedzickis, Marius Sumanas, Ernestas Sutinys, Sigitas Petkevicius, Jurate Butkiene, Darius Virzonis and Inga Morkvenaite-Vilkonciene
Pubblicato in: Machines, Numero 20751702, 2022, Pagina/e 20, ISSN 2075-1702
Editore: MDPI
DOI: 10.3390/machines10100940

Vega: A Ten-Core SoC for IoT Endnodes With DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode

Autori: D. Rossi, F. Conti, M. Eggiman, A. Di Mauro, G. Tagliavini, S. Mach, M. Guermandi, A. Pullini, I. Loi, J. Chen, E. Flamand, L. Benini
Pubblicato in: IEEE Journal of Solid-State Circuits, 2022, ISSN 0018-9200
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/jssc.2021.3114881

A Motion Capture and Imitation Learning Based Approach to Robot Control

Autori: Peteris Racinskis, Janis Arents and Modris Greitans
Pubblicato in: Applied Sciences, 2022, ISSN 2076-3417
Editore: MDPI

A TinyML Platform for On-Device Continual Learning With Quantized Latent Replays

Autori: L. Ravaglia, M. Rusci, D. Nadalini, A. Capotondi, L. Benini
Pubblicato in: IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2021, ISSN 2156-3357
Editore: IEEE Circuits and Systems Society

Model-based reasoning using answer set programming

Autori: Franz Wotawa and David Kaufmann
Pubblicato in: Applied Intelligence, 2022, ISSN 1573-7497
Editore: Applied Intelligence
DOI: 10.1007/s10489-022-03272-2

Automotive Intelligence Embedded in Electric Connected Autonomous and Shared Vehicles Technology for Sustainable Green Mobility

Autori: Vermesan O, John R, Pype P, Daalderop G, Kriegel K, Mitic G, Lorentz V, Bahr R, Sand HE, Bockrath S and Waldhör S
Pubblicato in: Front. Future Transp, Numero 26 August 2021, 2021, ISSN 2673-5210
Editore: Frontiers in future transportation
DOI: 10.3389/ffutr.2021.688482

Accurate effective harmonic potential treatment of the high-temperature cubic phase of Hafnia

Autori: Sebastian Bichelmaier,Jesús Carrete,Michael Nelhiebel,Georg K. H. Madsen
Pubblicato in: physica status solidi (RRL) – Rapid Research Letters, Numero 18626254, 2021, ISSN 1862-6254
Editore: Wiley - VCH Verlag GmbH & CO. KGaA
DOI: 10.48550/arxiv.2110.04771

AI in Industrial Machinery

Autori: Giulio Urlini , Janis Arents and Antonio Latella
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publisher

AI-Based Vehicle Systems for Mobility-as-a-Service Application

Autori: Mikko Tarkiainen , Matti Kutila , Topi Miekkala, Sami Koskinen , Jokke Ruokolainen , Sami Dahlmanand Jani Toiminen
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

Radar-Based Human-Robot Interfaces

Autori: Hans Cappelle , Ali Gorji Daronkolaei , Ing Jyh Tsang , Björn Debaillie and Ilja Ocket
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

Generating Trust in Hardware through Physical Inspection

Autori: Bernhard Lippmann, Matthias Ludwig and Horst Gieser
Pubblicato in: Embedded Artificial Intelligence Devices, Embedded Systems, and Industrial Applications, 2022
Editore: River Publishers

Benchmarking Neuromorphic Computing for Inference

Autori: Simon Narduzzi, Loreto Mateu, Petar Jokic, Erfan Azarkhish, and Andrea Dunbar
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

Impact of AI and Digital Twins on IIoT

Autori: Bin Han, Björn Richerzhagen, Hans Schotten, Davide Calandra, and Fabrizio Lamberti
Pubblicato in: 2022, ISBN 9788770226103
Editore: River Publishers

Failure Detection in Silicon Package

Autori: Saad Al-Baddai and Jan Papadoudis
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

AI-Powered Collision Avoidance Safety System for Industrial Woodworking Machinery

Autori: Conti, F.; Indirli, F.; Latella, A.; Papariello, F.; Puglia, G. M.; Tecce, F.; Urlini, G.; Zanghieri, M.
Pubblicato in: 2021
Editore: River Publishers

