期刊信息
Sensors (Sensors)
http://www.mdpi.com/journal/sensors
影响因子:
3.031
出版商:
MDPI
ISSN:
1424-8220
浏览:
16913
关注:
26
征稿
Journal Open for Submission
https://susy.mdpi.com/user/manuscripts/upload/d63bcb6dc1e06bf5bde439da70e2815e?pre_hash_key=d29661cd8958cc923333f6a84ea31dc5

Special Issue Proposal - Open for Application
https://www.mdpi.com/journalproposal/sendproposalspecialissue/sensors

Sensors 2021 Young Investigator Award
Amount: 2000 CHF
Nomination deadline: 30 June 2021
https://www.mdpi.com/journal/sensors/awards/submit/1338

Sensors 2021 Ph.D. Thesis Award
Amount: 1000 CHF
Application deadline: 31 August 2021
https://www.mdpi.com/journal/sensors/awards/submit/1249

Detailed description of all awards:
https://www.mdpi.com/journal/sensors/awards

Sensors (ISSN 1424-8220) provides an advanced forum for the science and technology of sensor and its applications. It publishes reviews (including comprehensive reviews on the complete sensors products), regular research papers and short notes. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. The full experimental details must be provided so that the results can be reproduced. There are, in addition, three unique features of this journal:
    
Manuscripts regarding research proposals and research ideas are particularly welcome.
Electronic files and software providing full details of calculation and experimental procedures can be deposited as supplementary material.  
We also accept manuscripts regarding research projects financed with public funds in order that reach a broader audience.

Scope
    Physical sensors
    Chemical sensors
    Biosensors
    Lab-on-a-chip
    Remote sensors
    Sensor networks
    Smart/Intelligent sensors
    Sensor devices
    Sensor technology and application
    Sensing principles
    Optoelectronic and photonic sensors
    Optomechanical sensors
    Sensor arrays and Chemometrics
    Micro and nanosensors
    Internet of Things
    Signal processing, data fusion and deep learning in sensor systems
    Sensor interface
    Human-Computer Interaction
    Advanced materials for sensing
    Sensing systems
    MEMS/NEMS
    Localization and object tracking
    Sensing and imaging
    Image sensors
    Vision/camera based sensors
    Action recognition
    Machine/deep learning and artificial intelligence in sensing and imaging
    3D sensing
    Communications and signal processing
    Wearable sensors, devices and electronics
最后更新 Jayleen Chen 在 2021-03-18
Special Issues
Special Issue on Advances and Applications of Micro/Nano-Electronic Sensors
截稿日期: 2021-12-15

Special Issue "Advances and Applications of Micro/Nano-Electronic Sensors" Website: https://www.mdpi.com/journal/sensors/special_issues/MicroNanoElectronicSensors Deadline for manuscript submissions: 15 December 2021 Dear Colleagues, Wearable electronics have started to gain momentum because of their essential role in improving the quality of life for various patients and healthy individuals. The function and performance of integrated NEMS/MEMS systems depend on the design of nano-/microsystems, choice of materials, manufacturing approaches, packaging, and device integration methods. It is also of high interest to investigate the interrelationships between material properties and processing, device/system structure, and the mechanical, electrical, optical, or (bio)chemical behavior of devices/systems. Resonant sensors are a type of sensor that relies on the measurement of resonant frequency to detect a variety of physical parameters such as pressure, temperatures, viscosity, gas concentrations, accelerations, etc. This type of sensor has drawn a significant amount of attention due to its excellent stability, resolution, and accuracy. In addition, this type of sensor allows devices to be easily connected to digital systems, which is required for its effective employment as a measurement device. Keywords MEMS sensors piezoelectric sensors radio frequency sensors acoustic sensors microsystem design device/system structure fabrication techniques biomedical applications mechanical, electrical, optical, or (bio)chemical behavior of devices/systems Prof. Dr. Huanyu Cheng Prof. Dr. Haifeng Zhang Dr. Zhiqun (Daniel) Deng Guest Editors
最后更新 Callie Liu 在 2020-12-30
Special Issue on MEMS and NEMS Sensors
截稿日期: 2021-12-31

