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Smartphone Integrated Sensor and Application

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (13 November 2020) | Viewed by 2511

Special Issue Editor


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Guest Editor
Indiana University-Purdue University Indianapolis, Indianapolis, United States
Interests: cyber security and privacy, wireless sensing and mobile computing

Special Issue Information

Dear Colleagues,

The prevelance of smartphone have resulted in the emergence and growth of millions of applications (apps) leveraging diverse integrated sensors on smartphones, which  have penetrated every cornor of people’s life, including business, personal finance, healthcare, shopping, entertainment, security management, etc.  Smartphones featuring the rich set of integrated sensors are largely diffused all over the world and serve as ideal devices for the development of low-cost sensing systems and applications. In the design of a smartphone based sensing system, different elements must be taken in consideration. This Special Issue aims to highlight advances in the development, testing, modeling and securing the sensing capabilities on smartphone platforms. Topics include, but not limited to:

  • Biometric sensing with smartphone sensors
  • Environmental sensing for situational awareness
  • Smartphone-based crowdsensing
  • Smartphone sensors and Internet of Things (IoT) systems
  • Human Computer Interaction (HCI) on smartphones
  • Mobile applications leveraging integrated sensors on smartphones
  • Security issues related to smartphone sensors
  • Advanced Sensor Characterization Techniques
  • Sensor Error Modeling and Online Calibration

Prof. Dr. Hongbo Liu
Guest Editor

Manuscript Submission Information

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Keywords

  • smartphone
  • integrated sensors
  • applications
  • sensing capabilities
  • modeling

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Published Papers (1 paper)

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Research

27 pages, 2111 KiB  
Article
New Position Candidate Identification via Clustering toward an Extensible On-Body Smartphone Localization System
by Mitsuaki Saito and Kaori Fujinami
Sensors 2021, 21(4), 1276; https://doi.org/10.3390/s21041276 - 11 Feb 2021
Cited by 1 | Viewed by 2060
Abstract
On-body device position awareness plays an important role in providing smartphone-based services with high levels of usability and quality. Traditionally, the problem assumed that the positions that were supported by the system were fixed at the time of design. Thus, if a user [...] Read more.
On-body device position awareness plays an important role in providing smartphone-based services with high levels of usability and quality. Traditionally, the problem assumed that the positions that were supported by the system were fixed at the time of design. Thus, if a user stores his/her terminal into an unsupported position, the system forcibly classifies it into one of the supported positions. In contrast, we propose a framework to discover new positions that are not initially supported by the system, which adds them as recognition targets via labeling by a user and re-training on-the-fly. In this article, we focus on a component of identifying a set of samples that are derived from a single storing position, which we call new position candidate identification. Clustering is applied as a key component to prepare a reliable dataset for re-training and to reduce the user’s burden of labeling. Specifically, density-based spatial clustering of applications with noise (DBSCAN) is employed because it does not require the number of clusters in advance. We propose a method of finding an optimal value of a main parameter, Eps-neighborhood (eps), which affects the accuracy of the resultant clusters. Simulation-based experiments show that the proposed method performs as if the number of new positions were known in advance. Furthermore, we clarify the timing of performing the new position candidate identification process, in which we propose criteria for qualifying a cluster as the one comprising a new position. Full article
(This article belongs to the Special Issue Smartphone Integrated Sensor and Application)
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