05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Classifying physical exercises and counting repetitions using three-dimensional pose estimation(2023) Wallmann, JonasResistance training is known to increase physical and mental health but requires a lot of knowledge and experience to be done effectively and safely. Personal trainers and physiotherapists provide their knowledge to athletes but their profession requires a lot of learning and experience, thus making their services often not affordable to the general public. Automating certain aspects of their work will make their services more available to the general population and therefore lead to more safe and more effective athletes. The first steps of automating personal training lie in observing a subject train and understanding their performed workout. This provides the basics for future work of automating providing feedback on exercise execution and improving their training regimes. In order to do so, we developed a proof-of-concept program, that uses a two-dimensional camera video as an input to classify what exercise a user performs and automatically counts the number of performed repetitions, in real-time. It should work without imposing requirements in the camera perspective or needing to know what exercise will be performed in advance. This is achieved by using a three-dimensional pose estimation model and defining a rule-based algorithm, that considers the position and angle of joints that characterize the performed exercises We evaluate our proof-of-concept program using videos of subjects performing squats and push-ups in order to understand the accuracy in a real-world scenario. Our program achieved an overall accuracy of 95.57% for the squats and 93.69% for the push-up evaluation.Item Open Access Prozessbausteine(2014) Eberle, Hanna; Leymann, Frank (Prof. Dr.)Gegenwärtig existierenden Modellierungssprachen und Werkzeugen zur Umsetzung prozessbasierter Anwendungen liegt im Allgemeinen die Annahme eines zur Entwicklungszeit bekannten und in seiner Struktur vollständig ausmodellierten Prozessmodells zugrunde. Für Szenarien, in welchen eine prozessbasierte Anwendung neben stabilen, d.h. zur Modellierungszeit des Prozesses bekannten, auch durch dynamische, d.h. erst zur Anwendungslaufzeit geltende, Rahmenbedingungen beeinflusst wird, ist eine derartige statische Prozessmodellierung nur bedingt geeignet. In diesen Szenarien ist es vielmehr wünschenswert, (i) zur Entwicklungszeit bereits bekannte Prozessteile der Anwendung detailliert ausmodellieren zu können, und diese (ii) zur Laufzeit der Anwendung unter Berücksichtigung der zum Ausführungszeitpunkt geltenden dynamischen Rahmenbedingungen zum vollständigen Prozess der Anwendung zu integrieren. Das im Verlauf dieser Arbeit vorgestellte Konzept der Prozessbausteine setzt an diesem Punkt an und schafft ein Rahmenwerk für die Modellierung und Ausführung prozessbasierter Anwendungen unter Berücksichtigung sowohl stabiler als auch dynamischer Rahmenbedingungen. Kerngedanke des Konzepts ist die Abbildung stabiler Rahmenbedingungen zur Entwicklungszeit in Form teilweise unvollständiger Prozessmodelle, sogenannter Prozessbausteine. Zu einem späteren Zeitpunkt im Lebenszyklus der Anwendung werden diese Prozessbausteine dann, motiviert durch die jeweils geltenden dynamischen Rahmenbedingungen, mit weiteren Prozessbausteinen zum vollständigen Prozessmodell der Anwendung integriert. Zur vollständigen Unterstützung der Entwicklung von Anwendungen auf Grundlage dieses Konzepts umfasst die vorliegende Arbeit die Definition eines Metamodells für sowohl die Modellierung einzelner als auch die Repräsentation integrierter Prozessbausteine, die Beschreibung der Ausführung integrierter Prozessbausteine, sowie die Vorstellung einer Architektur für die Ausführung integrierter Prozessbausteine.Item Open Access Feasibility analysis of using Model Predictive Control in Demand-Side Management of residential building(2020) Ramachandran Selvaraj, Sri VishnuThe energy systems are becoming smart recently with an increase in communication capabilities between producer, distributor and consumer. Also, many distributed renewable energy producers both in large and domestic scale are adding to the system day by day. Executing Smart Demand-Side Management (DSM) programs can help in providing financial benefits and stability of the energy system without compromising the comfort of end-users. Model Predictive Control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. Due to its ability to predict future events and generate optimal control, it is widely used in process industries since the 1980s and in recent years it is introduced in power systems. This motivates to study the economic feasibility of using MPC in executing DSM for Residential building, to optimize the power consumption costs and stability of the energy system in the presence of local renewable energy sources (E.g., PV system). The main contribution of this thesis work is to measure the economic benefit of using MPC on DSM of household electricity consumption. A detailed study of modeling the demand side, i.e the appliances of a smart home, along with the domestic energy generators is done in the initial part. Apart from the physical properties of the renewable energy generators, the influence of external factors like weather, dynamic-pricing of electricity and changing user preference is also considered in the model. This formulated model is used to perform simulation of the residential building to generate an optimized energy consumption schedule and calculate the resulting economic benefits. The periodic changes