Special Issue "MEMS and NEMS Sensors" Website: https://www.mdpi.com/journal/sensors/special_issues/MEMS_NEME_sensors Deadline for manuscript submissions: 31 December 2021 Dear Colleagues, The manufacturing and integration of autonomous and embedded sensors through a combination of micro- and nano-system technologies have been revolutionizing self-powered, high bandwidth devices for advance manufacturing (AM), artificial intelligence (AI), Internet of Things (IoT), and health technologies. More specifically, nano- and micro-electro-mechanical-systems (N/MEMS) sensors are the building blocks for a vast range of applications, from continuous real-time health (wearable) and environmental monitoring (gas, biomolecules, pressure, temperature, etc.) to enabling embedded mobile Internet services (wireless), including smart/connected cars and unattended vehicles (UAV) (inertial). As these devices have numbered in the tens of billions, the potential for disruptive innovation has been immense. Integration of nano- and micro-sensors-which are functionalized using emerging materials to complementary metal-oxide-semiconductors (CMOS) and microfluidics systems, and their electro-mechanical packing are very challenging. Because, the integration and packing require the multiple deposition of layers of different dielectrics and metals, the atomic mismatch between these layers, acting as electron trap, increases ohmic resistance, and creates noise and reduces sensitivity, selectivity and responsivity; and increases detection time. This Special Issue aims to introduce the manufacturing, packaging and integration of autonomous and embedded sensors through a combination of micro- and nano-system. Topics in general include, but are not limited, to: - Autonomous and embedded sensors: design, manufacture, packaging and reliability - Biosensors (photonic, electrical, chemical) and their integration to MEMS, CMOS and microfluidic systems for COVID-19 and other (future) pandemics’ roteins/metabolites/analytes - Sensor interconnectors/interfaces and their testing - Graphene-based nano-sensors - Electronic circuits for MEMS nano-sensor modulation - Nano-electro-mechanical sensors Prof. Dr. Mustafa Yavuz Guest Editor Keywords N/MEMS-sensors sensor integration to N/MEMS CMOS and microfluidic systems electronic circuits for N/MEMS nano-sensor modulation bifurcation sensing sensor functionalization Nano-electro-mechanical sensors PeCOD COVID-19
最后更新 Callie Liu 在 2020-12-30
Special Issue on Assistive Robots for Healthcare and Human-Robot Interaction
截稿日期: 2021-12-31

Dear Colleagues, Assistive technologies like Assistive Robots (AR) are being considered as enablers to support the process of care giving, potentially enhancing patient well-being and decreasing caregiver workload. Currently, it needs to deepen the research about person-centered care, multimodal interaction, multimodal data collection, caregiver expectancy model to improve AR acceptability. In light of these assumptions, the Human-Robot Interaction (HRI) field is devoted to understanding, designing, and assessing the robotic systems used by human being. By definition, the interaction implicates the communication. In light of this assumption, research in the HRI field is increasingly focused on the development of robots equipped with intelligent communicative abilities, in particular speech-based natural-language conversational abilities. These efforts directly relate to the research area of computational linguistics, generally defined as “the subfield of computer science concerned with using computational techniques to learn, understand, and produce human language content”. The advances and results in computational linguistics provide a foundational background for the development of so-called Spoken Dialogue Systems, i.e., computer systems designed to interact with humans using spoken natural language. The ability to communicate using natural language is a fundamental requirement for a robot that interacts with human being. Then, spoken dialogue is generally considered as the most natural way for social human-robot interaction. The sensing technologies represent a key role in the HRI and new approaches or application of existing ones in novel way could be really significant in facilitating the improvement of this field and consequently in all the sub-fields related to it. The central focus of this Special Issues will be to advance novel technologies applied in healthcare processes that have shown exceptional promise in models of HRI though the use of new sensors or methodologies capable to adapt, combine or improve the existing ones. The first important question concerns the modalities needed to sense the emotional state of people by the robot. Secondly, there is the problem of modelling the interaction between human and robot, not only on a haptic level, but also on an emotional level. Dr. Grazia D'Onofrio Dr. Daniele Sancarlo Guest Editors
最后更新 James Su 在 2021-04-26
Special Issue on Advanced Quantum Diamond Sensors and Applications
截稿日期: 2021-12-31

