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Special Issue "System-Integrated Intelligence and Intelligent Systems"

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

Deadline for manuscript submissions: closed (31 January 2017)

Special Issue Editors

Guest Editor
Dr. Stefan Bosse

University of Bremen, Department of Mathematics and Computer Science, 28359 Bremen, Germany
Website1 | Website2 | E-Mail
Interests: distributed computing; sensor networks; sensorial materials; Internet-of-Things; cloud computing; agent-based computing; multi-agent systems; agent platforms; machine learning; self-organizing systems; embedded systems
Guest Editor
Prof. Ansgar Trächtler

Research group Control engineering and Mechatronics, Fachgruppe Regelungstechnik und Mechatronik, Heinz Nixdorf Institut, Universität Paderborn, Fürstenallee 11, 33102 Paderborn, Germany
Website | E-Mail
Interests: modeling and design of mechatronic systems; control of complex systems; suspension systems and vehicle dynamics control; hardware
Guest Editor
Prof. Dr. Klaus-Dieter Thoben

Director of Research Area Applied Information and Communication Technology for Production (IKAP) at Bremer Institut für Betriebstechnik Produktion und Logistik GmbH (BIBA), University of Bremen, Hochschulring 20, 28359 Bremen, Germany
Website | E-Mail
Interests: product service systems; intelligent products; cyber physical systems; virtual enterprise; concurrent engineering
Guest Editor
Prof. Dr. Berend Denkena

Institut für Fertigungstechnik und Werkzeugmaschinen, Produktionstechnisches Zentrum Hannover, Leibniz Universität Hannover, An der Universität 2, 30823 Garbsen, Germany
Website | E-Mail
Interests: geometry and functionalizing manufacturing processes; machine tools for cutting and grinding; production planning and control; simulation of manufacturing processes
Guest Editor
Dr. Dirk Lehmhus

ISIS Sensorial Materials Scientific Centre, University of Bremen, 28359 Bremen, Germany
Website | E-Mail
Interests: porous and cellular metals, metal foams, syntactic foams, metal matrix syntactic foams, metal matrix composites, powder metallurgy, powder technology, finite element analysis, integrated computational materials engineering (ICME), smart structures, sensor integration, sensorial materials, structural health monitoring (SHM)

Special Issue Information

Dear Colleagues,

The Special Issue, SI3S (Short Title: System-Integrated Intelligence and Intelligent Systems), will be linked to the 3nd International Conference on System-Integrated Intelligence (SysInt 2016, see www.sysint-conference.org). On the one hand, it will gather the top contributions presented at this event, and on the other hand, is an open call for outstanding submissions.
The conference itself provided a forum for academia and industry to present their latest research findings, innovations, and practices in the field of system-integrated intelligence. It focused on the integration of advanced functional capabilities into materials, systems, parts, and products as an enabling technology for established application scenarios, as well as new products and services. The perspectives are highly interdisciplinary. The technological basis extends from new sensor technologies via material-integrated sensing and intelligence to aspects of communication and data evaluation. It includes the implementation of such approaches in autonomous decision-making, self-optimization, and control in advanced engineering products and systems.

The conference further addressed wider fields of research, such as materials science and engineering, microsystems technology, mechatronic systems, and production engineering, as well as electronics and computer science. Specific application environments in the field of robotics, structural health monitoring, production, and logistics were highlighted in the program through the definition of dedicated symposia. Studies on implementation of system-integrated intelligence in additional scenarios beyond this scope are highly welcome.

Individual topics of interest include, but are not limited to:

-    Methods and Algorithms: Agent-based systems, Machine Learning and biologically-inspired methods for optimization, design, production, and planning
-    Self-Optimization and Autonomous Control: Design, reliability, modeling and validation
-    Sensorial Materials, material-integrated sensing and intelligence
-    Advanced Applications of Autonomous Objects and Systems
-    Human-Machine-Interaction: Visualization and transparency
-    Gentelligent Production
-    Cyber-Physical Systems in Production and Logistics
-    Perceptive Robotics
-    Structural Health Monitoring
-    Cloud Computing and Production

Dr. Stefan Bosse
Prof. Dr. Ansgar Trächtler
Prof. Dr. Klaus-Dieter Thoben
Prof. Dr. Berend Denkena
Dr. Dirk Lehmhus
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 papers will be 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 monthly 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 1800 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

•    Intelligent Systems: Enabling Technologies
•    The Future of Manufacturing: Cyber-Physical Production and Logistic Systems
•    Pervasive and Ubiquitous Computing
•    Structural Health Monitoring
•    Systems Engineering in Advanced Mechatronics

