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Saguna Nr1.Ps ISSN: 1402-1544 ISBN 978-91-7439-XXX-X Se i listan och fyll i siffror där kryssen är DOCTORAL T H E SIS Department of Computer Science, Electrical and Space Engineering Tools within Social Interaction Validation and Context Recognition Activity Saguna Complex Division of Computer Science ISSN: 1402-1544 Complex Activity Recognition and ISBN 978-91-7439-660-7 (print) ISBN 978-91-7439-661-4 (pdf) Context Validation within Social Luleå University of Technology 2013 Interaction Tools Saguna Complex Activity Recognition and Context Validation within Social Interaction Tools Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Dual Award at Monash University and Lulea˚ University of Technology) by Saguna Master of Information Technology (Minor Thesis), Monash University Caulfield School of Information Technology, Faculty of Information Technology, Monash University, Australia and Department of Computer Science, Electrical and Space Engineering, Lulea˚ University of Technology, Sweden Date of submission: April 2013 Supervisors: Professor Arkady Zaslavsky (CSIRO, LTU) Dr. Dipanjan Chakraborty (IBM) Associate Professor Kare˚ Synnes (LTU) Professor David Abramson (Monash University) Printed by Universitetstryckeriet, Luleå 2013 ISSN: 1402-1544 ISBN 978-91-7439-660-7 (print) ISBN 978-91-7439-661-4 (pdf) Luleå 2013 www.ltu.se Declaration I hereby declare that this thesis contains no material which has been accepted for the award of any other degree or diploma in any university or equivalent institution, and that, to the best of my knowledge and belief, this thesis contains no material previously published or written by another person, except where due reference is made in the text of the thesis. Saguna iii To my doting parents (You inspire me always!) v In loving memory of my grandparents & Saroj auntie vii Acknowledgement I am deeply indebted to a number of people who have contributed towards the successful completion of my research. This research work would not have been possible without their support and guidance. The journey of my PhD research is a valuable learning experience for the rest of my life. I have to begin by thanking Prof. Arkady Zaslavsky, my main supervisor and men- tor, who gave me the opportunity to undertake this PhD. I will always remember how you convinced me to pursue PhD studies after the completion of my Masters course. Thank you for believing in me throughout the course of this PhD and motivating me through difficult and challenging times. It was a privilege and invaluable learning experience to work with you. This thesis would not have been possible without your guidance, comments and numerous inputs at all stages. I have knocked many times on your door for help and guidance. Thank you for taking time out for me every time and keeping patience during the numerous delays of publication and thesis drafts. You have always been there just a Skype call away even on weekends and for those midnight paper submissions. Thank you for looking after me at all times during the course of this PhD. I thank my co-supervisor Dr. Dipanjan Chakraborty for his valuable inputs during the different phases of this research as well as his continuous support. I am grateful to you for all the critical and technical comments that you have provided to improve on different aspects of the research. I also thank you for the motivation and encouragement which helped me in the completion of this research work. I thank A/Prof. Kare Synnes, my co-supervisor from Lulea˚ University of Technol- ogy, Lulea,˚ Sweden for his support and encouragement during this PhD. Thank you for your help during all my visits to Lulea˚ without you my PhD would not be a cotutelle degree. I thank Prof. David Abramson for agreeing to be my supervisor from Monash university during the later stages of this PhD. Thank you David for signing all those forms at a day’s notice and managing all administrative issues relating to my PhD degree. I am grateful to a number of people, both from Monash University and Lulea˚ Uni- versity of Technology, who have helped me for various administrative, technical, travel and funding related issues over the duration of my PhD. I thank Prof. Frada Burstein for her constant support and words of encouragement. I still remember at the very beginning of my PhD, how you helped me with the Faculty grant for xi waiving off my fees. I would not be able to start my PhD in time without your support. At Monash University, I am extremely thankful to Michelle Ketchen, Allison Mitchell, Katherine Knight, Akamon Kunkongkapun, Diana Sussman, Julie Austin, Trudi Robinson, Cornelia Lioulios, Denise Cove, Duke Fonias, Rafig Tjahjadi, See Ngieng, Samedin Balla, David Lau, Leeanne Evans, Jack Sotiriou, Vesna Nikolovski, May Chew and Cherie Lau for all their timely support and encouragement every time I met them for various jobs. A special thank you to Rob Gray for his words of encouragement