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Slides chase 2019 connected health conference - thursday 26 september 2019 - iamhappy towards an io-t knowledge-based cross-domain well-being recommendation system for happiness (4)

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Paper: IAMHAPPY: Towards An IoT Knowledge-Based Cross-Domain Well-Being Recommendation System for Everyday Happiness
IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Conference

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Slides chase 2019 connected health conference - thursday 26 september 2019 - iamhappy towards an io-t knowledge-based cross-domain well-being recommendation system for happiness (4)

  1. 1. IAMHAPPY: Towards an IoT Knowledge-Based Cross-Domain Well-Being Recommendation System for Happiness Ohio Center of Excellence in Knowledge-Enabled Computing Dr. Amelie Gyrard Kno.e.sis Research Center Department of Computer Science and Engineering, Wright State University, Dayton, Ohio (USA) Research website LinkedIn, Twitter, Facebook, Google Group Dr. Amit Sheth AI Institute University of South Carolina
  2. 2. Agenda • Introduction to Happiness and Well-Being • Towards a Recommender System for Happiness and Well-Being • Reusing the Knowledge Expertise: ̶ Demo: LOV4IoT Knowledge Repository ̶ Demo: SLOR Reasoning Engine and Recommender System • Conclusion & Future Work 2
  3. 3. The Importance of Positive Thinking: Happiness and Well-Being 3 ● Have you already ask yourself how to feel happy everyday? University of Pennsylvania Positive Psychology Center
  4. 4. Happiness Manager New Trend ● Is there a “Chief Happiness Officer” or “Happiness Manager” at your institute?
  5. 5. Dr. Masaru Emoto's Rice and Water Experiments Dr. Emoto was President Emeritus of the International Water For Life Foundation, a non-profit organization based in Oklahoma City in the United States. In 1992, Emoto became a Doctor of Alternative Medicine at the Open International University for Alternative Medicine in India. http://www.truthin7minutes.com/negative-rice-experiment/, https://www.masaru-emoto.net/en/science-of-messages-from-water/ Dr. Masaru Emoto's Rice Experiment
  6. 6. Affective Computing 6 How to find the right keywords/key phrases that are synonyms? • Affective Sciences • Affective Computing • Emotions and specific emotions name (e.g., happy) • Wearable devices for emotion • Positive thinking • Positive psychology • Etc.
  7. 7. Limitations of Current Emotion-related Applications • Emotion applications are focused on facial recognitions • Most of the current IoT applications are just visualizing the data.
  8. 8. Literature Survey: Limitations 8 Covering one specific emotion per application Need to support new multimodal sensors Need to unify the reasoning mechanism to interpret (IoT) data Need to support complementary domains
  9. 9. Research Challenges (RC) • (RC1) Which physiological data generated by sensors are needed to deduce users' emotions? (e.g., a stress sensor, does the serotonin level help understanding depression level?). • (RC2) How to integrate knowledge from complementary domains? (e.g., naturopathy and mindful activities). • (RC3) How to deduce meaningful knowledge from sensor data? How to design the well-being recommendation system? 9 RC RC 3 RC 2 RC 1
  10. 10. Agenda • Introduction to Happiness and Well-Being • Towards a Recommender System for Happiness and Well-Being • Reusing the Knowledge Expertise: ̶ Demo: LOV4IoT Knowledge Repository ̶ Demo: SLOR Reasoning Engine and Recommender System • Conclusion & Future Work 10
  11. 11. Our Solution: IAMHAPPY • An innovative IoT-based well-being recommendation system to encourage every day happiness. • A (Semantic) Web-based knowledge repository helps analyze data produced by IoT devices to understand users' emotions and health. • The knowledge repository is integrated with a rule-based engine to suggest recommendations. 11
  12. 12. IAMHAPPY Architecture 12
  13. 13. Reusing Reliable Scientific Knowledge 13 Knowledge Repository based on Reliable Scientific Research Taichi health and well-being benefits: ● Heart, bones, nerves, muscles, immune system, and the mind. ● Enhance work productivity, creativity, and sports performance. ● Enhancing mood
  14. 14. Cross-Domain Knowledge Repository 14 Qigong Art Therapy Music Therapy Acupuncture Visualization Techniques Taichi Etc. Naturopathy/ Food Fitness Obesity Emotion Sleep Depression Stress/Anxiety Yoga Ontology-based projects found for those topics Meditation Topics published as reliable scientific publication Legend:
  15. 15. Research Studies on Meditation • Effects of meditation on the brain Paul Ekman, pioneer in the study of emotions Matthieu Ricard, PhD in cellular genetics and monk.
