Automated Fusion System Design and Adaptation Implementation

This published prototype is a JAVA-based implementation of the automated fusion system design proposed in [FMH+17]. The implementation orchestrates a distributed information fusion system, i.e., it identifies features and attribute supported by the system. The automated orchestration is carried out at a central device called system manager. Basic elements of the fusion system are intelligent sensors. Intelligent sensors monitor a system using elementary sensors (e.g., temperature sensors or acoustic sensors) [MDL+16, FML16]. The sensor signals of all intelligent sensors are gathered and fused to evaluate the condition (i.e., health) of the monitored system. An intelligent sensor is additionally equipped with processor units, memory, and communication interfaces. It is self-adaptable and self-aware. An intelligent sensor hosts a semantic self-description stating available elementary sensors and algorithms. Algorithms are used to extract certain features from sensor signals. This implementation uses the Raspberry Pi 3B as platform for intelligent sensors. The Raspberry Pis 3B supports several interfaces to read multiple elementary sensor signals. This implementation reads sensor signals via the Serial Peripheral Interface (SPI). Communication between intelligent sensors uses the Raspberry Pi’s Ethernet interface. All communication for the organisation and configuration of the fusion system uses TCP/IP. Process data (sensor signals and features) are communicated via an Industrial Ethernet in real-time. The process data communication is not part of this publication. The automated fusion system design is structured into the following four phases: Discovery: The system manager searches for available intelligent sensors. The discovery phase is carried out continuously independent of the other three phases. If a new intelligent sensor is discovered, the knowledge building phase is triggered. Knowledge Building: Semantic information (self-description of intelligent sensors) is transferred to a knowledge base at the system manager. Orchestration: The system manager carries out the fusion system configuration automatically. Operation: All intelligent sensors periodically send their sensor signals and features to the system manager using a real-time Ethernet protocol. Discovery of intelligent sensors and transfer of semantic information is implemented using the Open Platform Communication Unified Architecture (OPC UA). OPC UA offers a Local Discovery Server (LDS), which exposes available OPC UA servers in a local network. As soon as the system manager has discovered an intelligent sensor, the semantic self-description is collected and stored in the system manager’s knowledge base. Then, the fusion system is orchestrated using a rule-based system. The orchestration engine identifies based on available sensors and algorithms features and different kinds of attributes (physical, module, functional,quality). For details about the orchestration process and the rule-based system the reader is referred to the corresponding journal article [FMH+17]. The last step in the orchestration phase is the creation of an configuration file for the real-time communication. This configuration file is used to determine the layout of the real-time Ethernet communication network. The source code is included in the ZIP file of this upload. The accompanying PDF contains a description on how to compile and execute the implementation. [FMH+17] FRITZE, Alexander ; MÖNKS, Uwe ; HOLST, Christoph-Alexander ; LOHWEG, Volker: An Approach to Automated Fusion System Design and Adaptation. In: Sensors 17 (2017), Nr. 3, 601. http://dx.doi.org/10.3390/s17030601. – DOI 10.3390/s17030601 [FML16] FRITZE, Alexander ; MÖNKS, Uwe ; LOHWEG, Volker: A Support System for Sensor and Information Fusion System Design. In: 3rd International Conference on System-Integrated Intelligence - New Challenges for Product and Production Engineering, Paderborn, Germany, 2016 [MDL+16] MÖNKS, Uwe ; DÖRKSEN, Helene ; LOHWEG, Volker ; HÜBNER, Michael: Information Fusion of Conflicting Input Data. In: Sensors (Basel, Switzerland) 16 (2016), Nr. 11. http://dx.doi.org/10.3390/s16111798. – DOI 10.3390/s16111798. – ISSN 1424–822

Integration with Ontologies

One of today’s hottest IT topics is integration, as bringing together information from different sources and structures is not completely solved. The approach outlined here wants to illustrate how ontologies [Gr93] could help to support the integration process

The KB paradigm and its application to interactive configuration

The knowledge base paradigm aims to express domain knowledge in a rich formal language, and to use this domain knowledge as a knowledge base to solve various problems and tasks that arise in the domain by applying multiple forms of inference. As such, the paradigm applies a strict separation of concerns between information and problem solving. In this paper, we analyze the principles and feasibility of the knowledge base paradigm in the context of an important class of applications: interactive configuration problems. In interactive configuration problems, a configuration of interrelated objects under constraints is searched, where the system assists the user in reaching an intended configuration. It is widely recognized in industry that good software solutions for these problems are very difficult to develop. We investigate such problems from the perspective of the KB paradigm. We show that multiple functionalities in this domain can be achieved by applying different forms of logical inferences on a formal specification of the configuration domain. We report on a proof of concept of this approach in a real-life application with a banking company. To appear in Theory and Practice of Logic Programming (TPLP).Comment: To appear in Theory and Practice of Logic Programming (TPLP

A multi-agent architecture for electronic payment

The Internet has brought about innumerable changes to the way enterprises do business. An essential problem to be solved before the widespread commercial use of the Internet is to provide a trustworthy solution for electronic payment. We propose a multi-agent mediated electronic payment architecture in this paper. It is aimed at providing an agent-based approach to accommodate multiple e-payment schemes. Through a layered design of the payment structure and a well-defined uniform payment interface, the architecture shows good scalability. When a new e-payment scheme or implementation is available, it can be plugged into the framework easily. In addition, we construct a framework allowing multiple agents to work cooperatively to realize automation of electronic payment. A prototype has been built to illustrate the functionality of this design. Finally we discuss the security issues

Product Configuration Systems: State of the Art, Conceptualization and Extensions

Product configurators are considered to be among the most successful applications of artificial intelligence technology. In this paper, we determine different conceptualizations of configurators and condense them in a comprehensive morphological box, which should support configurator designers as well as decision makers in selecting the right system. The analysis of the criteria according to which configurators that are designed thus far reveals a neglect of the front-end perspective. Therefore, it is relevant to extend configurators with a front-end component assisting customers during product configuration through advisory. We develop a framework describing the main requirements on an advisory system and propose the technical infrastructure for its implementation. Finally, the advisory system and the configurator are integrated into a comprehensive interaction system.product configurators; advisory system; product personalization