Multimedia Tools and Applications

, Volume 76, Issue 4, pp 5221–5241 | Cite as

Rule-based tools for the configuration of ambient intelligence systems: a comparative user study

  • Federico Cabitza
  • Daniela Fogli
  • Rosa Lanzilotti
  • Antonio Piccinno


This paper describes a 63-participant user study that compares two widely known systems supporting end users in creating trigger-action rules for the Internet of Things and Ambient Intelligence scenarios. The user study is the first stage of a research agenda that concerns the implementation of a novel conceptual framework for the design and continuous evolution of ‘sentient multimedia systems’, namely socio-technical systems, where people and many kinds of hardware/software components (sensors, robots, smart devices, web services, etc.) interact with one another through the exchange of multimedia information, to give rise to intelligent, proactive behaviors. The conceptual framework is structured along three layers - physical, inference and user – and is based on an information space of events, conditions and actions, linked together in Event-Condition-Action rules and operating according to the interconnection metaphor. The results of the user study have provided some indications for the implementation of the user layer, suggesting which could be the most suitable interaction style for rule design by a community of end users (e.g. a family) and which issues should be addressed in such a wide context.


End-user development Internet of things Ambient intelligence Interconnection Rule-based programming User study 


  1. 1.
    Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Computer Networks 54(15):2787–2805. doi:10.1016/j.comnet.2010.05.010 CrossRefMATHGoogle Scholar
  2. 2.
    Augusto JC, Liu J, McCullagh P, Wang H, Yang J-B (2008) Management of uncertainty and spatio-temporal aspects for monitoring and diagnosis in a smart home. International Journal of Computational Intelligence Systems 1(4):361–378. doi:10.1080/18756891.2008.9727632 CrossRefGoogle Scholar
  3. 3.
    Augusto JC, Nugent CD (2006) Smart homes can be smarter. In: Augusto JC, Nugent CD (eds) Designing smart homes, vol 4008. Springer, Berlin Heidelberg, pp 1–15. doi:10.1007/11788485_1 CrossRefGoogle Scholar
  4. 4.
    Bahadori S, Cesta A, Grisetti G, Iocchi L, Leone R, Nardi D, Oddi A, Pecora F, Rasconi R (2004) RoboCare: pervasive intelligence for the domestic care of the elderly. Intelligenza Artificiale 1(1):16–21Google Scholar
  5. 5.
    Bangor A, Kortum PT, Miller JT (2008) An empirical evaluation of the system usability scale. International Journal of Human Computer Interaction 24(6):574–594. doi:10.1080/10447310802205776 CrossRefGoogle Scholar
  6. 6.
    Barricelli BR, Valtolina S (2015). Designing for end-user development in the internet of things. In: Díaz P, Pipek V, Ardito C, Jensen C, Aedo I, Boden A (Eds) End-user development (Vol. 9083, pp 9–24): Springer International Publishing. doi: 10.1007/978-3-319-18425-8_2
  7. 7.
    Benini L, Poncino M (2003) Ambient intelligence: a computational platform perspective. In: Basten T, Geilen M, de Groot H (Eds) Ambient intelligence: impact on embedded sytem design (pp 31–50): Springer US. doi: 10.1007/0-306-48706-3_3
  8. 8.
    Benzi F, Cabitza F, Fogli D, Lanzilotti R, Piccinno A (2015) Gamification techniques for rule management in ambient intelligence. In: De Ruyter B, Kameas A, Chatzimisios P, Mavrommati I (Eds) Ambient intelligence (Vol. 9425, pp 353–356): Springer International Publishing. doi: 10.1007/978-3-319-26005-1_25
  9. 9.
    Bikakis A, Antoniou G (2010) Rule-based contextual reasoning in ambient intelligence. In: Dean M, Hall J, Rotolo A, Tabet S (eds) Semantic web rules, vol 6403. Springer Berlin Heidelberg, Berlin, pp 74–88CrossRefGoogle Scholar
  10. 10.
    Blackwell AF (2004) End-user developers at home. Communications of the ACM 47(9):65–66. doi:10.1145/1015864.1015892 CrossRefGoogle Scholar
  11. 11.
