This dissertation was written as a part of the MSc in Data Science at the International
Hellenic University. A key motivation for the thesis comes from the expanding field of
unmanned aerial vehicles and their applications in health, where we experienced a
rather big gap in the existence of an ontology that would cover the specific domain.
Unmanned Aerial Vehicles (UAVs), commonly known as drones, have emerged as
transformative entities shaping contemporary technological landscapes. This thesis
investigates the domain of drone technology, exploring its terminology, historical
evolution, and the manufacturing challenges inherent in their development.
Moving beyond theoretical constructs, the research investigates practical
applications across diverse sectors. It scrutinizes the historical trajectory of drones, from
their experimental phase during the First World War to their current ubiquity in military
arsenals worldwide. Additionally, the thesis navigates the intricate landscape of drone
types, ranging from fixed-wing models to multi-modal drones with versatile
capabilities. The synthesis of theoretical frameworks, historical context, and practical
applications seeks to provide a holistic understanding of drone technology, contributing
to the ongoing discourse in the field of unmanned vehicle science and technology.
The thesis utilizes Ontology Engineering to create an ontology in the domain of
drones and their applications in the healthcare ecosystem. The aim of the thesis was
firstly to understand the business needs of drone operated missions in healthcare, and
then build a corresponding ontology, in an efficient way that would cover the whole
range of health-related information carried through drones. Specifically, the thesis has
two objectives: a) Explore and understand the drone environment along with its
applications in health b) Develop an ontology to display this information and show how
such ontology can be useful in drone missions operated in health. After the development
of the ontology, the latter was evaluated thoroughly against experimental information
and data. The evaluation, mainly through SPARQL queries, shows that the ontology
meets the business needs of drone mission operators and indeed allows the distribution
-ivof data across the network of this group, such as available stations with specific drone
requirements.
Collections
Show Collections