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Integration of Sensors in Complex, Intelligent Systems—Selected Papers from the CHARMS 2015 Workshop

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (31 October 2015) | Viewed by 30443

Special Issue Editors

Dr. Donghan Kim

E-Mail Website
Guest Editor
Department of Robotics, Hanyang University ERICA Campus, Ansan, Republic of Korea
Interests: robot navigation; human-robot interaction; service robot; multi-robot system
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Eric Matson

E-Mail Website
Guest Editor
Department of Computer and Information Technology, Purdue University, 401 North Grant Street, West Lafayette, IN 47907-2121, USA
Interests: multiagent systems and agent organizations; autonomous robotics and intelligent systems
Special Issues, Collections and Topics in MDPI journals
Dr. Byung-Cheol Min

E-Mail Website
Guest Editor
Department of Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USA
Interests: robotics; multi-robot systems; human-robot interaction; field robotics; assistive robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cyber physical systems (CPS) are becoming more involved in the lives of humans. All indications point to a future where many varieties of CPS and humans co-exist and, at a minimum, must interact consistently through life’s tasks with massive amounts of sensors and sensor data. Specifically, how to model, design, validate, implement, and experiment with these complex systems of interaction, communication, and networked relationships are to be explored in this Special Issue. This Special Issue will include ideas of the future relevant for understanding, discerning, and developing the relationship between humans and CPS and the practical nature of systems that facilitate the integration between humans, agents, robots, machines, and sensors (HARMS).

Papers showing human integration with sensors, machines, robots, and agents and practical experimental results are particularly encouraged, as are papers setting advances in the wider context of large, complex systems, including those involving multiple, heterogeneous actors.

Dr. Eric T. Matson
Dr. Byung-Cheol Min
Dr. Donghan Kim
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensors
  • robot
  • human-robot interaction
  • HARMS
  • cyber-physical systems

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Published Papers (5 papers)

