Process-Driven and Flow-Based Processing of Industrial Sensor Data

For machine manufacturing companies, besides the production of high quality and reliable machines, requirements have emerged to maintain machine-related aspects through digital services. The development of such services in the field of the Industrial Internet of Things (IIoT) is dealing with solutions such as effective condition monitoring and predictive maintenance. However, appropriate data sources are needed on which digital services can be technically based. As many powerful and cheap sensors have been introduced over the last years, their integration into complex machines is promising for developing digital services for various scenarios. It is apparent that for components handling recorded data of these sensors they must usually deal with large amounts of data. In particular, the labeling of raw sensor data must be furthered by a technical solution. To deal with these data handling challenges in a generic way, a sensor processing pipeline (SPP) was developed, which provides effective methods to capture, process, store, and visualize raw sensor data based on a processing chain. Based on the example of a machine manufacturing company, the SPP approach is presented in this work. For the company involved, the approach has revealed promising results

Konzeption einer modernen Web-Application zur Verwaltung von Dynamischen Mobile Crowdsensing Plattformen im Healthcare Bereich

Steigender Stress und Leistungsdruck in der Schule oder später im Berufsleben können unter anderem zu psychischen Erkrankungen, Tinnitus oder Bluthochdruck führen. Viele Betroffene finden keine Zeit mehr für sich selber um den angesammelten Stress und Leistungsdruck abbauen zu können. Durchgeführte Studien belegen Zusammenhänge zwischen Stress und Tinnitus und zeigen die Auswirkungen auf die Betroffenen. Dieses Projekt wurde gegründet, um noch mehr spezifische Daten zu erhalten, diese zu analysieren und um den Betroffenen anschließend direkt persönliche Informationen hierzu bereitstellen zu können. Die Basis hierfür bildet eine Vielzahl an bereits vorhandenen Studien, sowie die darin enthaltenen Fragebögen, welche intervallabhängig wiederholt werden können. Die Benutzer der Webapplikation können bequem von zu Hause aus die Fragebögen beantworten und erhalten anschließend individuelle, auf den Benutzer angepasste Informationen. Dabei werden die Informationen graphisch dargestellt um eine schnelle und übersichtliche Anschauung zu ermöglichen und um Veränderungen direkt erkennen zu können

A Decision Support System for Benefits Realisation in Front End Design of Construction Projects in Dynamic Contexts

There is an increasing interest in the performance of construction projects, focussing on measurable value delivery. This research proposes a novel decision support system to support Front End Design (FED) decision making in addressing continuing value constraints in the delivery of project benefits. Stakeholder involvement and interests in projects that impact on project requirements understanding and management often means competing and sometimes conflicting requirements. However, projects now face increasing expectations to cope with emergent needs, which adds to uncertainty in the design process. As a result, there are continuing challenges in understanding and measuring project performance in terms of derived benefits. Increasingly, research points to the need for new understanding of FED processes on account of their vital contribution to value generation throughout the project life cycle. Much of current design practice however relies on qualitative explanatory/rationalistic methods to model uncertainty and predict changes in use cases in projects. The reliability of the approaches in the face of myriad, often conflicting and competing stakeholder interests in AEC design is increasingly under focus. This research adopts a mixed-methods approach in developing, validating and evaluating the proposed system in two case study project contexts for comparative assessment of the modelling results. The research formalises a new decision system (DESIDE), in exploring mathematical modelling based on Bayesian probabilistic models and proposes a new system focussed on the utility of decision making in the realisation of project benefits. The research explores the use of probability theory and appropriate mathematical approaches in the management and modelling of requirements and uncertainty during design decision making. The research also explores the use of complementary requirements forecasting modelling in a holistic integrated modelling approach. The research contributes to knowledge through 1) the new decision system that presents new frontiers in empirical evaluation of FED Benefits Realisation, 2) presenting an integrated analytical modelling approach of project requirements modelling in FED with a focus on the full project lifecycle performance based on analytical utility assessments and cause-effect modelling and 3) presenting a new integrated forecast and uncertainty probabilistic modelling approach of requirements in FED to support benefits realisation in projects