in weather forecast and dynamic-prices are fed into the simulation to improve the prediction accuracy of the system. Lastly, the model is evaluated on a physical implementation to analyze its performance. There are multiple findings as part of the result of this thesis, like the economic benefit of using such a system will encourage many users to participate in Demand response programs, this in turn will help in the reduction of pollution originating from non-renewable energy generators.Item Open Access A systematic mapping study on development and use of AI planning tools(2021) Philippsohn, RobertArtificial intelligence (AI) planning is a big area in the AI field with many needs and special problems. Therefore, it needs tools to suit these special problems and request, as well as for trends in the AI planning community. Since 1971 there has been an influx of many tools that assist insolving planning problems and making plans. To give a better overview of the available landscape of AI planning tools this systematic mapping study was conducted and try also to shows what software engineering principles are used in creating the tools. We also try to depict in which industry domains the AI planning tools are used and how many papers mention the tools being used in the industry. In the end, we conclude that there are at least 106 different tools out there, with only a fraction being used in the industry. While only a small part of the tools are talked about being used in the industry, this small part is covering a wide array of industry domains.Item Open Access The impact of domain models on energy consumption of classical planners(2025) Tekin, SerhatThe increasing integration of artificial intelligence into real-world systems has intensified concerns about the ecological footprint of computational processes. As the capabilities of AI expand and their applications spread into diverse areas of society, questions of efficiency are no longer confined to algorithmic performance alone but extend to the broader impact of computation on energy usage. Within this context classical planning provides a particularly relevant case since it is a core technique in automated planning. Research in this field has traditionally emphasized runtime efficiency, plan quality and algorithmic design while the energetic dimension has remained largely neglected. This thesis examines that omission by shifting the focus from planners to the domain models that constitute their input. Through systematic modifications of syntactic, semantic and solvability related features it demonstrates that modeling decisions can exert a measurable influence on energy consumption. Rather than viewing energy use as an inherent property of planners, the study shows it to emerge from the interaction between algorithmic behavior and representational form. The work introduces a replicable framework that combines controlled domain transformations with fine grained energy measurements, thereby enabling systematic evaluations of energy usage in symbolic AI. The empirical analysis indicates that syntactic variations usually result in only minor fluctuations, whereas modeling inefficiencies can increase energy demand, with operator arity standing out as a recurring factor. The most pronounced effects arise from solvability constraints which, depending on the planner and the domain, can lead to substantial increases in energy usage or in some cases reductions. Taken together the results highlight that domain modeling is not only a matter of syntactic correctness or semantic adequacy but also of energetic efficiency. The contribution of this thesis is twofold. It establishes a framework for investigating the energy implications of domain features and provides empirical evidence that modeling choices shape the energy profile of planning systems. These findings offer a foundation for further research and provide practical guidance for approaching domain modeling with energy consumption in mind.Item Open Access Service Injection von TOSCA-basierten Diensten in Java-Anwendungen(2019) Kiefer, LeonViele Cloud Anwendungen bestehen aus mehreren Komponenten und Services, die miteinander kommunizieren. Die Topology and Orchestration Specification for Cloud Applications (TOSCA) definiert einen Standard, um solche Cloud Anwendungen zu beschreiben und zu managen. Um Cloud Services in lokalen Anwendungen zu verwenden, müssen abhängig von der verwendeten Kommunikationstechnologie und der Implementierung der Cloud Services Verbindungsinformationen ausgetauscht werden und spezielle Client Bibliotheken verwendet werden. Dies sorgt für eine hohe Komplexität und schlechte Wiederverwendbarkeit der Implementierung von lokalen Anwendungen. In dieser Arbeit wird ein Konzept vorgestellt, bei dem die komplexe und technologiespezifische Kommunikation nicht in der lokalen Anwendung implementiert wird. Stattdessen werden vorgefertigte Adapter für die jeweilige Technologie mit den passenden Verbindungsinformationen der externen Services in die lokale Anwendung injiziert. Es wird ein Programmiermodell vorgestellt mit dem diese lokalen Anwendungen entwickelt und bereitgestellt werden können. Externen Services werden automatisiert bereitgestellt, wenn diese von der lokalen Anwendung benötigt werden. Die Umsetzbarkeit des Konzeptes wird anhand einer prototypischen Implementierung in Java und der Verwendung von TOSCA-basierten Cloud Services validiert.Item Open Access Economic feasibility analysis of vehicle-to-grid service from an EV owner's perspective in the german electricity market(2020) Malya, Prasad PrakashThe increasing number of Electrical Vehicles (EV) has led to a tremendous amount of inac- cessible electric energy stored in the EV batteries. Vehicle-to-grid (V2G) services can utilize this energy to profit the EV owners’ and stabilize the grid during faults and fluctuations. This thesis presents a novel way of estimating the profitability of V2G from the EV owner’s perspective. The main contribution of this thesis is the formulation of a profit model that includes the EV battery degradation due to V2G. The work done so far considers fixed battery degradation cost, whereas in this work, an online battery degradation model is used. This model takes into account the parameters that represent real-life scenarios resulting in more accurate battery degradation estimation. The V2G profit model uses the electricity price signal from the German energy market for the year 2019 and estimates the annual profit. The first part of the thesis calculates the profitability of V2G, where EV can participate freely in energy arbitrage. This analysis explores the range of profit when EV participates in V2G purely based on the EV owner’s discretion. A sensitivity analysis is done with respect to battery capacity, battery efficiency, and driving distance. The second part of the thesis evaluates the profitability of EV participating in the German energy market’s frequency regulation ancillary service.=. The analysis compares the profitability of EV participating in primary, secondary, and tertiary frequency regulation services. The results of this thesis provide several findings, the potential profit from V2G services should encourage EV owners’ to participate in the V2G services. Additionally, participating in V2G service can extend the life of the battery. However, this depends on the battery technology and battery usage during V2G services. Ancillary services provide higher potential profit compared to energy arbitrage because of the high remuneration scheme. The ancillary services with both capacity and energy payment result in higher profit compared to ancillary services with only capacity payment.Item Open Access Enhancing HTN planning with deep reinforcement learning for method selection(2025) Bahrami, SepidehAutomated planning is a central area within Artificial Intelligence (AI), enabling intelligent behavior in domains such as cloud computing, autonomous systems, context-aware activity recognition, and smart environments. Hierarchical Task Network (HTN) planning, which decomposes complex tasks into simpler subtasks using predefined methods, has proven effective in such structured domains. However, its performance is often constrained by static method selection strategies that lack adaptability to varying planning contexts. To address this limitation, this thesis proposes a neuro-symbolic framework that integrates HTN planning with Deep Reinforcement Learning (DRL), combining the strengths of symbolic reasoning and data-driven learning. Among the available DRL algorithms, Deep Q-Learning (DQL) is particularly suitable due to its off-policy nature, batch-efficient learning, and robust generalization across symbolic planning states. These characteristics align well with deterministic and hierarchical planners, enabling offline learning from curated datasets without requiring interactive exploration. The proposed integration introduces a learning-based decision layer that improves adaptability while preserving the reproducibility and determinism of the underlying planner. The effectiveness of this approach is demonstrated through a comprehensive evaluation across planning efficiency, memory consumption, and plan quality. Results highlight the potential of reinforcement learning to enhance classical HTN systems and support intelligent decision-making in complex, structured environments.Item Open Access Concept and implementation of digital beacons(2015) Chughtai, Muhammad BilalItem Open Access Die Rolle von Verschränkung im Quantencomputing : Speedup und Konsensusprotokolle(2019) Salm, Marie OliviaIn Zukunft werden Quantencomputer Probleme womöglich effizienter lösen als klassische Computer. Dies wäre eine bahnbrechende Errungenschaft und erweckt daher große Hoffnungen bei Forschung und Wirtschaft. Noch befindet sich das Gebiet der Quanteninformatik und des Quantencomputings vor allem in der Grundlagenforschung, und die Entwicklung eines leistungsfähigen Quantencomputers liegt noch in weiter Ferne. Dennoch werden bereits heute Quantenalgorithmen entwickelt, die eine Überlegenheit gegenüber klassischen Algorithmen aufzeigen könnten. So könnten verteilte Systeme von den quantenmechanischen Eigenschaften unter anderem durch Kommunikationsersparnisse profitieren. In dieser Arbeit wurde untersucht, ob das Phänomen der Verschränkung für den möglichen Speedup gegenüber klassischen Computer verantwortlich ist. Dazu wurden Annahmen wissenschaftlicher Arbeiten zusammengefasst. Des Weiteren wurde das Konsensusprotokoll Paxos mit quantenmechanischen Konzepten erweitert. Für eine der Erweiterungen wurde der verschränkte W-Zustand für die Wahl eines Proposers eingesetzt. In der zweiten Erweiterung wurde für die Bestimmung einer Rundennummer Superposition verwendet. Zudem wurde das 2-Phasen-Commit-Protokoll in unterschiedlichen Varianten mit dem GHZ-Zustand erweitert. Auch für das 3-Phasen-Commit-Protokoll wurde der W-Zustand für die Wahl eines Koordinators verwendet. Die Ergebnisse zeigen unter anderem, dass eine Reduzierung des Kommunikationsaufwands bei Paxos und dem 3-Phasen-Commit-Protkoll möglich ist. Es zeigt sich auch, dass eine Deblockierung des erweiterten 2-Phasen-Commit-Protokolls in der behandelten Weise nicht möglich ist.