and support during the course of this PhD. At Lulea˚ University of Technology, I thank Lisbet Markgren, Jenny Niemi, Jeanette Buskdal, Monika Ohman,¨ Sven Molin, Ronnie Pekkari and Jonas Ekman for the numerous times I have reached out for your help with administrative and travel related issues. Lisbet, thank you picking up stuff for me and helping us with postal issues. A special thank you to Andreas Nilsson for always taking care of the many technical and not so technical things at LTU. You all made my life in Lulea˚ so much easier and comfortable. I thank my friends and colleagues at Monash Univeristy and Lulea˚ University of Technology for their words of encouragement and support during this PhD. Thank you Kutila Gunasekera, Prem Jayaraman, John Page, Shahaan Ayyub, Luke Steller, Pari Delir Haghighi, Andrey Boytsov, Juwel Rana, Basel Kikhia, and Robert Brannstr¨ om.¨ I specially thank Kutila Gunasekera for helping out with things while I was at Monash campus and especially when I was away at LTU. I thank Jeff Tan at Monash University for his support and words of encouragement during the initial phase of my PhD. I also thank Jens Eliasson and Mikael Larsmark for their help with sensors I used for my research. A special thank you to Prof. Christer Ahlund˚ and again to A/Prof. Kare Synnes for helping out with travel funding and sorting out various administrative issues. I would like to thank Dr. Mark Cameron for his support and guidance during the last phase of this thesis at CSIRO. Thank you Mark for helping me survive in Canberra and for being my mentor during my visit to CSIRO. I would like to thank Karan Mitra, for all the time spent with him discussing, debating and guiding during all stages of this thesis from brain storming to implementation to writing the document and proof-reading. All your effort and patience has significantly contributed towards overcoming all the challenges I faced during my research. I thank Kamal Mitra and Madhurima Mitra for their words of encouragement, prayers, patience and constant support. I thank my Meenakshi Roy for the encouragement and for just being there forever with me. I would also like to thank my friends Bharat Mitra, Neeti Puri, Shubhi Dubey, Nakul Kampasi and Anubhav Sood for their support and good wishes during this long journey. A special thank you to Stephen Mepham for all his support and encouragement. I also take this opportunity to thank my extended family (Usha auntie (and family), Saroj auntie (and family), Veena auntie (and family), Viren mamu (and family), Sanju mamu (and family) and Bhajjo Bhua ji (and family), naming all of you xii will fill up another thesis!) for their blessings, love and good wishes which have definitely helped me over the duration of this PhD. This acknowledgement could not be complete without a big heartfelt thank you to my dear parents. Mom and Dad this thesis would not have been possible if you would not have supported me and done those countless things that you have done for me. I really thank you from the bottom of my heart for all your unconditional love, support, guidance and blessings. Finally, I would like to thank everyone who was supportive for the successful realisation of this thesis in case I have inadvertently missed mentioning you here individually. Saguna Canberra April 2013 xiii Abstract Human activity recognition using sensing technology is crucial in achieving per- vasive and ubiquitous computing paradigms. It can be applied in many domains such as health-care, aged-care, personal-informatics, industry, sports and military. Activities of daily living (ADL) are those activities which users perform in their everyday life and are crucial for day-to-day living. Human users perform a large number of these complex activities at home, office and outdoors. This thesis proposes, develops and validates a mechanism which combines knowl- edge and data-driven approaches for the recognition of complex ADLs. This thesis focuses on the challenging task of capturing data from sensors and recognizing user’s complex activities which are concurrent, interleaved or varied-order in nature. We propose, develop and validate mechanisms and algorithms to in- fer complex activities which are concurrent and interleaved and build a testbed which enables the sharing of this information on social interaction tools (SITs). In particular, we propose, develop and validate a novel context-driven activity theory (CDAT) to build atomic and complex activity definitions using domain knowledge and activity data collected from real-life experimentation. We develop a novel situation- and context-aware activity recognition system (SACAAR) which recognizes complex activities which are concurrent and interleaved and validate it by performing extensive real-life experimentation. We build a novel context- driven complex activity recognition algorithm to infer complex concurrent and interleaved activities.
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