  16. 16. NCCIH complementary and alternative medicine: ● Whole medical systems such as homeopathy, naturopathy, traditional Chinese medicine, and ayurveda. ● Mind-body medicine such as meditation, mental healing, art therapy, music therapy, and dance therapy. ● Biologically based practices such as dietary supplements, herbal supplements. ● Manipulative and body-based practices such as spinal manipulation (both chiropractic and osteopathic) and massage. ● Energy therapies such as qigong, reiki, therapeutic touch, and electromagnetic therapy. US NSF NIH NCCIH
  17. 17. Demo & Reminder: Ontology, Schema, and Knowledge Graph Structured information automatically built by machines =>
  18. 18. Demo & Background: Schema.org Structured information automatically built by machines =>
  19. 19. Demo & Background: Google Knowledge Graph Video (2 mins 44): https://youtu.be/mmQl6VGvX-c Blog: https://googleblog.blogspot.com/2012/05/introducing-knowledge-graph-things-not.html Google Knowledge Graph 2012
  20. 20. Paper: “Semantic Web of Things: an analysis of the application semantics for the IoT moving towards the IoT convergence” [Jara et al. 2014] Why Do We Use Semantic Web Technologies Within Internet of Things? ⇒ How to provide a common description of sensor data to later reason on it? • Machine-understandable data • Describe data with common vocabularies • Reuse domain knowledge • Link to other data • Ease the reasoning 20
  21. 21. Workflow: From Data to Recommendations 21 Paper: Cross-Domain Internet of Things Application Development: M3 Framework and Evaluation [Gyrard et al. 2015]. International Conference on Future Internet of Things and Cloud (FiCloud) (Cited x60 in Sept. 2019). White Paper: Semantic Interoperability for the Web of Things [Murdock et al. 2016] (35 authors)
  22. 22. Agenda • Introduction to Happiness and Well-Being • Towards a Recommender System for Happiness and Well-Being • Reusing the Knowledge Expertise: ̶ Demo: LOV4IoT Knowledge Repository ̶ Demo: SLOR Reasoning Engine and Recommender System • Conclusion & Future Work 22
  23. 23. Reusing domain knowledge from Ontology Catalogs ● BioPortal for biomedical ontologies [1] ● Linked Open Vocabularies (LOV) [2] ● Linked Open Vocabularies for Internet of Things (LOV4IoT) [3] ○ Exploring knowledge from ontologies and scientific publications [1] https://bioportal.bioontology.org/, [2] https://lov.linkeddata.es/dataset/lov/, [3] http://lov4iot.appspot.com/ RC 1, 2, 4
  24. 24. Cannot Find Ontologies on BioPortal for Our Needs Knowledge repositories for the topics that we are interested in are needed
  25. 25. LOV4IoT-Extensions Emotion (15) Fitness (5) Food (40) Obesity (4) Sleep (1) Depression (6) Stress (1) Anxiety • Knowledge repository extended to support Happiness and Well-Being Systems Topic (# ontology-based projects) Acupuncture (3) Legend:
  26. 26. Demo: Reusing Domain Knowledge already Designed within Applications LOV4IoT Project: http://lov4iot.appspot.com/?p=ontologies 26 Classify Exchange Annotate Annotate Collect
  27. 27. Demo: Ontology Catalog for Food 27 http://lov4iot.appspot.com/?p=lov4iot-food <= New projects can be added <= Ontology code availability
  28. 28. KE4WoT: Domain Knowledge Extraction Research Methodology 28 Outstanding Paper Award - Concept Extraction from Web of Things Knowledge Bases. International Conference WWW/Internet. 21-23 October 2018, Budapest, Hungary. Mahda Noura, Amelie Gyrard, Sebastian Heil, and Martin Gaedke
  29. 29. KE4WoT Knowledge Extraction of Popular Terms E.g., Smart Home and Ambient Assisted Living 29 Paper: Automatic Knowledge Extraction to build Semantic Web of Things Applications. Mahda Noura, Amelie Gyrard, Sebastian Heil, Martin Gaedke. IEEE Internet of Things (IoT) Journal 2019. Impact factor: 9.515 in Sept. 2019. 3rd top journal in Computing Systems according to Google Scholar, h5 index=70 29 Also statistics: Extent of re-use among ontologies Planned extensions for numerous domains introduced here.
