UbiPhone: Human-Centered Ubiquitous Phone System

Hwang, Ren-Junn; Tsai, Shang-Yi; Wang, Chiung-Ying

doi:10.1109/mprv.2009.37

Cited by 12 publications

(6 citation statements)

References 4 publications

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“…Interestingly, other more recent researches had come quite close to providing useful solution when there is the need for contact to be made to RFoCA. For instance, [13] proposed an emergency contact model that used social status, location information since they reside as calendar items on mobile phones. The model used these parameters to determine the most appropriate third party to call in an emergency situation.…”

Section: Related Workmentioning

confidence: 99%

An Architecture-Based Technique to Mobile Contact Recommendation for Emergency Situation in Nigeria

Akigbe¹,

Ikono²,

Ejidokun³

et al. 2016

Nig. J. Tech.

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Smart technologies such as smart phones, iPad and Tablets are ubiquitous in today’s society. They possess increasing computing and storage potentials. Thus, emerging as a dominant computing platform for different kinds of end-users. However, these technological possibilities have not been fully explored for emergency situations where close relatives must be contacted. This paper therefore presents an Emergency Contact Recommendation Model (ECRM) that was implemented into an emergency contact recommendation system. An architectural based approach was employed to highlight the contribution this paper made to extant knowledge. The leveraged of the Dust miner algorithmic technique, the direct discriminative pattern mining, and the Bayesian Inference Network technique were used to formulate the ECRM. The ECRM was implemented using the Java development and android tool kit. The model demonstrated commendable capabilities - considering the foregoing techniques when compared with what obtains in literature- to make useful recommendation in emergency situation(s) after implementation. http://dx.doi.org/10.4314/njt.v36i124

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Section: Related Workmentioning

confidence: 99%

An Architecture-Based Technique to Mobile Contact Recommendation for Emergency Situation in Nigeria

Akigbe¹,

Ikono²,

Ejidokun³

et al. 2016

Nig. J. Tech.

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“…This research focuses on the use of mobile devices for shopping. Service adaptation using Fuzzy theory in context aware mobile computing middleware (Cao et al , 2005). This research proposes a fuzzy‐based service adaptation model (FSAM) that can be used in context aware middleware. UbiPhone: human‐centered ubiquitous phone system (Hwang et al , 2009). UbiPhone automatically connects using the most appropriate phone system based on current context information, such as caller and contact's location, presence status, network status, available phone systems, calendars, and social relationships.In comparison with the previous works the major contribution of this paper can be summarized as follows:Reduction in application searching time in different context.…”

Section: Literature Surveymentioning

confidence: 99%

Design and implementation of user context aware recommendation engine for mobile using Bayesian network, fuzzy logic and rule base

Thyagaraju

Kulkarni

2012

International Journal of Pervasive Computing and Communications

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Context-aware computing refers to a general class of mobile systems that can sense their physical environment, and adapt their behavior accordingly. Such systems are a component of a ubiquitous computing. Context aware computing makes systems aware of situations of interest, enhances services to users, automates systems and reduces obtrusiveness and customizes and personalizes applications. Mobile phones and PDAs are converging into mobile lifestyle devices that offer a wide range of applications to end users. Many of these applications will have the ability to adapt themselves to the user's situation, commonly referred to as context awareness. Context-aware services have been introduced into mobile devices, such as cellular phones. Context aware service recommendation engine for mobile is designed to automatically adopt its behavior to changing environment. To achieve this, an important issue to be addressed is how to effectively select services for adaptation according to the user's current context. In this paper, we propose an intelligent service recommendation model. We formulate the service adaptation process by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rule based reasoning .Bayesian Network to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the rules for adopting the policies of implementing a service, fitness degree computation and service recommendation. In addition to this we have proposed maximum to minimum priority based context attributes matching algorithm for rule selection based on fitness degree of rules. The context aware mobile is tested for library and class room scenario to exemplify the proposed service recommendation engine and demonstrate its effectiveness

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“…They described the design requirements of contact book for mobile devices systematically and provided an application interface implemented. Hwang et al made a human-centered social network and presented a smart and comfortable contact service and an emergency contact service [7].…”

Section: B Mobile Social Networkmentioning

confidence: 99%

“…The reality mining project in MIT Media Lab conducted social network analyses using information of Bluetooth proximity [5], [6]. On the other hand, Hwang et al made a user-centered social network and presented the UbiPhone including UbiCall, a smart and comfortable contact service, and an emergency contact service using call records [7].…”

Section: Introductionmentioning

confidence: 99%

Building Mobile Social Network with Semantic Relation Using Bayesian NeTwork-based Life-log Mining

Park

Cho

2010

2010 IEEE Second International Conference on Social Computing

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Mobile devices such as cell phone, PDA and smart phone have been so popularized that they are to be a necessity for everyday life. These mobile devices can be very useful tools to collect users' life-logs because they have many sensors and users always carry them. Therefore, many studies using mobile life-logs are actually being conducted. Mobile life-logs include interaction information between users as well as personal information of each user. We collect these mobile life-logs, and additionally, high-level logs such as activity and emotion as helping users to annotate them. Based on these life-logs, we build a novel mobile social network by mining semantic relations between users in life-logs using Bayesian network. For experiments, we build the mobile social networks and analyze them. Finally, we discuss how this mobile social network can be used for practical application and implemented a proof-of-concept application.

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UbiPhone: Human-Centered Ubiquitous Phone System

Cited by 12 publications

References 4 publications

An Architecture-Based Technique to Mobile Contact Recommendation for Emergency Situation in Nigeria

An Architecture-Based Technique to Mobile Contact Recommendation for Emergency Situation in Nigeria

Design and implementation of user context aware recommendation engine for mobile using Bayesian network, fuzzy logic and rule base

Building Mobile Social Network with Semantic Relation Using Bayesian NeTwork-based Life-log Mining

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