After the links, from which you can download the whole thesis and see the presentation slides used during the Ph.D. defense, you can find a brief summary of the thesis.
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Summary of the thesis: "IoT Notifications: from disruption to benefit - Architectures for the future of notifications in the IoT"
The growing number of mobile and IoT devices able to generate and show incoming notifications is fostering the spread of notifications in people lives. Nonetheless, although users are getting used to them, their presence is not always perceived as a benefit by recipients. With the aim of improving user experience with notifications, two different approaches are presented in this dissertation. The former acts at the distribution level, i.e., notifications are intercepted and then a system decides if, when, and how to show them; while the latter acts at the design level, i.e., notifications and their distribution strategies are designed with the aim of reducing user disruption and exploiting all the benefits that the availability of multiple devices could bring.
An IoT architecture is proposed for each approach: the Smart Notification System that relies on machine learning algorithms to adequately manage incoming notifications, and the XDN (Cross-Device Notification) framework that assists developers in creating cross-device notifications by scripting. The modular nature of both architectures allowed the simultaneous development and test of different independent but compatible subsystems and their exploitation in preliminary deployment sessions. The results, feedbacks and lessons learned from such sessions can foster the development of future solutions in the IoT notifications field and related domains.
An IoT architecture is proposed for each approach: the Smart Notification System that relies on machine learning algorithms to adequately manage incoming notifications, and the XDN (Cross-Device Notification) framework that assists developers in creating cross-device notifications by scripting. The modular nature of both architectures allowed the simultaneous development and test of different independent but compatible subsystems and their exploitation in preliminary deployment sessions. The results, feedbacks and lessons learned from such sessions can foster the development of future solutions in the IoT notifications field and related domains.
Acknowledgements
I know that it is not a good practice to use emoticons in a doctoral thesis, but I think I can do it in the acknowledgments paragraph.
As almost everyone knows, I love to speak :-). I’m not as good as my brother to establish a conversation with every person, animal or object present on the earth XD, but I cannot declare that I can stay more that a minute without speaking. Now that it is clear, I will use the same approach I usually use when I am near a person (and I am not tired, this is the only situation in which I could be a silent person) to say thanks to the people who helped me during my Ph.D.
At first, I want to thank all the people that guided me and “walked” near me during the Ph.D.! Specifically, I want to thank Fulvio Corno and Luigi De Russis, my mentors. Their patience and support allowed me to grow, improve my skills, and, most important, arrive at the end of the Ph.D. :-) In addition, I would like to thank them, together with Laura Farinetti, a teacher of rare goodness, for the opportunity they gave me to discover my passion in teaching. They involved me in the teaching activities of the two courses “Ambient Intelligence” and “Social Networking: technologies and applications” letting me improve my teaching skills and, maybe, find my future way.
Then, I would like to thank all the other members and alumni of the e-Lite research group for their support: Sebastian Aced Lopez, who convinced me to continue my training with a Ph.D., Alberto Monge Roffarello and Juan Pablo Sáenz that started their Ph.D. in our research group one year before my departure, and Fabio Ballati who started a few days before my last day.
Moreover, I’m indebted with all the TIM members: Pino Castrogiovanni, my industrial tutor and Claudio Borean who guided me in cooperating within the JOL Swarm team. Also, I would like to thank Dario, Ennio, Roberta, Giuseppe and Alfonso who cooperated with me in some projects and that taught me a lot of industrial tricks that I am appreciating now in my new job.
Furthermore, I want to thank all the people I have met in these years, even if only for a few moments, in the department, in the laboratory (“lab6” has been my second house during the Ph.D., so Alessandro, Andrea, Francesco, Roberta, Alberto and Giuseppe were my second family) and also all around the Politecnico.
And it is not finished: I would like to thank Andrea Marcelli for involving me in some of his projects and supporting me in almost all the machine learning experiments, and also, Edoardo Fadda, Giovanni Zenezini, Maliheh Ghajargar, Rosario Scatamacchia, Carmelo Migliore, Luca Cagliero, and Evelina Di Corso for their patience in the collaborations we made during some extra projects carried on during the Ph.D.
I’m proud of have been part of the DAUIN department at Politecnico di Torino but also of the TIM JOL Swarm team and I hope to continue to meet all of you in the future! ;-)
Finally, I would like to thank all the people who helped me by testing the XDN framework: Alberto Monge Roffarello, Luca Venturini, Alberto Cannavò, Fabio Ballati, Federica Bazzano, Federico Salaroglio, Gianpaolo Paterno, Giovanni Piumatti, Giuseppe Ministeri, Juan Pablo Sáenz, Luca Mannella, Orazio Scivolone, Tamer Saadeh and Mohammad Ghazi Vakili.
