Special issue on “Personalization and situation awareness in smart environments”
J Ambient Intell Human Comput
Special issue on ''Personalization and situation awareness in smart environments''
Ana M. Bernardos 0 1 2
Boon-Chong Seet 0 1 2
Elisabetta Farella 0 1 2
0 E. Farella Universita` di Bologna-Fondazione Bruno Kessler , Bologna, Trento , Italy
1 B.-C. Seet Auckland University of Technology , Auckland , New Zealand
2 A. M. Bernardos (&) Universidad Polite cnica de Madrid , Madrid , Spain
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Smart environments are technology augmented physical
ecosystems, which have been pervasively and
non-invasively instrumented to become perceptive and responsive.
These enriched capabilities are possible thanks to the
existence of infrastructures that enable the acquisition and
fusion of data coming from a wide variety of both virtual
sources and ubiquitous sensing devices (wireless sensor
networks, personal devices, smart objects, etc.). On top of
this data, user-centric paradigms aim at learning about the
ecosystems activity, in order to adapt and personalize the
offering of features and applications that may better fit the
needs and preferences of its dwellers. In a complementary
way, environment-centric paradigms exploit information in
pursuit of a holistic understanding of the smart spaces
status and its evolution, through situation analysis
techniques, to enhance decision making of global management
services.
With this context in mind, the present Special Issue
brings together recent advances on tools, activity
recognition, applications and service design for Personalization
and Situation Awareness in Smart Environments. The
Special Issue contains both extended versions of selected
papers presented at the International Workshop on Smart
Environments and Ambient Intelligence 2013 (SEnAmI
2013) and submissions accepted from open call. After a
three-round review process, in which three referees
reviewed each submitted paper, eight papers were finally
selected for publication.
The first paper, System-Level Approach to the Design
of Ambient Intelligence Systems based on Wireless Sensor
and Actuator Networks by U.D. Atmojo et al., lies within
the architectural solutions to deal with smart environments
information. The authors propose a system-level
programming language to develop a middleware-free Ambient
Intelligence system, in order to overcome the problems of
designing distributed systems on top of Wireless Sensor
and Actor Networks (WSANs).
The three following papers explore different aspects of
activity/behavior recognition in smart
environments.Bioinspired relevant interaction modeling in Cognitive crowd
management by S. Chiappino et al., describes an
Intelligent Video Surveillance (IVS) system based on a
bioinspired model of human reasoning and consciousness that
applies Cognitive Systems to anomaly detection and
management. Thereafter, CRAFFT: An activity prediction
model based on Bayesian networks by E. Nazerfard and
D.J. Cook, details and validates an activity prediction model
that relies on Bayesian networks together with a two-step
inference process to predict and label the activities and to
anticipate the start time of the next one. The paper entitled
Using implicit user feedback to balance energy
consumption and user comfort of computer screens by P.
Jaramillo et al., presents a dynamically adaptive proximity
controller to balance energy consumption and user comfort
of computer screens in office environments.
Two application-oriented papers are next included.
Building a smart campus to support ubiquitous learning
by Y. Atif et al., describes a social community platform for
university campuses that involves learners, experts and
physical resources. The proposed model of smart campus,
conceived as a composition of ambient learning spaces and
capable of dynamically modeling the learners profiles,
aims at offering a persuasive and ubiquitous approach to
learning. Following, the research work entitled
Situational awareness in smart environments: socio-mobile and
sensor data fusion for emergency response to disasters by
G.L. Foresti et al., explores the potentiality of analyzing
mobile social and smart sensors data to increase the
efficiency of the whole situational awareness emergency
services, localize the critical areas and obtain relevant
information for response and completion of search and
rescue operations.
The Special Issue concludes with two papers related to
service design and user experience.Evaluating
contextaware user interface migration in multi-device
environments by G. Ghiani et al., describes a solution for
migrating user interfaces and maintaining the interaction
sessions across devices when changing situations. The
solution is validated through a longitudinal diary study and
a controlled user study that serves to gain insights into the
user needs and technical requirements for context-aware
information sharing. The final paper is Situation-aware
safety service for children via participatory design by S.
Pantsar-Syvaniemi et al. The research work reports the
lesso (...truncated)