On the Verification of Diagnosis Models

Autori: Franz Wotawa and Oliver Tazl
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022
Editore: River Publishers

AI for Inbound Logistics Optimisation in Automotive Industry

Autori: Nikolaos Evangeliou1, George Stamatis1, George Bravos1, Daniel Plorin2 and Dominik Stark2
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021, ISBN 9788770226646
Editore: River Publishers

Optimisation of Soybean Manufacturing Process Using Real-time Artificial Intelligence of Things Technology

Autori: Ovidiu Vermesan , Jøran Edell Martinsen , Anders Kristoffersen , Roy Bahr , Ronnie Otto Bellmann, Torgeir Hjertaker , John Breiland , Karl Andersen, Hans Erik Sand , Parsa Rahmanpour and David Lindberg
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

Edge AI Platforms for Predictive Maintenance in Industrial Applications

Autori: Ovidiu Vermesan and Marcello Copolla
Pubblicato in: Embedded Artificial Intelligence - Devices, Embedded Systems, and Industrial Applications, 2022
Editore: River Publishers

Automated Anomaly Detection Through Assembly and Packaging Process

Autori: Saad Al-Baddai , Martin Juhrisch , Jan Papadoudis , Anna Renner , Lippmann Bernhard , Cristina De Luca , Fabian Haas and Wolfgang Schober
Pubblicato in: 2021
Editore: River Publishers

Artificial Intelligence Advancements for Digitising Industry

Autori: Ovidiu Vermesan and Reiner John
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022, ISBN 9788770226103
Editore: River Publishers

AI-Based Quality Control System at the Pressing Stages of the Champagne Production

Autori: Lucas Mohimont , Mathias Roesler, Angelo Steffenel , Nathalie Gaveau , Marine Rondeau , François Alin , Clément Pierlot , Rachel Ouvinha de Oliveira , Marcello Coppola and Philipe Doré
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

Real-Time Predictive Maintenance – Model-Based, Simulation-Based and Machine Learning-Based Diagnosis

Autori: Franz Wotawa, David Kaufmann, Adil Amukhtar , Iulia Nica , Florian Klück , Hermann Felbinger, Petr Blaha, Matus Kozovsky , Zdenek Havranek and Martin Dosedel
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

Ethical Considerations and Trustworthy Industrial AI Systems

Autori: Ovidiu Vermesan, Cristina De Luca, Reiner John, Marcello Coppola, Björn Debaillie, and Giulio Urlini
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022, ISBN 9788770226103
Editore: River Publishers

Touch Identification on Sensitive Robot Skin Using Time Domain Reflectometry and Machine Learning Methods

Autori: Pawel Kostka, Anja Winkler, Adnan Haidar, Muhammad Ghufran Khan, Rene Jäkel, Peter Winkler and Ralph Müller-Pfefferkorn
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publisher

State of Health Estimation using a Temporal Convolutional Network for an Efficient Use of Retired Electric Vehicle Batteries within Second-Life Applications

Autori: Steffen Bockrath, Stefan Waldhör, Harald Ludwig, Vincent Lorentz
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021, ISBN 9788770226646
Editore: River Publishers

AI and IIoT-based Predictive Maintenance System for Soybean Processing

Autori: Ovidiu Vermesan , Jøran Edell Martinsen , Anders Kristoffersen , Roy Bahr , Ronnie Otto Bellmann, Torgeir Hjertaker , John Breiland , Karl Andersen, Hans Erik Sand , Parsa Rahmanpour and David Lindberg
Pubblicato in: Artificial Intelligence For Digitising Industry, 2021
Editore: River Publishers

AI-Driven Yield Estimation Using an Autonomous Robot for Data Acquisition

Autori: Lucas Mohimont , Luiz Angelo Steffenel , Mathias Roesler , Nathalie Gaveau , Marine Rondeau , François Alin , Clément Pierlot , Rachel Ouvinha de Oliveira and Marcello Coppola
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