    Borsci S, Federici S, Lauriola M (2009) On the dimensionality of the System Usability Scale: a test of alternative measurement models. Cognitive Processing 10(3):193–197. doi:10.1007/s10339-009-0268-9 CrossRefGoogle Scholar
  12. 12.
    Cabitza F, Dal Seno B, Sarini M, Simone C (2005) “Being at one with things”: the interconnection metaphor for intelligent environments. Proceedings of IEE International Workshop on Intelligent Environments (IEE'05), Colchester, UK, 63–73. doi: 10.1049/ic:20050218
  13. 13.
    Cabitza F, Fogli D, Lanzilotti R, Piccinno A (2015) End-user development in ambient intelligence: a user study. Proceedings of 11th Biannual Conference on Italian SIGCHI Chapter (CHItaly), Rome, Italy, October 29–30, 146–153. doi: 10.1145/2808435.2808446
  14. 14.
    Cabitza F, Fogli D, Piccinno A (2014) “Each to his own”: distinguishing activities, roles and artifacts in EUD practices. In: Caporarello L, Di Martino B, Martinez M (eds) Smart organizations and smart artifacts, vol 7. Springer International Publishing, Switzerland, pp 193–205. doi:10.1007/978-3-319-07040-7_19 Google Scholar
  15. 15.
    Cabitza F, Fogli D, Piccinno A (2014) Fostering participation and co-evolution in sentient multimedia systems. Journal of Visual Languages and Computing 25(6):684–694. doi:10.1016/j.jvlc.2014.10.014 CrossRefGoogle Scholar
  16. 16.
    Cabitza F, Gesso I (2014) Reporting a user study on a visual editor to compose rules in active documents. In: Blashki K, Isaias P (eds) Emerging research and trends in interactivity and the human-computer interface. IGI Global, Hershey, pp 182–203. doi:10.4018/978-1-4666-4623-0.ch009 CrossRefGoogle Scholar
  17. 17.
    Castelfranchi C, Piunti M, Ricci A, Tummolini L (2012) AmI systems as agent-based mirror worlds: bridging humans and agents through stigmergy. In: Bosse T (Ed.) Agents and ambient intelligence (Vol. 12, pp 17–31). IOS Press. doi: 10.3233/978-1-61499-050-5-17
  18. 18.
    Cook DJ, Augusto JC, Jakkula VR (2009) Ambient intelligence: technologies, applications, and opportunities. Pervasive and Mobile Computing 5(4):277–298. doi:10.1016/j.pmcj.2009.04.001 CrossRefGoogle Scholar
  19. 19.
    Cook DJ, Youngblood M, Das SK (2006) A multi-agent approach to controlling a smart environment. In: Augusto JC, Nugent CD (eds) Designing smart homes, vol 4008. Springer, Berlin Heidelberg, pp 165–182. doi:10.1007/11788485_10 CrossRefGoogle Scholar
  20. 20.
    Coutaz J, Demeure A, Caffiau S, Crowley JL (2014) Early lessons from the development of SPOK, an end-user development environment for smart homes. Proceedings of 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication (UbiComp), Seattle, Washington, 895–902. doi: 10.1145/2638728.2641559
  21. 21.
    Crowley J, Coutaz J (2015). An ecological view of smart home technologies. In: De Ruyter B, Kameas A, Chatzimisios P, Mavrommati I (Eds) Ambient intelligence (Vol. 9425, pp 1–16). Springer International Publishing. doi: 10.1007/978-3-319-26005-1_1
  22. 22.
    Cvijikj IP, Michahelles F (2011) The toolkit approach for end-user participation in the internet of things. In: Uckelmann D, Harrison M, Michahelles F (eds) Architecting the internet of things. Springer Berlin Heidelberg, Berlin Heidelberg, pp 65–96. doi:10.1007/978-3-642-19157-2_4 CrossRefGoogle Scholar
  23. 23.
    Dahl Y, Svendsen R-M (2011) End-user composition interfaces for smart environments: a preliminary study of usability factors. In: Marcus A (ed) Design, user experience, and usability. theory, methods, tools and practice, vol 6770. Springer, Berlin Heidelberg, pp 118–127. doi:10.1007/978-3-642-21708-1_14 CrossRefGoogle Scholar
  24. 24.
    Danado J, Paternò F (2014) Puzzle: a mobile application development environment using a jigsaw metaphor. Journal of Visual Languages and Computing 25(4):297–315. doi:10.1016/j.jvlc.2014.03.005 CrossRefGoogle Scholar
  25. 25.
    Davidoff S, Lee MK, Yiu C, Zimmerman J, Dey AK (2006) Principles of smart home control. In: Dourish P, Friday A (eds) UbiComp 2006: ubiquitous computing, vol 4206. Springer, Berlin Heidelberg, pp 19–34. doi:10.1007/11853565_2 CrossRefGoogle Scholar