  30. 30. Agenda • Introduction to Happiness and Well-Being • Towards a Recommender System for Happiness and Well-Being • Reusing the Knowledge Expertise: ̶ Demo: LOV4IoT Knowledge Repository ̶ Demo: SLOR Reasoning Engine and Recommender System • Conclusion & Future Work 30
  31. 31. Demo: Selecting Emotion Sensors and Existing Projects 31http://linkedopenreasoning.appspot.com/?p=slorv2 1 - Choose the “Emotion” domain 2 - Choose a sensor from our dictionary (automatically retrieved) 3 - Projects using this sensor are automatically retrieved from the LOV4IoT knowledge repository
  32. 32. Demo: Selecting Health Sensors and Existing Rules to Interpret data 32 http://linkedopenreasoning.appspot.com/?p=slorv2 1 - Generic solution for another domain: “Healthcare” 3 - Rules automatically retrieved for a specific sensor 2 - Choose a sensor from our dictionary (automatically retrieved)
  33. 33. Demo: Using Reliable Knowledge for Recommendations • Current suggestions provide the source of knowledge Most of the time scientific publications who designed ontologies 33 http://sensormeasurement.appspot.com/?p=naturopathy Scientific publications are provided to prove the veracity of the recommendations
  34. 34. Planned Evaluation ● Planned evaluation ○ User feedback (need more robust software) ○ Physiological datasets ○ Partnership with clinicians to access depressed-diagnosed patients ● Guidelines to evaluate patient's happiness and reduce depression ○ Satisfaction With Life Scale (SWLS) ○ Oxford Happiness Questionnaire (OHQ) ○ Gratitude Questionnaire (GQ-6) ○ Circumplex mood model ○ Oldenburg burnout inventory 34
  35. 35. Agenda • Introduction to Happiness and Well-Being • Towards a Recommender System for Happiness and Well-Being • Reusing the Knowledge Expertise: ̶ Demo: LOV4IoT Knowledge Repository ̶ Demo: SLOR Reasoning Engine and Recommender System • Conclusion & Future Work 35
  36. 36. Conclusion & Future Work ● IAMHAPPY: Towards An IoT Knowledge-Based Cross-Domain Well-Being Recommendation System for Everyday Happiness ○ Societal impact ● Future work: ○ Integration with real sensors ○ Evaluation with real patients 36
  37. 37. Acknowledgments & Questions 37 ● Thanks to the Kno.e.sis team for fruitful discussions. ● The opinions expressed are those of the authors and do not reflect those of the sponsors.
  38. 38. IAMHAPPY: Towards an IoT Knowledge-Based Cross-Domain Well-Being Recommendation System for Happiness Ohio Center of Excellence in Knowledge-Enabled Computing Dr. Amelie Gyrard Kno.e.sis Research Center Department of Computer Science and Engineering, Wright State University, Dayton, Ohio (USA) Research website LinkedIn, Twitter, Facebook, Google Group Dr. Amit Sheth AI Institute University of South Carolina

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