Lesson Learnt and Future of AI Applied to Manufacturing

Autori: Valerio Frascolla, Matthias Hummert, Tobias Monsees, Dirk Wübben, Armin Dekorsy, Nicola Michailow, Volkmar Döricht, Christoph Niedermeier, Joachim Kaiser, Arne Bröring, Michael Villnow, DanielWessel, Florian Geiser, MatthiasWissel, Alberto Viseras, Bin Han, Björn Richerzhagen, Hans Schotten, Davide Calandra, and Fabrizio Lamberti
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022, ISBN 9788770226103
Editore: River Publishers

Innovative Vineyards Environmental Monitoring System Using Deep Edge AI

Autori: Marcello Coppola , Louis Noaille , Clément Pierlot , Rachel Ouvinha de Oliveira , Nathalie Gaveau , Marine Rondeau , Lucas Mohimont , Luiz Angelo Steffenel , Simone Sindaco and Tullio Salmon
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publisher

AI-Driven Strategies to Implement a Grapevine Downy Mildew Warning System

Autori: Luiz Angelo Steffenel, Axel Langlet, Lilian Hollard, Lucas Mohimont, Nathalie Gaveau, Marcello Copola, Clément Pierlot, and Marine Rondeau
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

AI Reshaping the Automotive Industry

Autori: Daniel Plorin
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers
DOI: 10.13052/rp-9788770226639

Towards Fully Automated Verification of Semiconductor Technologies

Autori: Matthias Ludwig , Dinu Purice , Bernhard Lippmann, Ann-Christin Bette and Claus Lenz
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

Temporal Delta Layer: Exploiting Temporal Sparsity in Deep Neural Networks for Time-Series Data

Autori: Preetha Vijayan, Amirreza Yousefzadeh, Manolis Sifalakis, and Rene van Leuken
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

Power Optimised Wafermap Classification for Semiconductor Process Monitoring

Autori: Ana Pinzari, Thomas Baumela, Liliana Andrade, Marcello Copolla and Frédéric Pétrot
Pubblicato in: Embedded Artificial Intelligence - Devices, Embedded Systems, and Industrial Applications, 2022
Editore: River Publishers

Current Challenges of AI Standardisation in the Digitising Industry

Autori: Ovidiu Vermesan, Marcello Coppola, Reiner John, Cristina De Luca, Roy Bahr, and Giulio Urlini
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022, ISBN 9788770226103
Editore: River Publishers

Radar-Based Human-Robot Interfaces

Autori: Hans Cappelle , Ali Gorji Daronkolaei , Ing Jyh Tsang , Björn Debaillie and Ilja Ocket
Pubblicato in: 2021
Editore: River Publisher

Construction of a Smart Vision-Guided Robot System for Manipulation in a Dynamic Environment

Autori: Janis Arents , Modris Greitans and Bernd Lesser
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

Feasibility of Wafer Exchange for European Edge AI Pilot Lines

Autori: Annika Franziska Wandesleben, Delphine Truffier-Boutry, Varvara Brackmann, Benjamin Lilienthal-Uhlig, Manoj Jaysnkar, Stephan Beckx, Ivan Madarevic, Audde Demarest, Bernd Hintze, Franck Hochschulz, Yannick Le Tiec, Alessio Spessot, and Fabrice Nemouchi
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

Open Traffic Data for Mobility-as-a-Service Applications – Architecture and Challenges

Autori: Mathias Schneider, Mina Marmpena , Haris Zafeiris , Ruben Prokscha , Seifeddine Saadani , Nikolaos Evangeliou , George Bravos and Alfred Höß1
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

Embedded Edge Intelligent Processing for End-To-End Predictive Maintenance in Industrial Applications

Autori: Ovidiu Vermesan and Marcello Coppola
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

Applications of AI in Transportation Industry

Autori: Mathias Schneider, Matti Kutila and Alfred Höß1
Pubblicato in: 2021
Editore: River Publishers

Tools and Methodologies for Training, Profiling, and Mapping a Neural Network on a Hardware Target

Autori: Alexandre Valentian, Simon Narduzzi, Muhammad Arsalan, Kay Bierzynski, Stefano Traferro, Preetha Vijayan, Amirreza Yousefzadeh, Manolis Sifalakis, Rene Van Leuken, Dylan Muir, Rashid Ali, Maen Mallah, Bijoy Kundu, Loreto Mateu, and Mario Diaz Nava
Pubblicato in: 2022, ISBN 9788770226103
Editore: River Publishers

Technology and Hardware for Neuromorphic Computing

Autori: Björn Debaillie, Ilja Ocket, and Peter Debacker
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022, ISBN 9788770226103
Editore: River Publishers

Touch Identification on Sensitive Robot Skin Using Time Domain Reflectometry and Machine Learning Methods

Autori: Pawel Kostka, Anja Winkler, Adnan Haidar, Muhammad Ghufran Khan, Rene Jäkel, Peter Winkler and Ralph Müller-Pfefferkorn
Pubblicato in: 2021
Editore: River Publisher

Touch Identification on Sensitive Robot Skin Using Time DomainReflectometry.

