Dr. Bin Guo

School of Computer Science
Northwestern Polytechnical University

Xi'an, Shaanxi, 710129, P. R. China

Email: guobin.keio(AT)gmail.com




Honors & Awards




Employment History

Useful Links


Research Interests

  • Ubiquitous Computing
  • Mobile Crowd Sensing
  • Urban Big Data
  • Articifical Intelligence
  • Social Media Mining
  • Smartphone Sensing

Ph.D Projects (2006-2009)

  • Smart artifacts have been used to support a range of human-centric services. However, there lacks a study on how to create smart artifact based entertainments in future homes. This research investigates the prospects and issues surrounding designing and playing smart-artifect based games in future homes, which includes a programming platform that allows users to program pervasive games by exploring physical (e.g., smart objects) and virtual (user generated contents, like photos, video clips, and music clips) resources in smart homes.


    Images of iFun   Pervasive Gaming At Home

  • Due to the reasons such as privacy, personality, and acceptability, end users should be allowed to control the context-aware applications in future homes, and even create new applications if they find that existing ones do not meet their needs. There have been several visual programming tools designed for end users, however, the variety and complexity of the enabled applications is quite low by using them, and the development process is still a burden to average home users. LogicEasy suggests a multi-level programming environment for users with different abilities, to address the powerful requirement from advanced users and the simplicity requirement from novices.

  • Home-Explorer includes several smart-object based applications. (1) Real-World-Search: This is a web-based indoor physical object search system. Different from the Google search targeted in the virtual world, Home-Explorer can help the human residents quickly localize his belongings (e.g., lost keys). (2) Smart-Reminder-Agent: People are prone to forget things. For example, one user may forget to take a wallet when he goes shopping. The smart reminder agent is designed to reduce such difficult situations by delivering suggestions or alerts to human residents according to various conditions.


    Real-World-Search,   Smart-Reminder-Agent

Semantic Sensor Network Infrastructure
  • Recent research results show that building and maintaining smart-artifact systems is still a complex and time-consuming task due to the lack of an adequate infrastructure support. To address this, we proposed a new system infrastructure called SS-ONT. Unlike previous studies, Sixth-Sense explores the Semantic Web technology to define a common ontology to assist the development of human-artifact interaction systems. SS-ONT reflects several aspects that have not been discussed in previous ontology-based studies, such as artifact property and status description (e.g., size, location, orientation), and artifact-artifact (e.g., spatial relation) and artifact-human relationships (e.g., object-related human behavior).

  • This research is mainly on how to obtain physical world information in smart sensor rich environment. The view is object-centered and we attached sensors to everyday artefacts to create smart artefacts, which are both self-awareness and ambient-awareness. Unlike other smart object studies, Sixth-Sense especially addresses the uncertainty in context-aware systems (owing to the sensor problems such as sensor is broken, running out of buttery, sensor blockage and limited coverage), i.e., the so-called hidden object problem. In Sixth-Sense, hidden objects are detected using a set of user-defined rules (written in the format of SWRL, a language that is intended to be the rule language of the Semantic Web). The rules are mainly abstracted from common sense knowledge and various physical relations among objects.


    Hidden-Object-1, Hidden-Object-2, Hidden-Object-3

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Last update: Mar. 31, 2009.