ConaMSN: A context-aware messenger using dynamic Bayesian networks with wearable sensors

Bayesian networks for user modeling: Predicting the user's preferences

“…Korpipaa et al [16] have qualified the user context using the naive Bayes classifier . Hong et al [11] have proposed a context sensitive messenger that automatically deducts the context of the user . In other research work [13], Horvitz et al have proposed a system that infers user attention in an uncertain environment.…”

Ontology Modeling of Social Roles of Users in Mobile Computing Environments

“…AwarePhone provides context information about colleagues and workplaces while the AwareMedia acts as a whiteboard system for cooperation in workplaces. Similarly, in [23], the authors described a prototyped context-aware messenger called ConaMSN, which uses context information (emotion, stress, activity) obtained from wearable sensors (using probabilistic methods) and shares it among the application users. The lack of conceptual models and tools to support the rapid development of rich context-aware applications for empirical investigation of interaction design and the social implications of context-aware computing is a challenge.…”

Sociology Paradigms for Dynamic Integration of Devices into a Context-Aware System

“…The literature review suggests that there are numerous research works devoted to the ontology-based approach and context modelling (Attard et al, 2013;Wang et al, 2004;Fook et al, 2006;Christopoulou & Goumopoulos, 2004;Paganelli & Giuli, 2011), and software architecture solutions in developing context-aware application (Baltrunas et al, 2011;Bardram et al, 2004;Bardram & Hansen, 2010;Coppola et al, 2009;Hong et al, 2010;Löwe et al, 2012;Westhuizen & Coetzee, 2013;Yılmaz & Erdur, 2012). (Sriram et al, 2015) compared and discussed the frameworks that support crucial features in the healthcare system, while Gelogo et al (2015) proposed a context-aware framework for ubiquitous healthcare that can reduce the network traffic.…”

“…The CAB system was designed in a three-tier architecture, in which the topmost layer interacts with the user, the middle layer facilitates the communication between the topmost and the bottom layer, which is responsible for the collection and the analysis of the contextual information, and the search of the suitable contents given the inferred context. Hong et al (2010) designed and prototyped context-aware messenger (ConaMSN), which used information collected from wearable sensors and shared it among application users. Emotion, stress, and activity are types of sensed context information using probabilistic methods.…”