Dear Colleagues, There is as growing body of knowledge demonstrating the quantum sensing capabilities of atomic scale defects within diamond. Over the past decade significant advances in the science and technology underpinning quantum diamond sensors have been realised opening up a broad range of measurement capabilities. To date methodologies for ultra-sensitive detection of magnetic fields, electric fields and temperature have been widely reported. Globally, significant research efforts and investment are being directed towards the further development of quantum diamond sensors and demonstration of their measurement capabilities. There is tremendous potential for deployment of quantum diamond sensors in electrical and thermal monitoring in electric vehicle batteries, high resolution magnetic resonance spectroscopy to uncover the chemical structures at a single molecule level, novel microwave sensors for use in the telecommunication sector, characterisation of future materials including spintronics devices and nanomaterials. Overall, quantum diamond sensors provide unprecedented measurement sensitivity and are poised to become essential tools across many sectors. This Special Issue on “Advanced Quantum Diamond Sensors and Applications” has the objective of showcasing current and emerging technologies that exploit the quantum assisted sensing capabilities of diamond. Reports describing new methodologies, materials, technical developments and applications are particularly welcome. https://www.mdpi.com/journal/sensors/special_issues/quantum_diamond_sensors Keywords biological imaging diamond quantum sensors optical microscopy healthcare technologies Prof. Dr. Melissa L. Mather Prof. Dr. Philippe B. Wilson Guest Editors
最后更新 James Su 在 2021-04-26
Special Issue on Camera Calibration and 3D Reconstruction
截稿日期: 2021-12-31

Dear Colleagues, The importance of accurate image-based assessment of 3D objects and scenes is rapidly growing in the fields of computer vision (cf. AR/VR, autonomous driving, aerial surveillance, etc.) and optical metrology (photogrammetry, fringe projection, deflectometry, etc.). As the performance of digital sensors and optics approaches physical limits, uncertainties associated with models of imaging geometry, calibration workflows and data types, pattern recognition algorithms etc. directly affect numerous applications. We are pleased to invite you to contribute manuscripts to this Special Issue. It addresses the metrological aspects of modeling, characterizing, and using digital cameras in the context of 3D measurements, as well as novel analytic (e.g., visualization) tools and techniques facilitating robust and reliable camera-based measurements. Both original research articles and reviews are welcome. https://www.mdpi.com/journal/sensors/special_issues/camera_calibration_3D_reconstruction Keywords camera calibration geometrical camera models image-based 3D reconstruction uncertainties in optical 3D measurements shape-from-X techniques high-precision camera-based measurements non-conventional imaging systems for 3D measurements computational imaging for 3D measurements We look forward to receiving your contributions. Please do not hesitate to contact us if you have any comments or questions. Dr. Alexey Pak Prof. Dr. Steffen Reichel Dr. Jan Burke Guest Editors
最后更新 James Su 在 2021-04-26
Special Issue on special issue on Cyber-Security-Based Internet of Things for Smart Homes
截稿日期: 2021-12-31

link: https://www.mdpi.com/journal/sensors/special_issues/Cyber-Security_IoT_Smart_Homes Special Issue Information The rapidly evolving technology of the Internet of Things introduces new cybersecurity challenges, especially where installations handle and process personal and private data. As such, smart homes constitute an ecosystem which is prone to new complex cyberattacks and attractive to attackers. This Special Issue aims to present recent advances in new techniques for the cyber defense of smart homes, by taking advantage of recent developments in machine, deep and federated learning, distributed ledger technologies such as blockchain, as well as behavioral monitoring of IoT devices. Topics of interest include but are not limited to the following: Cybersecurity architectures for IoT and smart homes; Cybersecurity analytics platforms for IoT; Blockchain for IoT and smart homes; Machine and deep learning for the security of IoT; Behavioral monitoring of IoT; Federated IoT smart home infrastructures with focus on security and privacy; Cyberthreat intelligence; AI-based methods for malware and ransomware; Privacy and trust in IoT. Keywords Smart homes Internet of Things Cyber security Privacy Intrusion detection systems Network behavior analysis Machine/deep/federated learning Distributed ledger technologies Dr. Konstantinos Votis (Information Technologies Institute, Centre for Research and Technology Hellas) Dr. Konstantinos M. Giannoutakis (Information Technologies Institute, Centre for Research and Technology Hellas) Dr. Nikolaos Dimitriou (Information Technologies Institute, Centre for Research and Technology Hellas) Guest Editors
最后更新 Vicky Cai 在 2020-12-31
Special Issue on special issue on Human Centered Artificial Intelligence: Putting the Human in the Loop for Implementing Sensors Based Intelligent Environments
截稿日期: 2021-12-31