Published Papers (17 papers)

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Research

Open AccessArticle Natural Inspired Intelligent Visual Computing and Its Application to Viticulture
Sensors 2017, 17(6), 1186; doi:10.3390/s17061186
Received: 16 February 2017 / Revised: 28 April 2017 / Accepted: 2 May 2017 / Published: 23 May 2017
PDF Full-text (1763 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing
[...] Read more.
This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia. The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model. The arcs detected are then extended to perform the multiple arcs and ring detectors information processing for the berry detection application. The performance of the developed algorithms were compared with traditional image processing algorithms like the circular Hough transform (CHT) and other well-known circle detection methods. The proposed AIS approach gave a Fscore of 0.71 compared with Fscores of 0.28 and 0.30 for the CHT and a parameter-free circle detection technique (RPCD) respectively. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Development and Design of Next-Generation Head-Mounted Ambulatory Microdose Positron-Emission Tomography (AM-PET) System
Sensors 2017, 17(5), 1164; doi:10.3390/s17051164
Received: 1 February 2017 / Revised: 14 April 2017 / Accepted: 12 May 2017 / Published: 19 May 2017
PDF Full-text (4008 KB) | HTML Full-text | XML Full-text
Abstract
Several applications exist for a whole brain positron-emission tomography (PET) brain imager designed as a portable unit that can be worn on a patient’s head. Enabled by improvements in detector technology, a lightweight, high performance device would allow PET brain imaging in different
[...] Read more.
Several applications exist for a whole brain positron-emission tomography (PET) brain imager designed as a portable unit that can be worn on a patient’s head. Enabled by improvements in detector technology, a lightweight, high performance device would allow PET brain imaging in different environments and during behavioral tasks. Such a wearable system that allows the subjects to move their heads and walk—the Ambulatory Microdose PET (AM-PET)—is currently under development. This imager will be helpful for testing subjects performing selected activities such as gestures, virtual reality activities and walking. The need for this type of lightweight mobile device has led to the construction of a proof of concept portable head-worn unit that uses twelve silicon photomultiplier (SiPM) PET module sensors built into a small ring which fits around the head. This paper is focused on the engineering design of mechanical support aspects of the AM-PET project, both of the current device as well as of the coming next-generation devices. The goal of this work is to optimize design of the scanner and its mechanics to improve comfort for the subject by reducing the effect of weight, and to enable diversification of its applications amongst different research activities. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Low Power Multi-Hop Networking Analysis in Intelligent Environments
Sensors 2017, 17(5), 1153; doi:10.3390/s17051153
Received: 7 April 2017 / Revised: 6 May 2017 / Accepted: 15 May 2017 / Published: 19 May 2017
PDF Full-text (2784 KB) | HTML Full-text | XML Full-text
Abstract
Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More
[...] Read more.
Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle A Data-Driven Diagnostic Framework for Wind Turbine Structures: A Holistic Approach
Sensors 2017, 17(4), 720; doi:10.3390/s17040720
Received: 31 January 2017 / Revised: 11 March 2017 / Accepted: 21 March 2017 / Published: 30 March 2017
Cited by 4 | PDF Full-text (16304 KB) | HTML Full-text | XML Full-text
Abstract
The complex dynamics of operational wind turbine (WT) structures challenges the applicability of existing structural health monitoring (SHM) strategies for condition assessment. At the center of Europe’s renewable energy strategic planning, WT systems call for implementation of strategies that may describe the WT
[...] Read more.
The complex dynamics of operational wind turbine (WT) structures challenges the applicability of existing structural health monitoring (SHM) strategies for condition assessment. At the center of Europe’s renewable energy strategic planning, WT systems call for implementation of strategies that may describe the WT behavior in its complete operational spectrum. The framework proposed in this paper relies on the symbiotic treatment of acting environmental/operational variables and the monitored vibration response of the structure. The approach aims at accurate simulation of the temporal variability characterizing the WT dynamics, and subsequently at the tracking of the evolution of this variability in a longer-term horizon. The bi-component analysis tool is applied on long-term data, collected as part of continuous monitoring campaigns on two actual operating WT structures located in different sites in Germany. The obtained data-driven structural models verify the potential of the proposed strategy for development of an automated SHM diagnostic tool. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle An Approach to Automated Fusion System Design and Adaptation
Sensors 2017, 17(3), 601; doi:10.3390/s17030601
Received: 14 December 2016 / Revised: 9 February 2017 / Accepted: 9 March 2017 / Published: 16 March 2017
PDF Full-text (824 KB) | HTML Full-text | XML Full-text
Abstract
Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in
[...] Read more.
Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in all disciplines. Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems. This contribution thus proposes an approach, which relies on a network of self-descriptive intelligent sensor nodes, for the automatic design and update of sensor and information fusion systems. This article encompasses the fusion system configuration and adaptation as well as communication aspects. Manual interaction with the flexibly changing system is reduced to a minimum. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Autonomous Pointing Control of a Large Satellite Antenna Subject to Parametric Uncertainty
Sensors 2017, 17(3), 560; doi:10.3390/s17030560
Received: 3 January 2017 / Revised: 26 February 2017 / Accepted: 3 March 2017 / Published: 10 March 2017
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Abstract
With the development of satellite mobile communications, large antennas are now widely used. The precise pointing of the antenna’s optical axis is essential for many space missions. This paper addresses the challenging problem of high-precision autonomous pointing control of a large satellite antenna.
[...] Read more.
With the development of satellite mobile communications, large antennas are now widely used. The precise pointing of the antenna’s optical axis is essential for many space missions. This paper addresses the challenging problem of high-precision autonomous pointing control of a large satellite antenna. The pointing dynamics are firstly proposed. The proportional–derivative feedback and structural filter to perform pointing maneuvers and suppress antenna vibrations are then presented. An adaptive controller to estimate actual system frequencies in the presence of modal parameters uncertainty is proposed. In order to reduce periodic errors, the modified controllers, which include the proposed adaptive controller and an active disturbance rejection filter, are then developed. The system stability and robustness are analyzed and discussed in the frequency domain. Numerical results are finally provided, and the results have demonstrated that the proposed controllers have good autonomy and robustness. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation †
Sensors 2017, 17(3), 558; doi:10.3390/s17030558
Received: 30 January 2017 / Revised: 2 March 2017 / Accepted: 6 March 2017 / Published: 10 March 2017
Cited by 6 | PDF Full-text (4536 KB) | HTML Full-text | XML Full-text
Abstract
Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices.
[...] Read more.
Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle PDMAA Hydrogel Coated U-Bend Humidity Sensor Suited for Mass-Production
Sensors 2017, 17(3), 517; doi:10.3390/s17030517
Received: 14 November 2016 / Revised: 28 February 2017 / Accepted: 2 March 2017 / Published: 4 March 2017
Cited by 2 | PDF Full-text (1856 KB) | HTML Full-text | XML Full-text
Abstract
We present a full-polymer respiratory monitoring device suited for application in environments with strong magnetic fields (e.g., during an MRI measurement). The sensor is based on the well-known evanescent field method and consists of a 1 mm plastic optical fiber with a bent
[...] Read more.
We present a full-polymer respiratory monitoring device suited for application in environments with strong magnetic fields (e.g., during an MRI measurement). The sensor is based on the well-known evanescent field method and consists of a 1 mm plastic optical fiber with a bent region where the cladding is removed and the fiber is coated with poly-dimethylacrylamide (PDMAA). The combination of materials allows for a mass-production of the device by spray-coating and enables integration in disposable medical devices like oxygen masks, which we demonstrate here. We also present results of the application of an autocorrelation-based algorithm for respiratory frequency determination that is relevant for real applications of the device. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
Sensors 2017, 17(2), 427; doi:10.3390/s17020427
Received: 30 November 2016 / Revised: 9 February 2017 / Accepted: 19 February 2017 / Published: 22 February 2017
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Abstract
The foot-mounted inertial navigation system is an important method of pedestrian navigation as it, in principle, does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems.
[...] Read more.
The foot-mounted inertial navigation system is an important method of pedestrian navigation as it, in principle, does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial pedestrian navigation aided with both ZUPT (zero velocity update) and the range decomposition constraint performs better than those in their own respective methods. This paper recommends that the separation distance between the position estimates of the two foot-mounted inertial navigation systems be restricted by an ellipsoidal constraint that relates to the maximum step length and the leg height. The performance of the proposed method is studied by utilizing experimental data, and the results indicate that the method can effectively correct the dual navigation systems’ position over the traditional spherical constraint. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle A Sensor Data Fusion System Based on k-Nearest Neighbor Pattern Classification for Structural Health Monitoring Applications
Sensors 2017, 17(2), 417; doi:10.3390/s17020417
Received: 30 December 2016 / Revised: 9 February 2017 / Accepted: 17 February 2017 / Published: 21 February 2017
Cited by 4 | PDF Full-text (4784 KB) | HTML Full-text | XML Full-text