Ok, if you arrived here and you are not yet in the list, the answer to your question is: NO, I did not forget you. However, I wanted to leave you at the end to oblige you to read everything XD!
I am forever grateful to my parents, Rosario and Francesca, my brother Andrea, all the members of my big family (aunts, uncles, cousins, and grandma) and all my friends (you are too many to be mentioned in a few lines, so I will thank you personally after the discussion XD) who have always supported and encouraged me.
And last, but not the least, I would like to thank the reviewers of this thesis: even though I will discover who you are only when I will have finished to write the thesis, I would like to thank you for your work and your suggestions.
As almost everyone knows, I love to speak :-). I’m not as good as my brother to establish a conversation with every person, animal or object present on the earth XD, but I cannot declare that I can stay more that a minute without speaking. Now that it is clear, I will use the same approach I usually use when I am near a person (and I am not tired, this is the only situation in which I could be a silent person) to say thanks to the people who helped me during my Ph.D.
At first, I want to thank all the people that guided me and “walked” near me during the Ph.D.! Specifically, I want to thank Fulvio Corno and Luigi De Russis, my mentors. Their patience and support allowed me to grow, improve my skills, and, most important, arrive at the end of the Ph.D. :-) In addition, I would like to thank them, together with Laura Farinetti, a teacher of rare goodness, for the opportunity they gave me to discover my passion in teaching. They involved me in the teaching activities of the two courses “Ambient Intelligence” and “Social Networking: technologies and applications” letting me improve my teaching skills and, maybe, find my future way.
Then, I would like to thank all the other members and alumni of the e-Lite research group for their support: Sebastian Aced Lopez, who convinced me to continue my training with a Ph.D., Alberto Monge Roffarello and Juan Pablo Sáenz that started their Ph.D. in our research group one year before my departure, and Fabio Ballati who started a few days before my last day.
Moreover, I’m indebted with all the TIM members: Pino Castrogiovanni, my industrial tutor and Claudio Borean who guided me in cooperating within the JOL Swarm team. Also, I would like to thank Dario, Ennio, Roberta, Giuseppe and Alfonso who cooperated with me in some projects and that taught me a lot of industrial tricks that I am appreciating now in my new job.
Furthermore, I want to thank all the people I have met in these years, even if only for a few moments, in the department, in the laboratory (“lab6” has been my second house during the Ph.D., so Alessandro, Andrea, Francesco, Roberta, Alberto and Giuseppe were my second family) and also all around the Politecnico.
And it is not finished: I would like to thank Andrea Marcelli for involving me in some of his projects and supporting me in almost all the machine learning experiments, and also, Edoardo Fadda, Giovanni Zenezini, Maliheh Ghajargar, Rosario Scatamacchia, Carmelo Migliore, Luca Cagliero, and Evelina Di Corso for their patience in the collaborations we made during some extra projects carried on during the Ph.D.
I’m proud of have been part of the DAUIN department at Politecnico di Torino but also of the TIM JOL Swarm team and I hope to continue to meet all of you in the future! ;-)
Finally, I would like to thank all the people who helped me by testing the XDN framework: Alberto Monge Roffarello, Luca Venturini, Alberto Cannavò, Fabio Ballati, Federica Bazzano, Federico Salaroglio, Gianpaolo Paterno, Giovanni Piumatti, Giuseppe Ministeri, Juan Pablo Sáenz, Luca Mannella, Orazio Scivolone, Tamer Saadeh and Mohammad Ghazi Vakili.
Ok, if you arrived here and you are not yet in the list, the answer to your question is: NO, I did not forget you. However, I wanted to leave you at the end to oblige you to read everything XD!
I am forever grateful to my parents, Rosario and Francesca, my brother Andrea, all the members of my big family (aunts, uncles, cousins, and grandma) and all my friends (you are too many to be mentioned in a few lines, so I will thank you personally after the discussion XD) who have always supported and encouraged me.
And last, but not the least, I would like to thank the reviewers of this thesis: even though I will discover who you are only when I will have finished to write the thesis, I would like to thank you for your work and your suggestions.
A brief overview of all the contributions provided in the thesis
Figure 1: Architecture of the Smart Notification System
Figure 2: Architecture of the XDN framework
Figure 3: Screenshot of the XDN GUI