SI LINK: https://www.mdpi.com/journal/sensors/special_issues/Artificial_Intelligence_Implementing_Sensors Special Issue Information: This Special Issue aims to solicit original and high quality research articles that consider the current evolvement of AI approaches under a human-centric approach in the development of intelligent environments. Exceptional contributions that extend previously published work will also be considered, provided that they contribute at least 60% new results. Authors of such submissions will be required to provide a clear indication of the new contributions and explain how this work extends the previously published contributions. Topics may include, but are not limited to, the following: Active machine learning Adaptive personal AI systems Causal learning, causal discovery, causal reasoning, causal explanations, and causal inference Cognitive computing Decision making and decision support systems Emotional intelligence Explainable, accountable, transparent, and fair AI Explanatory user interfaces and HCI for explainable AI Ethical and trustworthy AI Federated learning and cooperative intelligent information systems and tools Gradient-based interpretability Interaction modalities and devices: visual, 2D/3D, augmented reality, simulations, digital twin, conversational interfaces, and multimodal interfaces Interactive machine learning Interpretability in reinforcement learning Human–AI interactions and intelligent user interfaces Human–AI teaming Natural language generation for explanatory models Processes, tools, methods, user involvement, user research, evaluation, AI technology assessment and customization, and standards Rendering of reasoning processes Self-explanatory agents and decision support systems Usability of human–AI interfaces Dr. Constantine Stephanidis (1. Foundation for Research and Technology Hellas (FORTH), Institute of Computer Science (ICS), Human Computer Interaction Laboratory (HCI Lab); 2. Department of Computer Science, University of Crete) Dr. George Margetis (Foundation for Research and Technology Hellas (FORTH), Institute of Computer Science (ICS), Human Computer Interaction Laboratory (HCI Lab)) Guest Editors
最后更新 Vicky Cai 在 2021-01-08
Special Issue on Assistive Robots for Healthcare and Human-Robot Interaction
截稿日期: 2021-12-31

Dear Colleagues, Assistive technologies like Assistive Robots (AR) are being considered as enablers to support the process of care giving, potentially enhancing patient well-being and decreasing caregiver workload. Currently, it needs to deepen the research about person-centered care, multimodal interaction, multimodal data collection, caregiver expectancy model to improve AR acceptability. In light of these assumptions, the Human-Robot Interaction (HRI) field is devoted to understanding, designing, and assessing the robotic systems used by human being. By definition, the interaction implicates the communication. In light of this assumption, research in the HRI field is increasingly focused on the development of robots equipped with intelligent communicative abilities, in particular speech-based natural-language conversational abilities. These efforts directly relate to the research area of computational linguistics, generally defined as “the subfield of computer science concerned with using computational techniques to learn, understand, and produce human language content”. The advances and results in computational linguistics provide a foundational background for the development of so-called Spoken Dialogue Systems, i.e., computer systems designed to interact with humans using spoken natural language. The ability to communicate using natural language is a fundamental requirement for a robot that interacts with human being. Then, spoken dialogue is generally considered as the most natural way for social human-robot interaction. The sensing technologies represent a key role in the HRI and new approaches or application of existing ones in novel way could be really significant in facilitating the improvement of this field and consequently in all the sub-fields related to it. The central focus of this Special Issues will be to advance novel technologies applied in healthcare processes that have shown exceptional promise in models of HRI though the use of new sensors or methodologies capable to adapt, combine or improve the existing ones. The first important question concerns the modalities needed to sense the emotional state of people by the robot. Secondly, there is the problem of modelling the interaction between human and robot, not only on a haptic level, but also on an emotional level. Keywords development of new sensing methodologies to facilitate the HRI improvement of existing technologies in HRI application of multimodal approaches in HRI role of emotional detection in the HRI ethical aspects of HRI value sensitive design in care robotics patient centeredness acceptability and usability assessment impact of robot embodiment and how this affected the interactions https://www.mdpi.com/journal/sensors/special_issues/assisstive_robots_healthcare Dr. Grazia D'Onofrio Dr. Daniele Sancarlo Guest Editors
最后更新 James Su 在 2021-06-15
Special Issue on Advanced Quantum Diamond Sensors and Applications
截稿日期: 2021-12-31