Abstract
Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure) is a requirement to reduce operational
[...] Read more.
Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure) is a requirement to reduce operational and maintenance costs. In this sense, the use of sensors permanently attached to the structures has demonstrated a great versatility and benefit since the inspection system can be automated. This automation is carried out with signal processing tasks with the aim of a pattern recognition analysis. This work presents the detailed description of a structural health monitoring (SHM) system based on the use of a piezoelectric (PZT) active system. The SHM system includes: (i) the use of a piezoelectric sensor network to excite the structure and collect the measured dynamic response, in several actuation phases; (ii) data organization; (iii) advanced signal processing techniques to define the feature vectors; and finally; (iv) the nearest neighbor algorithm as a machine learning approach to classify different kinds of damage. A description of the experimental setup, the experimental validation and a discussion of the results from two different structures are included and analyzed. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System
Sensors 2017, 17(2), 403; doi:10.3390/s17020403
Received: 18 December 2016 / Revised: 13 February 2017 / Accepted: 14 February 2017 / Published: 20 February 2017
Cited by 2 | PDF Full-text (7251 KB) | HTML Full-text | XML Full-text
Abstract
Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts
[...] Read more.
Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Middleware Design for Swarm-Driving Robots Accompanying Humans
Sensors 2017, 17(2), 392; doi:10.3390/s17020392
Received: 26 December 2016 / Revised: 13 February 2017 / Accepted: 14 February 2017 / Published: 17 February 2017
Cited by 1 | PDF Full-text (12551 KB) | HTML Full-text | XML Full-text
Abstract
Research on robots that accompany humans is being continuously studied. The Pet-Bot provides walking-assistance and object-carrying services without any specific controls through interaction between the robot and the human in real time. However, with Pet-Bot, there is a limit to the number of
[...] Read more.
Research on robots that accompany humans is being continuously studied. The Pet-Bot provides walking-assistance and object-carrying services without any specific controls through interaction between the robot and the human in real time. However, with Pet-Bot, there is a limit to the number of robots a user can use. If this limit is overcome, the Pet-Bot can provide services in more areas. Therefore, in this study, we propose a swarm-driving middleware design adopting the concept of a swarm, which provides effective parallel movement to allow multiple human-accompanying robots to accomplish a common purpose. The functions of middleware divide into three parts: a sequence manager for swarm process, a messaging manager, and a relative-location identification manager. This middleware processes the sequence of swarm-process of robots in the swarm through message exchanging using radio frequency (RF) communication of an IEEE 802.15.4 MAC protocol and manages an infrared (IR) communication module identifying relative location with IR signal strength. The swarm in this study is composed of the master interacting with the user and the slaves having no interaction with the user. This composition is intended to control the overall swarm in synchronization with the user activity, which is difficult to predict. We evaluate the accuracy of the relative-location estimation using IR communication, the response time of the slaves to a change in user activity, and the time to organize a network according to the number of slaves. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Structural Health Monitoring Using Textile Reinforcement Structures with Integrated Optical Fiber Sensors
Sensors 2017, 17(2), 345; doi:10.3390/s17020345
Received: 30 November 2016 / Accepted: 4 February 2017 / Published: 10 February 2017
Cited by 3 | PDF Full-text (5071 KB) | HTML Full-text | XML Full-text
Abstract
Optical fiber-based sensors “embedded” in functionalized carbon structures (FCSs) and textile net structures (TNSs) based on alkaline-resistant glass are introduced for the purpose of structural health monitoring (SHM) of concrete-based structures. The design aims to monitor common SHM parameters such as strain and
[...] Read more.
Optical fiber-based sensors “embedded” in functionalized carbon structures (FCSs) and textile net structures (TNSs) based on alkaline-resistant glass are introduced for the purpose of structural health monitoring (SHM) of concrete-based structures. The design aims to monitor common SHM parameters such as strain and cracks while at the same time acting as a structural strengthening mechanism. The sensor performances of the two systems are characterized in situ using Mach-Zehnder interferometric (MZI) and optical attenuation measurement techniques, respectively. For this purpose, different FCS samples were subjected to varying elongation using a tensile testing machine by carefully incrementing the applied force, and good correlation between the applied force and measured length change was observed. For crack detection, the functionalized TNSs were embedded into a concrete block which was then exposed to varying load using the three-point flexural test until destruction. Promising results were observed, identifying that the location of the crack can be determined using the conventional optical time domain reflectometry (OTDR) technique. The embedded sensors thus evaluated show the value of the dual achievement of the schemes proposed in obtaining strain/crack measurement while being utilized as strengthening agents as well. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †
Sensors 2017, 17(2), 311; doi:10.3390/s17020311
Received: 23 December 2016 / Revised: 30 January 2017 / Accepted: 1 February 2017 / Published: 8 February 2017
PDF Full-text (6178 KB) | HTML Full-text | XML Full-text
Abstract
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to
[...] Read more.
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle A Semantic Labeling of the Environment Based on What People Do
Sensors 2017, 17(2), 260; doi:10.3390/s17020260
Received: 27 October 2016 / Revised: 19 January 2017 / Accepted: 20 January 2017 / Published: 29 January 2017
PDF Full-text (26693 KB) | HTML Full-text | XML Full-text
Abstract
In this work, a system is developed for semantic labeling of locations based on what people do. This system is useful for semantic navigation of mobile robots. The system differentiates environments according to what people do in them. Background sound, number of people
[...] Read more.
In this work, a system is developed for semantic labeling of locations based on what people do. This system is useful for semantic navigation of mobile robots. The system differentiates environments according to what people do in them. Background sound, number of people in a room and amount of movement of those people are items to be considered when trying to tell if people are doing different actions. These data are sampled, and it is assumed that people behave differently and perform different actions. A support vector machine is trained with the obtained samples, and therefore, it allows one to identify the room. Finally, the results are discussed and support the hypothesis that the proposed system can help to semantically label a room. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Intelligent RF-Based Gesture Input Devices Implemented Using e-Textiles
Sensors 2017, 17(2), 219; doi:10.3390/s17020219
Received: 1 December 2016 / Revised: 17 January 2017 / Accepted: 17 January 2017 / Published: 24 January 2017
PDF Full-text (1666 KB) | HTML Full-text | XML Full-text
Abstract
We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures,
[...] Read more.
We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures, using a single measurement line. We demonstrate that the swatches can perform gesture detection when under thin layers of cloth or when weatherproofed, providing a high level of versatility not present with other types of approaches. Additionally, using small convolutional neural networks, low-level gestures can be identified with a high level of accuracy using a small, inexpensive microcontroller, allowing for an intelligent fabric that reports only gestures of interest, rather than a simple sensor requiring constant surveillance from an external computing device. The resulting e-textile smart composite has applications in controlling wearable devices by providing a simple, eyes-free mechanism to input simple gestures. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle A Multipurpose CMOS Platform for Nanosensing
Sensors 2016, 16(12), 2034; doi:10.3390/s16122034
Received: 23 September 2016 / Revised: 17 November 2016 / Accepted: 23 November 2016 / Published: 30 November 2016
PDF Full-text (12026 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper presents a customizable sensing system based on functionalized nanowires (NWs) assembled onto complementary metal oxide semiconductor (CMOS) technology. The Micro-for-Nano (M4N) chip integrates on top of the electronics an array of aluminum microelectrodes covered with gold by means of a customized
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This paper presents a customizable sensing system based on functionalized nanowires (NWs) assembled onto complementary metal oxide semiconductor (CMOS) technology. The Micro-for-Nano (M4N) chip integrates on top of the electronics an array of aluminum microelectrodes covered with gold by means of a customized electroless plating process. The NW assembly process is driven by an array of on-chip dielectrophoresis (DEP) generators, enabling a custom layout of different nanosensors on the same microelectrode array. The electrical properties of each assembled NW are singularly sensed through an in situ CMOS read-out circuit (ROC) that guarantees a low noise and reliable measurement. The M4N chip is directly connected to an external microcontroller for configuration and data processing. The processed data are then redirected to a workstation for real-time data visualization and storage during sensing experiments. As proof of concept, ZnO nanowires have been integrated onto the M4N chip to validate the approach that enables different kind of sensing experiments. The device has been then irradiated by an external UV source with adjustable power to measure the ZnO sensitivity to UV-light exposure. A maximum variation of about 80% of the ZnO-NW resistance has been detected by the M4N system when the assembled 5 μ m × 500 nm single ZnO-NW is exposed to an estimated incident radiant UV-light flux in the range of 1 nW–229 nW. The performed experiments prove the efficiency of the platform conceived for exploiting any kind of material that can change its capacitance and/or resistance due to an external stimulus. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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