Tesi etd-04292025-153323 |
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Tipo di tesi
Tesi di dottorato di ricerca
Autore
MATTIOLI, ANDREA
URN
etd-04292025-153323
Titolo
End User Control of Smart Home Automations Through Mobile Augmented Reality and Recommender Systems
Settore scientifico disciplinare
IINF-05/A - Sistemi di elaborazione delle informazioni
Corso di studi
INGEGNERIA DELL'INFORMAZIONE
Relatori
tutor Prof. Paternò, Fabio
tutor Prof. Cimino, Mario Giovanni Cosimo Antonio
tutor Prof. Cimino, Mario Giovanni Cosimo Antonio
Parole chiave
- end-user development
- home automation
- internet of things
- mobile augmented reality
- recommender systems
- trigger-action programming
Data inizio appello
06/05/2025
Consultabilità
Non consultabile
Data di rilascio
06/05/2028
Riassunto
In recent years, the so-called smart objects have become increasingly common in our everyday environments, making the vision of an Internet of Things a reality.
They promise to improve our lives, optimising comfort, energy management, and in general our daily well-being.
To make the most of the possibilities of these ecosystems of connected objects and services, it is necessary to use platforms that allow their coordinated use, enabling the creation of multi-object automations.
However, there are several problems with these platforms, both commercial and research ones.
Firstly, it isn’t easy to balance expressiveness with ease of use. Indeed, home automation platforms range from allowing only simple "if-then" automations to the possibility of defining actual programs.
However, the most expressive platforms tend to become difficult to use and unengaging.
An unbalanced expressive capacity can make these platforms of little use to the user. Furthermore, the selection and configuration of functionalities to be used in automations can be a complex operation.
It is, therefore, necessary to find solutions to make this task easier for users, using representations that allow them to form an accurate mental model of the functionalities of the tools and consequently use them correctly.
This dissertation will present how mobile-enabled Augmented Reality can minimise these problems and empower users to seamlessly create automation in smart environments. It will also discuss how recommender systems can be introduced in this context, further facilitating operations on the platform.
Two main cycles of platform development, each culminating in a user study, will be reported, along with the additional preliminary studies and interviews conducted.
Together, these activities enabled us to answer the defined research questions and delineate the ‘lessons learned’, which can serve the development of further solutions in this regard.
They promise to improve our lives, optimising comfort, energy management, and in general our daily well-being.
To make the most of the possibilities of these ecosystems of connected objects and services, it is necessary to use platforms that allow their coordinated use, enabling the creation of multi-object automations.
However, there are several problems with these platforms, both commercial and research ones.
Firstly, it isn’t easy to balance expressiveness with ease of use. Indeed, home automation platforms range from allowing only simple "if-then" automations to the possibility of defining actual programs.
However, the most expressive platforms tend to become difficult to use and unengaging.
An unbalanced expressive capacity can make these platforms of little use to the user. Furthermore, the selection and configuration of functionalities to be used in automations can be a complex operation.
It is, therefore, necessary to find solutions to make this task easier for users, using representations that allow them to form an accurate mental model of the functionalities of the tools and consequently use them correctly.
This dissertation will present how mobile-enabled Augmented Reality can minimise these problems and empower users to seamlessly create automation in smart environments. It will also discuss how recommender systems can be introduced in this context, further facilitating operations on the platform.
Two main cycles of platform development, each culminating in a user study, will be reported, along with the additional preliminary studies and interviews conducted.
Together, these activities enabled us to answer the defined research questions and delineate the ‘lessons learned’, which can serve the development of further solutions in this regard.
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