Dear Colleagues, There is as growing body of knowledge demonstrating the quantum sensing capabilities of atomic scale defects within diamond. Over the past decade significant advances in the science and technology underpinning quantum diamond sensors have been realised opening up a broad range of measurement capabilities. To date methodologies for ultra-sensitive detection of magnetic fields, electric fields and temperature have been widely reported. Globally, significant research efforts and investment are being directed towards the further development of quantum diamond sensors and demonstration of their measurement capabilities. There is tremendous potential for deployment of quantum diamond sensors in electrical and thermal monitoring in electric vehicle batteries, high resolution magnetic resonance spectroscopy to uncover the chemical structures at a single molecule level, novel microwave sensors for use in the telecommunication sector, characterisation of future materials including spintronics devices and nanomaterials. Overall, quantum diamond sensors provide unprecedented measurement sensitivity and are poised to become essential tools across many sectors. This Special Issue on “Advanced Quantum Diamond Sensors and Applications” has the objective of showcasing current and emerging technologies that exploit the quantum assisted sensing capabilities of diamond. Reports describing new methodologies, materials, technical developments and applications are particularly welcome. Keywords biological imaging diamond quantum sensors optical microscopy healthcare technologies Prof. Dr. Melissa L. Mather Prof. Dr. Philippe B. Wilson Guest Editors
最后更新 James Su 在 2021-06-15
Special Issue on Camera Calibration and 3D Reconstruction
截稿日期: 2021-12-31

Dear Colleagues, The importance of accurate image-based assessment of 3D objects and scenes is rapidly growing in the fields of computer vision (cf. AR/VR, autonomous driving, aerial surveillance, etc.) and optical metrology (photogrammetry, fringe projection, deflectometry, etc.). As the performance of digital sensors and optics approaches physical limits, uncertainties associated with models of imaging geometry, calibration workflows and data types, pattern recognition algorithms etc. directly affect numerous applications. We are pleased to invite you to contribute manuscripts to this Special Issue. It addresses the metrological aspects of modeling, characterizing, and using digital cameras in the context of 3D measurements, as well as novel analytic (e.g., visualization) tools and techniques facilitating robust and reliable camera-based measurements. Both original research articles and reviews are welcome. We look forward to receiving your contributions. Please do not hesitate to contact us if you have any comments or questions. Keywords camera calibration geometrical camera models image-based 3D reconstruction uncertainties in optical 3D measurements shape-from-X techniques high-precision camera-based measurements non-conventional imaging systems for 3D measurements computational imaging for 3D measurements https://www.mdpi.com/journal/sensors/special_issues/camera_calibration_3D_reconstruction Dr. Alexey Pak Prof. Dr. Steffen Reichel Dr. Jan Burke Guest Editors
最后更新 James Su 在 2021-06-15
Special Issue on Multistage Manufacturing Processes in the Industry 4.0 for Zero-Defect Products
截稿日期: 2022-01-01

https://www.mdpi.com/journal/sensors/special_issues/mul_manu Dear Colleagues, One of the most important challenges in modern industry is the implementation of manufacturing systems that are capable of producing “zero-defect” products. In most cases, manufacturing consists of a sequence of stages where manufacturing operations are sequentially conducted to manufacture a part or product. These multistage manufacturing processes (MMP) show complex error interactions among stages, which makes it difficult to control product quality, and tasks such as predictive maintenance, process control, quality assurance and fault diagnosis are challenging. Under the new paradigm of Industry 4.0, sensing networks based on IIoT and the implementation of digital twins based on engineering and data-based models is set to have a major impact on these processes. The implementation of this new paradigm is expected to lead to manufacturing systems with self-adjust and self-optimization capabilities, optimal decision making based on simulated-driven strategies, correction actions for error compensation, optimal predictive maintenance actions, and so on. In this Special Issue, we encourage scholars to share recent advances in the field of MMPs and Industry 4.0. Investigations related to in-process sensing and data analytics, IIoT, fault diagnosis, digital twins, predictive maintenance, quality assurance and quality control are welcome, especially those focused on strategies for “zero defect” manufacturing. Prof. Dr. Jose Vicente Abellan-Nebot Prof. Dr. Ignacio Peñarrocha-Alós Guest Editors
最后更新 Chloe Guo 在 2021-04-26
Special Issue on Sensors for Digital Construction
截稿日期: 2022-01-01

