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In case you wish to refer to AWARE in your publications, please use the following:

If you wish to refer iOS version of AWARE, please use the following(s):

  • Nishiyama, Y., Ferreira, D., Eigen, Y., Sasaki, W., Okoshi, T., Nakazawa, J., Dey, A.K., Sezaki, K. iOS crowd–sensing won’t hurt a bit!: AWARE Framework and Sustainable Study Guideline for iOS Platform. In International Conference on Human-Computer Interaction (HCII 2020), pp. 223-243. Springer, Cham, 2020, DOI:10.1007/978-3-030-50344-4_17
  • Nishiyama, Y., Ferreira, D., Sasaki, W., Okoshi, T., Nakazawa, J., Dey, A.K., Sezaki, K. Using iOS for inconspicuous data collection: a real-world assessment. In Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp’20), pp. 261–266, 2020, DOI:10.1145/3410530.3414369

Publications 1

Publications 2

  • Moshe et al. Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data, Frontiers Psychiatry, 2021 (https://www.frontiersin.org/articles/10.3389/fpsyt.2021.625247/full)
  • Vega, J. Monitoring Parkinson’s Disease Progression Using Behavioural Inferences, Mobile Devices and Web Technologies. WWW’16 Companion, April 11–15, 2016, Montréal, Québec, Canada. DOI:10.1145/2872518.2888598
  • Hosio, S., Ferreira, D., Goncalves, J., van Berkel, N., Luo, C., Ahmed, M., Flores, H., Kostakos, V. Monetary Assessment of Battery Life on Smartphones. CHI’16, San Jose, US, 2016.
  • van Berkel, N., Luo, C., Anagnostopoulos, T., Ferreira, D., Goncalves, J., Hosio, S., Kostakos, V. A Systematic Assessment of Smartphone Usage Gaps. CHI’16, San Jose, US, 2016.
  • Jones, SL., Ferreira, D., Hosio, S., Goncalves, J., Kostakos, V. Revisitation Analysis of Smartphone App Use. UbiComp’15, Osaka, Japan, 2015.
  • Church, K., Ferreira, D., Banovic, N., Lyons, K. Understanding the Challenges of Mobile Phone Usage Data. MobileHCI’15, Copenhagen, Denmark, 2015, 504-514.
  • Ferreira, D., Kostakos, V., Beresford, A.R, Lindqvist, J., Dey, A.K. Securacy: An Empirical Investigation of Android Applications’ Network Usage, Privacy and Security. WiSec’15, New York, US, 2015.
  • Ferreira, D., Kostakos, V., Dey, A.K. AWARE: mobile context instrumentation framework. Frontiers in ICT (Vol 2, Issue 6), 2015, DOI: 10.3389/fict.2015.00006
  • Jörg Schlötterer, Christin Seifert, Wolfgang Lutz, and Michael Granitzer “From Context-Aware to Context-Based: Mobile Just-In-Time Retrieval of Cultural Heritage Objects”. ECIR, Vienna 2015.
  • Bobek, S., Nalepa, G.J., Ligȩza, A., Adrian, W.T. and Kaczor, K. Mobile context-based framework for threat monitoring in urban environment with social threat monitor. Multimedia Tools and Applications, (2014), 1-22.
  • Ferreira, D., Goncalves, J., Kostakos, V., Barkhuus, L., Dey, A.K.: Contextual Experience Sampling of Mobile Application Micro-Usage. MobileHCI’14: 91-100.
  • Banovic, N., Brant, C., Mankoff, J. and Dey, A. ProactiveTasks: The Short of Mobile Device Use Sessions. MobileHCI’14: 243-252.
  • Vandenbroucke, K., Ferreira, D., Goncalves, J., Kostakos, V., De Moor, K.: Mobile Cloud Storage: A Contextual Experience. MobileHCI’14: 101-110.
  • Ferreira, D., Ferreira, E., Goncalves, J., Kostakos, V. & Dey, A.K. (2013). Revisiting Human-Battery Interaction With An Interactive Battery Interface. UbiComp’13: 563-572.
  • Ickin, S., Wac, K., Fiedler, M., Janowski, L., et al. Factors influencing quality of experience of commonly used mobile applications. Communications Magazine, IEEE 50, 4 (2012), 48-56.
  • Ferreira, D, Miluzzo, E, Hakkila, J, Lovett, T & Kostakos, V (2012). UbiMI: ubiquitous mobile instrumentation. UbiComp’12: 715–716.
  • Shin, C., Hong, J.-H. and Dey, A.K. Understanding and Prediction of Mobile Application Usage for Smart Phones. UbiComp’12: 173-182.
  • Dey, AK, Wac, K, Ferreira, D, Tassini, K, Hong, J-H & Ramos, J (2011). Getting closer. Proceedings of the 13th international conference on Ubiquitous computing – UbiComp ’11: 163–172.
  • Ferreira, D, Dey, A & Kostakos, V (2011). Understanding Human-Smartphone Concerns: A Study of Battery Life. Pervasive Computing: 19–33.
  • Venkatanathan, J, Ferreira, D, Benisch, M, Lin, J, Karapanos, E, Kostakos, V, Sadeh, N, et al. (2011). Improving users’ consistency when recalling location sharing preferences. INTERACT’11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction:Vol. 1: 380–387.
  • Ferreira, D & Kostakos, V (2010). Design, Prototyping and Evaluation of Ambient Media: Lessons Learned from the Ambient Notifier. MobileHCI’10, Lisbon.

Thesis

  • Yuuki Nishiyama (2017) Enhancing Team-Level Behavior Change Using Information Sharing. Graduate School of Media and Governance, Keio University, Japan. Doctoral thesis.
  • Wolfgang Lutz (2014) Using physical context for mobile just in time information retrieval. University of Passau, Germany. Master’s thesis.
  • Korhonen M., Koski H., Visuri A. (2014) AWARE-WS: A Multipurpose Science Dashboard. Department of Computer Science and Engineering, University of Oulu, Oulu, Finland. Bachelor’s thesis.
  • Staniec Artur (2014) AWARE testing software functionality extension. Department of Telecommunications, University of Science and Technology in Krakow, Poland. Bachelor’s thesis.
  • Ferreira, D. (2013) AWARE: A Mobile Context Instrumentation Middleware To Collaboratively Understand Human Behavior. Doctoral thesis, University of Oulu, Faculty of Technology.

Tools

  • KnowMe: Uncertain and incomplete knowledge modelling for mediation in mobile context-aware systems.
  • Context Simulator: a Java program that allows for simulating events from the AWARE framework database. In case you want to make some tests on a real data, but you do not want to make real-life experiments this may be useful. You may increase, or decrease the simulation speed, write your own events and handlers, and so on.
  • Context Viewer: a simple visualiser of data that is gathered by the AWARE framework. It allows to visualise Location, application foreground, user activity and others. In the future we plan to add more tools for processing and analysing data (maybe binding it with WEKA machine learning tool) as well as some more visualisation of data.
  • HeaRTDroid: a rule-based inference engine dedicated for android devices.
  • Contextopheles: deliver information about Europe’s cultural heritage to the user, by gathering and integrating context information from the users device. The integrated context is automatically transformed in a search query for the Europeana search API. The user is notified about the results and can access the retrieved documents. This project has been developed within the EU-FP7 project EEXCESS.

Projects

MyPath: Breast Cancer application built using AWARE.
CARE: A Context-Aware Sensor System for Elderly Care
STOP: Sentient Tracking Of Parkinson’s