  26. 26.
    Davidoff S, Lee MK, Zimmerman J, Dey AK (2006) Socially-aware requirements for a smart home. Proceedings of International Symposium on Intelligent Environments, 41–44. doi: Scholar
  27. 27.
    Demeure A, Caffiau S, Elias E, Roux C (2015) Building and using home automation systems: a field study. In: Díaz P, Pipek V, Ardito C, Jensen C, Aedo I, Boden A (Eds) End-user development (Vol. 9083, pp 125–140). Springer International Publishing. doi: 10.1007/978-3-319-18425-8_9
  28. 28.
    Demeure A, Caffiau S, Coutaz J (2014) Activity based end-user-development for smart homes: relevance and challenges, ambient intelligence and smart environments, Vol. 18. In: Augusto JC, Zhang T (Eds) (pp 141–152). Retrieved from doi:10.3233/978-1-61499-411-4-141
  29. 29.
    Dey AK, Sohn T, Streng S, Kodama J (2006) ICAP: interactive prototyping of context-aware applications. In: Fishkin KP, Schiele B, Nixon P, Quigley A (eds) Pervasive computing, vol 3968. Springer, Berlin Heidelberg, pp 254–271. doi:10.1007/11748625_16 CrossRefGoogle Scholar
  30. 30.
    Emani S, Yamin CK, Peters E, Karson AS, Lipsitz SR, Wald JS, Williams DH, Bates DW (2012) Patient perceptions of a personal health record: a test of the diffusion of innovation model. J Med Internet Res 14(6). doi: 10.2196/jmir.2278
  31. 31.
    Foddy WH (1993) Constructing questions for interviews and questionnaires: theory and practice in social research. Cambridge University Press, Cambridge. doi:10.1017/CBO9780511518201 CrossRefGoogle Scholar
  32. 32.
    Fogli D, Piccinno A (2013) Co-evolution of end-user developers and systems in multi-tiered proxy design problems. In: Dittrich Y, Burnett M, Mørch A, Redmiles D (eds) End-user development, vol 7897. Springer, Berlin Heidelberg, pp 153–168. doi:10.1007/978-3-642-38706-7_12 CrossRefGoogle Scholar
  33. 33.
    García-Herranz M, Haya PA, Esquivel A, Montoro G, Alamán X (2008) Easing the smart home: semi-automatic adaptation in perceptive environments. Journal of Universal Computer Science 14(9):1529–1544. doi:10.3217/jucs-014-09-1529 Google Scholar
  34. 34.
    García-Herranz M, Haya P, Alamán X (2010) Towards a ubiquitous end-user programming system for smart spaces. Journal of Universal Computer Science 16(12):1633–1649. doi:10.3217/jucs-016-12-1633 Google Scholar
  35. 35.
    Graziano AM, Raulin ML (2012) Research methods: a process of inquiry (8th Edition). PearsonGoogle Scholar
  36. 36.
    Humble J, Crabtree A, Hemmings T, Åkesson K-P, Koleva B, Rodden T, Hansson P (2003) “Playing with the bits” user-configuration of ubiquitous domestic environments. In: Dey AK, Schmidt A, McCarthy JF (eds) UbiComp 2003: ubiquitous computing, vol 2864. Springer, Berlin Heidelberg, pp 256–263. doi:10.1007/978-3-540-39653-6_20 CrossRefGoogle Scholar
  37. 37.
    Kalofonos DN, Wisner P (2007) A framework for end-user programming of smart homes using mobile devices. Proceedings of 4th IEEE Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, USA, Jan. 2007, 716–721. doi: 10.1109/CCNC.2007.146
  38. 38.
    Kemp JAM, Gelderen v T (1996) Co-discovery exploration: an informal method for iterative design of consumer products. In: Jordan PW, Thomas B, Weerdmeester BA, McClelland IL (eds) Usability evaluation in industry. Taylor and Francis, London, pp 139–146Google Scholar
  39. 39.
    Klos A (2012) Central tendency bias and self-reported risk attitudes. SSRN Electronic Journal. doi:10.2139/ssrn.2050899 Google Scholar
  40. 40.
    Kubitza T, Schmidt A (2015) Towards a toolkit for the rapid creation of smart environments. In: Díaz P, Pipek V, Ardito C, Jensen C, Aedo I, Boden A (Eds) End-user development (Vol. 9083, pp 230–235). Springer International Publishing. doi: 10.1007/978-3-319-18425-8_21
  41. 41.
    Lewis JR, Sauro J (2009) The factor structure of the system usability scale. In: Kurosu M (ed) Human centered design, vol 5619. Springer, Berlin Heidelberg, pp 94–103. doi:10.1007/978-3-642-02806-9_12 CrossRefGoogle Scholar