Autori: Pawel Kostka; Anja Winkler; Adnan Haidar; Muhammad Ghufran Khan; Rene Jäkel; Peter Winkler; Ralph Müller‐Pfefferkorn
Pubblicato in: Artificial Intelligence for Digitising Industry–Applications, 2021, ISBN 9788770226646
Editore: River Publishers

On the Use of Answer Set Programming for Model-Based Diagnosis

Autori: Franz Wotawa
Pubblicato in: Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices - 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, Kitakyushu, Japan, September 22-25, 2020, Proceedings, Numero 12144, 2020, Pagina/e 518-529, ISBN 978-3-030-55788-1
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-55789-8_45

AI-Powered Collision Avoidance Safety System for Industrial Woodworking Machinery

Autori: Francesco Conti , Fabrizio Indirli , Antonio Latella, Francesco Papariello, Giacomo Michele Puglia, Felice Tecce , Giulio Urlini and Marcello Zanghieri
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

An End-to-End AI-based Automated Process for Semiconductor Device Parameter Extraction

Autori: Dinu Purice, Matthias Ludwig, and Claus Lenz
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

Emerging In-memory Computing for Neural Networks

Autori: Nellie Laleni, Taha Soliman, Alptekin Vardar, and Thomas K¨ampfe
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022, ISBN 9788770226103
Editore: River Publishers

Innovative Vineyards Environmental Monitoring System Using Deep Edge AI

Benchmarking the Epiphany Processor as a Reference Neuromorphic Architecture

Autori: Maarten Molendijk, Kanishkan Vadivel, Federico Corradi, Gert-Jan van Schaik, Amirreza Yousefzadeh, and Henk Corporaal
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

Foundations of Real-Time Predictive Maintenance with Root Cause Analysis

AI in Semiconductor Industry

Autori: Cristina De Luca , Bernhard Lippmann, Wolfgang Schober , Saad Al-Baddai , Georg Pelz , Andreja Rojko , Frédéric Pétrot, Marcello Coppola and Reiner John
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publisher

Industrial AI Technologies for Next-Generation Autonomous Operations with Sustainable Performance

Autori: Ovidiu Vermesan, Frédéric Pétrot, Marcello Coppola, Mathias Schneider, and Alfred Höß
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022, ISBN 9788770226103
Editore: River Publishers

AI in Food and Beverage Industry

Autori: Rachel Ouvinha de Oliveira , Marcello Coppola and Ovidiu Vermesan
Pubblicato in: 2021
Editore: River Publisher

Deploying a Convolutional Neural Network on Edge MCU and Neuromorphic Hardware Platforms

Autori: Simon Narduzzi, Dorvan Favre, Nuria Pazos Escudero and L. Andrea Dunbar
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

AI-Based Knowledge Management System for Risk Assessment and Root Cause Analysis in Semiconductor Industry

Autori: Houssam Razouk, Roman Kern, Martin Mischitz , Josef Moser , Mirhad Memic , Lan Liu , Christian Burmer and Anna Safont-Andreu
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publisher

Using FeFETs as Resistive Synapses in Crossbar-based Analog MAC Accelerating Units

Autori: Lei Zhang, David Borggreve, Frank Vanselow, Ralf Brederlow
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022, ISBN 9788770226103
Editore: River Publishers

AI-Driven Yield Estimation Using an Autonomous Robot for Data Acquisition

Efficient Deep Learning Approach for Fault Detection in the Semiconductor Industry

Autori: Liliana Andrade , Thomas Baumela , Frédéric Pétrot , David Briand , Olivier Bichler and Marcello Coppola
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publishers

