26 research outputs found
How to understand better “Smart Vehicle”? Knowledge extraction for the automotive sector using web of things
No full textGoal-Oriented End User Development of Web of Things Compositions
No full textThe adoption of IoT devices has expanded due to their benefits, and the Web of Things (WoT) standard has further simplified access. However, enabling end users — especially non-technical ones — to compose WoT environments remains complex due to challenges in expertise, effort, and time. This thesis systematically analyzes the situation, identifying three key barriers: insufficient interoperability, usability, and usefulness. A set of requirements for end-user Things composition is derived and used to assess existing WoT research, revealing shortcomings in supporting heterogeneous Things composition.
To address these issues, this thesis proposes GrOWTH (Goal-oriented End User Development for Web of Things) — a holistic framework integrating software engineering principles, formalisms, methods, and tools for Things interoperability, interaction, and composition. GrOWTH tackles vendor- and technology-dependent systems with a semi-automatic, knowledge-based approach, allowing personalized Things usage. A goal-oriented, multimodal interface enhances usability, while AI planning-based composition simplifies development and reduces effort.
The feasibility and applicability of these concepts are demonstrated through various evaluation experiments and empirical user studies. The thesis concludes with an evaluation based on requirements assessment and technical evaluation of the approach with a smart home application scenario, accompanied by an outlook towards future research directions.:1 Introduction
2 Problem and Requirements Analysis
3 State of the Art
4 End User Development WoT Composition
5 GrOWTH Things Interoperability
6 GrOWTH End User Interaction
7 GROWTH Things Composition
8 Evaluation
9 Conclusion and Outlook
A Problem Analaysis Materials
B GROWTH:TI Materials
C GROWTH:EI Materials
D GROWTH:TC Material
Goal-Oriented End User Development of Web of Things Compositions
No full textThe adoption of IoT devices has expanded due to their benefits, and the Web of Things (WoT) standard has further simplified access. However, enabling end users — especially non-technical ones — to compose WoT environments remains complex due to challenges in expertise, effort, and time. This thesis systematically analyzes the situation, identifying three key barriers: insufficient interoperability, usability, and usefulness. A set of requirements for end-user Things composition is derived and used to assess existing WoT research, revealing shortcomings in supporting heterogeneous Things composition.
To address these issues, this thesis proposes GrOWTH (Goal-oriented End User Development for Web of Things) — a holistic framework integrating software engineering principles, formalisms, methods, and tools for Things interoperability, interaction, and composition. GrOWTH tackles vendor- and technology-dependent systems with a semi-automatic, knowledge-based approach, allowing personalized Things usage. A goal-oriented, multimodal interface enhances usability, while AI planning-based composition simplifies development and reduces effort.
The feasibility and applicability of these concepts are demonstrated through various evaluation experiments and empirical user studies. The thesis concludes with an evaluation based on requirements assessment and technical evaluation of the approach with a smart home application scenario, accompanied by an outlook towards future research directions.:1 Introduction
2 Problem and Requirements Analysis
3 State of the Art
4 End User Development WoT Composition
5 GrOWTH Things Interoperability
6 GrOWTH End User Interaction
7 GROWTH Things Composition
8 Evaluation
9 Conclusion and Outlook
A Problem Analaysis Materials
B GROWTH:TI Materials
C GROWTH:EI Materials
D GROWTH:TC Material
An Automated Cyclic Planning Framework Based on Plan-Do-Check-Act for Web of Things Composition
No full textLinguistic rule-based methods for the extraction of medical summaries to benefit patients progression tracking
Full text linkClinical narratives contain useful information that can complement the patient progress records which are obtained throughout the patient’s medical and treatment duration. In order to understand the clinical narratives content, medical concepts that include events and temporal information should be performed. This study addresses this issue based on a linguistic rule-based approach which combines domain knowledge, extraction modules and temporal linker component. This is in contrast to the fundamentals adopted by the major works based on machine learning. The proposed work’s performance is therefore evaluated against a machine learning based approach and a knowledge intensive approach. Results have shown its strength regardless of its different nature
Interoperability in Internet of Things Infrastructure: Classification, Challenges, and Future Work
No full text