  42. 42.
    Lieberman H, Paternò F, Wulf V (eds) (2006) End user development, vol 9. Springer, Dordrecht. doi:10.1007/1-4020-5386-X_9 Google Scholar
  43. 43.
    Litvinova E, Vuorimaa P (2012) Engaging end users in real smart space programming. Proceedings of ACM Conference on Ubiquitous Computing (UbiComp), Pittsburgh, Pennsylvania, 1090–1095. doi: 10.1145/2370216.2370447
  44. 44.
    Lucci G, Paternò F (2014) Understanding end-user development of context-dependent applications in smartphones. In: Sauer S, Bogdan C, Forbrig P, Bernhaupt R, Winckler M (Eds) Human-centered software engineering (Vol. 8742, pp 182–198). Springer Berlin Heidelberg. doi: 10.1007/978-3-662-44811-3_11
  45. 45.
    Mavrommati I, Darzentas J (2007) End user tools for ambient intelligence environments: an overview. In: Jacko JA (ed) Human-computer interaction. Interaction platforms and techniques, vol 4551. Springer, Berlin Heidelberg, pp 864–872. doi:10.1007/978-3-540-73107-8_95 CrossRefGoogle Scholar
  46. 46.
    Mavrommati I, Kameas A, Markopoulos P (2004) An editing tool that manages device associations in an in-home environment. Personal and Ubiquitous Computing 8(3–4):255–263. doi:10.1007/s00779-004-0286-7 Google Scholar
  47. 47.
    Mehandjiev N, Ning L, Namoun A (2015) Assisted composition of services on mobile devices. In: Díaz P, Pipek V, Ardito C, Jensen C, Aedo I, Boden A (Eds) End-user development (Vol. 9083, pp 242–248). Springer International Publishing. doi: 10.1007/978-3-319-18425-8_23
  48. 48.
    Riva G, Vatalaro F, Davide F, Alcañiz M (eds) (2005) Ambient intelligence: the evolution of technology, communication and cognition towards the future of human-computer interaction, vol 6. Ios Press, AmsterdamGoogle Scholar
  49. 49.
    Rosson MB, Carroll JM (2002) Usability engineering: scenario-based development of human-computer interaction. Morgan Kaufmann Publishers Inc., San FranciscoGoogle Scholar
  50. 50.
    Sadri F (2007) Ambient intelligence for care of the elderly in their homes. Proceedings of 2nd workshop on artificial techniques for ambient intelligence (AITAmI ‘07), Hyderabad, India, 62–67Google Scholar
  51. 51.
    Sadri F (2011) Ambient intelligence: a survey. ACM Computing Surveys 43(4):1–66. doi:10.1145/1978802.1978815 CrossRefGoogle Scholar
  52. 52.
    Sadri F, Stathis K (2009) Ambient intelligence. In: Rabuñal Dopico JR, Dorado J, Pazos A (eds) Encyclopedia of artificial intelligence. IGI Global, Hershey, pp 85–91. doi:10.4018/978-1-59904-849-9.ch013 CrossRefGoogle Scholar
  53. 53.
    Schmidt A (2015) Programming ubiquitous computing environments. In: Díaz P, Pipek V, Ardito C, Jensen C, Aedo I, Boden A (Eds) End-user development (Vol. 9083, pp 3–6). Springer International Publishing. doi: 10.1007/978-3-319-18425-8_1
  54. 54.
    Shafti LS, Haya PA, García-Herranz M, Pérez E (2013) Inferring ECA-based rules for ambient intelligence using evolutionary feature extraction. Journal of Ambient Intelligence and Smart Environments 5(6):563–587. doi:10.3233/AIS-130232 Google Scholar
  55. 55.
    Ur B, McManus E, Pak Yong Ho M, Littman ML (2014) Practical trigger-action programming in the smart home. Proceedings of SIGCHI Conference on Human Factors in Computing Systems, Toronto, Ontario, Canada, 803–812. doi: 10.1145/2556288.2557420
  56. 56.
    Zhang T, Brugge B (2004) Empowering the user to build smart home applications. Proceedings of 2nd International conference on smart homes and health telematics; Toward a human-friendly assistive environment: ICOST ‘2004. doi: Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Federico Cabitza
    • 1
  • Daniela Fogli
    • 2
  • Rosa Lanzilotti
    • 3
  • Antonio Piccinno
    • 3
  1. 1.Dipartimento di Informatica, Sistemistica e ComunicazioneUniversità degli Studi di Milano-BicoccaMilanoItaly
  2. 2.Dipartimento di Ingegneria dell’InformazioneUniversità degli Studi di BresciaBresciaItaly
  3. 3.Dipartimento di InformaticaUniversità degli Studi di Bari “Aldo Moro”BariItaly

Personalised recommendations