A Framework for Integrating Automated Diagnosis into Simulation

Autori: David Kaufmann and Franz Wotawa
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022
Editore: River Publisher

Optimising Trajectories in Simulations with Deep Reinforcement Learning for Industrial Robots in Automotive Manufacturing

Autori: Noah Klarmann, Mohammadhossein Malmir, Josip Josifovski, Daniel Plorin, Matthias Wagner and Alois C. Knoll
Pubblicato in: Artificial Intelligence for Digitising Industry Applications, 2021
Editore: River Publishers

Real-Time Predictive Maintenance – Artificial Neural Network Based Diagnosis

Autori: Petr Blaha , Matus Kozovsky , Zdenek Havranek , Martin Dosedel , Franz Wotawa , David Kaufmann , Adil Amukhtar , Iulia Nica , Florian Klück and Hermann Felbinger
Pubblicato in: Artificial Intelligence for Digitising Industry, 2021
Editore: River Publisher

Construction of a Smart Vision-Guided Robot System for Manipulation in a Dynamic Environment

Autori: Janis Arents , Modris Greitans and Bernd Lesser
Pubblicato in: 2021
Editore: River Publisher

Efficient Edge Deployment Demonstrated on YOLOv5 and Coral Edge TPU

Autori: Ruben Prokscha, Mathias Schneider, and Alfred Höß
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

Vers des Modèles IA pour l'Estimation du Rendement en Viticulture

Autori: Luiz Angelo Steffenel
Pubblicato in: TERINT2021, 2021, ISBN 9782364938953
Editore: 1er Colloque 2021 sur l’émergence de TERritoires INTelligents (TERINT2021)

AI Machine Vision System for Wafer Defect Detection

Autori: Dmitry Morits, Marcelo Rizzo Piton, and Timo Laakko
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022, ISBN 9788770227919
Editore: River Publishers

Artificial Intelligence for Digitising Industry

Autori: Editors: Ovidiu Vermesan, Reiner John, Cristina De Luca and Marcello Coppola
Pubblicato in: 2021, ISBN 9788770226646
Editore: River Publishers

Intelligent Edge-Embedded Technologies for Digitising Industry

Autori: Editors: Ovidiu Vermesan and Mario Diaz Nava
Pubblicato in: 2022, ISBN 9788770226110
Editore: River Publishers
DOI: 10.13052/rp-9788770226103

Industrial Artificial Intelligence Technologies and Applications

Autori: Editors: Ovidiu Vermesan, Franz Wotawa, Mario Diaz Nava and Björn Debaillie
Pubblicato in: 2022, ISBN 9788770227919
Editore: River Publishers
DOI: 10.13052/rp-9788770227902

Embedded Artificial Intelligence: Devices, Embedded Systems, and Industrial Applications

Autori: Editors Ovidiu Vermesan, SINTEF, Norway Mario Diaz Nava, STMicroelectronics, France Björn Debaillie, imec, Belgium
Pubblicato in: 2022, ISBN 978-87-7022-820-6
Editore: River Publishers

Testumgebung für Edge Computing in Intelligenten Transportsystemen (ITS)

Autori: Mathias Schneider, Seifeddine Saadani, Ruben Prokscha, Alfred Höß
Pubblicato in: 2021
Editore: Research Gate
DOI: 10.13140/rg.2.2.35627.16169

KI-basierte Optimierung von Daten-Pipelines

Autori: Ruben Prokscha, Mathias Schneider, Seifeddine Saadani, Dr.-Ing. Alfred Höß
Pubblicato in: 2022
Editore: Research gate

Graph Neural Networks for Relational Inductive Bias in Vision-based Deep Reinforcement Learning of Robot Control

Autori: Oliva, Marco, Soubarna Banik, Josip Josifovski, and Alois Knoll.
Pubblicato in: 2021
Editore: arXiv

Application of machine learning in Microelectromechanical systems (MEMS) manufacturing

Autori: Kamil Marwat
Pubblicato in: 2019
Editore: Aalto University

Realization of a Service Pipeline for Traffic Density Estimation and Prediction based on Traffic Data using Machine Learning

Autori: Ruben Prokscha
Pubblicato in: 2022
Editore: -
DOI: 10.13140/rg.2.2.13704.49927

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