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1999 KiB  
Article
Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling
by Sangmi Shin, Seongha Park, Yongho Kim and Eric T. Matson
Sensors 2016, 16(4), 575; https://doi.org/10.3390/s16040575 - 22 Apr 2016
Cited by 6 | Viewed by 5673
Abstract
Recently, commercial unmanned aerial systems (UAS) have gained popularity. However, these UAS are potential threats to people in terms of safety in public places, such as public parks or stadiums. To reduce such threats, we consider a design, modeling, and evaluation of a [...] Read more.
Recently, commercial unmanned aerial systems (UAS) have gained popularity. However, these UAS are potential threats to people in terms of safety in public places, such as public parks or stadiums. To reduce such threats, we consider a design, modeling, and evaluation of a cost-efficient sensor system that detects and tracks small UAS. In this research, we focus on discovering the best sensor deployments by simulating different types and numbers of sensors in a designated area, which provide reasonable detection rates at low costs. Also, the system should cover the crowded areas more thoroughly than vacant areas to reduce direct threats to people underneath. This research study utilized the Agent-Based Modeling (ABM) technique to model a system consisting of independent and heterogeneous agents that interact with each other. Our previous work presented the ability to apply ABM to analyze the sensor configurations with two types of radars in terms of cost-efficiency. The results from the ABM simulation provide a list of candidate configurations and deployments that can be referred to for applications in the real world environment. Full article
(This article belongs to the Special Issue Integration of Sensors in Complex, Intelligent Systems—Selected Papers from the CHARMS 2015 Workshop)
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3236 KiB  
Article
Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid
by Bat-erdene Byambasuren, Donghan Kim, Mandakh Oyun-Erdene, Chinguun Bold and Jargalbaatar Yura
Sensors 2016, 16(2), 250; https://doi.org/10.3390/s16020250 - 19 Feb 2016
Cited by 16 | Viewed by 8546
Abstract
Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity [...] Read more.
Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct power line tracking is a very prominent issue. In order to correctly track and make accurate measurements, the swing path of a power line should be previously fitted and predicted by a mathematical function using an inspection robot. After this, the remote inspection robot can follow the power line and measure the current. This paper presents a new power line tracking method using parabolic and circle fitting algorithms for illegal electricity detection. We demonstrate the effectiveness of the proposed tracking method by simulation and experimental results. Full article
(This article belongs to the Special Issue Integration of Sensors in Complex, Intelligent Systems—Selected Papers from the CHARMS 2015 Workshop)
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8124 KiB  
Article
A Mobile Robot Localization via Indoor Fixed Remote Surveillance Cameras
by Jae Hong Shim and Young Im Cho
Sensors 2016, 16(2), 195; https://doi.org/10.3390/s16020195 - 4 Feb 2016
Cited by 16 | Viewed by 6473
Abstract
Localization, which is a technique required by service robots to operate indoors, has been studied in various ways. Most localization techniques have the robot measure environmental information to obtain location information; however, this is a high-cost option because it uses extensive equipment and [...] Read more.
Localization, which is a technique required by service robots to operate indoors, has been studied in various ways. Most localization techniques have the robot measure environmental information to obtain location information; however, this is a high-cost option because it uses extensive equipment and complicates robot development. If an external device is used to determine a robot’s location and transmit this information to the robot, the cost of internal equipment required for location recognition can be reduced. This will simplify robot development. Thus, this study presents an effective method to control robots by obtaining their location information using a map constructed by visual information from surveillance cameras installed indoors. With only a single image of an object, it is difficult to gauge its size due to occlusion. Therefore, we propose a localization method using several neighboring surveillance cameras. A two-dimensional map containing robot and object position information is constructed using images of the cameras. The concept of this technique is based on modeling the four edges of the projected image of the field of coverage of the camera and an image processing algorithm of the finding object’s center for enhancing the location estimation of objects of interest. We experimentally demonstrate the effectiveness of the proposed method by analyzing the resulting movement of a robot in response to the location information obtained from the two-dimensional map. The accuracy of the multi-camera setup was measured in advance. Full article
(This article belongs to the Special Issue Integration of Sensors in Complex, Intelligent Systems—Selected Papers from the CHARMS 2015 Workshop)
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1815 KiB  
Article
A Context-Aware Mobile User Behavior-Based Neighbor Finding Approach for Preference Profile Construction
by Qian Gao, Deqian Fu and Xiangjun Dong
Sensors 2016, 16(2), 143; https://doi.org/10.3390/s16020143 - 23 Jan 2016
Cited by 3 | Viewed by 5174 | Correction
Abstract
In this paper, a new approach is adopted to update the user preference profile by seeking users with similar interests based on the context obtainable for a mobile network instead of from desktop networks. The trust degree between mobile users is calculated by [...] Read more.
In this paper, a new approach is adopted to update the user preference profile by seeking users with similar interests based on the context obtainable for a mobile network instead of from desktop networks. The trust degree between mobile users is calculated by analyzing their behavior based on the context, and then the approximate neighbors are chosen by combining the similarity of the mobile user preference and the trust degree. The approach first considers the communication behaviors between mobile users, the mobile network services they use as well as the corresponding context information. Then a similarity degree of the preference between users is calculated with the evaluation score of a certain mobile web service provided by a mobile user. Finally, based on the time attenuation function, the users with similar preference are found, through which we can dynamically update the target user’s preference profile. Experiments are then conducted to test the effect of the context on the credibility among mobile users, the effect of time decay factors and trust degree thresholds. Simulation shows that the proposed approach outperforms two other methods in terms of Recall Ratio, Precision Ratio and Mean Absolute Error, because neither of them consider the context mobile information. Full article
(This article belongs to the Special Issue Integration of Sensors in Complex, Intelligent Systems—Selected Papers from the CHARMS 2015 Workshop)
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155 KiB  
Correction
Correction: Gao, Q. et al. A Context-Aware Mobile User Behavior-Based Neighbor Finding Approach for Preference Profile Construction. Sensors 2016, 16, 143
by Qian Gao, Deqian Fu and Xiangjun Dong
Sensors 2016, 16(8), 1230; https://doi.org/10.3390/s16081230 - 4 Aug 2016
Cited by 1 | Viewed by 3688
Abstract
At first, may I offer my profoundest respects to the previous work obtained by the author Shi, whose work enlarged our view and set a good research direction for us and enlightened the initial idea of our paper.[...] Full article
(This article belongs to the Special Issue Integration of Sensors in Complex, Intelligent Systems—Selected Papers from the CHARMS 2015 Workshop)
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