Intro
Preface
6th International Conference on System-Integrated Intelligence (SysInt2022)
General Chair
Organizing Committee
International Scientific Committee
Technical Program Chairs
Track and Special Session Chairs
Organizers
Sponsors
Contents
Artificial Intelligence
Towards Challenges and Proposals for Integrating and Using Machine Learning Methods in Production Environments
1 Introduction
1.1 Motivation
2 General Overview
3 Identified Challenges and Proposals
3.1 Social Challenges and Human Factors
3.2 Sensors and Data Sources

3.3 Computational and Processing Capacity
3.4 Software Dependencies
3.5 Model Availability and System Failures
3.6 Adaptation of Business Processes and Model Adjustments
4 Summary and Conclusion
References
Autonomous Driving Based on Imitation and Active Inference
1 Introduction
2 Proposed Framework
2.1 Offline Learning Phase
2.2 Online Learning Phase
3 Experimental Evaluation
3.1 Offline Learning Phase
3.2 Online Learning Phase
4 Conclusion
References
Machine Learning Based Reconstruction of Process Forces
1 Introduction
2 Methods

2.1 Experimental Setup
2.2 Data Preprocessing
2.3 Algorithms and Model Training
3 Results
3.1 Data Complexity
3.2 Generalizability
3.3 Comparing MILLTAP700 and HSC30
4 Summary and Conclusion
References
A Novel Rule-Based Modeling and Control Approach for the Optimization of Complex Water Distribution Networks
1 Introduction
2 Related Work
3 Rule Based Control
3.1 Modeling
3.2 Control
4 Results
5 Discussion
References
Graph-Based Segmentation and Markov Random Field for Covid-19 Infection in Lung CT Volumes
1 Introduction

2 Materials and Methods
2.1 Overview
2.2 Dataset
2.3 Lung Masking and Region Segmentation
2.4 Parametric Model Fitting
2.5 Markov Random Field Modelling
3 Results
4 Conclusion
References
Image Based Classification of Methods-Time Measurement Operations in Assembly Using Recurrent Neuronal Networks
1 Introduction
2 Classification of Assembly Operations
3 Experimental Design and Data Analysis
3.1 Architecture of the Neuronal Network
3.2 Analysis of the Data Set
3.3 Data Processing
4 Results
5 Summary
References

Pervasive and Ubiquitous Intelligence
FPGA-Based Road Crack Detection Using Deep Learning
1 Introduction
2 Dataset and Crack Detection Network Architecture
3 FPGA Implementation and Deployment
3.1 Implementation Results
4 Performance Analysis
4.1 Detection Accuracy
4.2 Throughput and Energy Efficiency
5 Conclusion
References
Simple Non Regressive Informed Machine Learning Model for Prescriptive Maintenance of Track Circuits in a Subway Environment
1 Introduction
2 Problem Formalization and Available Data
3 Simple Non Regressive Informed Data Driven Model