https://www.mdpi.com/journal/sensors/special_issues/Digi_Constru Dear Colleagues, Detailed insights into the ongoing processes of construction projects are a prerequisite for an efficient management of time, costs, and resources. However, providing relevant information requires the analysis of vast amounts of data. A consistent digitization throughout all phases of a project facilitates a proper aggregation of these data, as well as an automated evaluation. While digital building models already support decision making during project planning, other domains are only sparsely digitized. The use of sensors helps to advance digitization in construction through the automated collection of time-dependent data. It allows for a continuous localization of resources and materials as well as the monitoring of construction machines and their states. This enables a digital monitoring of construction projects through their entire life cycle and supports the management in optimizing workflows, scheduling maintenance, improving safety, and so on. This Special Issue focuses on the application of sensors in construction-related domains and the processing of the collected data. Relevant topics include but are not limited to: Digital twin Internet of Things Safety Productivity Maintenance Prof. Dr. Markus König Guest Editor
最后更新 Chloe Guo 在 2021-04-26
Special Issue on Machine Learning in Human Activity Recognition
截稿日期: 2022-01-31

https://www.mdpi.com/journal/sensors/special_issues/ML_HAR Dear Colleagues, Human Activity Recognition (HAR) using pervasive and body-worn sensors has become a major research field with numerous practical applications. At the heart of most HAR systems lies the automated analysis of sensor readings, for which machine learning techniques are typically applied. With the explosion of research in the core machine learning area, numerous methods have been developed that are also of value for the HAR community. However, HAR comes with its own challenges for machine learning methods, such as challenging data quality, including sensor noise, faulty sensor readings, or ambiguities; often only very small datasets come with ground truth annotation; computational challenges for performing activity recognition in real time and on severely resource constrained devices; open ended activity recognition; and continuous adaptation of recognition systems, to name but a few. This Special Issue aims to provide an overview of the state-of-the-art and latest developments in the field of machine learning for human activity recognition. Prof. Dr. Thomas Ploetz Dr. Yu Guan Prof. Dr. Daniel Roggen Guest Editors
最后更新 Chloe Guo 在 2021-04-26
Special Issue on Wearables and Modern Technology for Sports Medicine: The Digital Age of Athletes
截稿日期: 2022-02-01

https://www.mdpi.com/journal/sensors/special_issues/wearable_sports Dear Colleagues, Sports engineering has led to modern technology substantially increasing and advancing in the field of sport and exercise medicine over the past decade. The interest in sports engineering aligns with the increased provision for sports medicine within professional and amateur sport, with multidisciplinary teams of professionals now employed to keep athletes healthy and continuing to perform to a high standard: medics, physiotherapists, nutritionists, strength and conditioning experts, etc. Technological development is creating more objective and accurate assessment tools that can augment the clinical reasoning/judgement that sports medicine decisions typically rely on. Digital health approaches are being developed at a rapid pace, with increasingly smaller and more discrete sensors/devices/applications that are able to collect data on all aspects of athlete health and performance on and off the field of play (in or out of competition). This Special Issue will focus on the technology that has been applied within sporting contexts and relevant populations to support sports medicine, particularly the following topics: Wearable sensing and mobile technology; Concussion assessment and management; Diet and nutrition tracking or intervention; Physical activity or performance metrics; Cardiovascular screening; Lower limb injury and player biometrics; Pitch-side assessment and management; Injury or performance evaluation and management; Novel technology in amateur and elite sport. Dr. Sam Stuart Dr. Steven Marshall Dr. Alan Godfrey Guest Editors
最后更新 Chloe Guo 在 2021-04-26
Special Issue on Prototyping of Industrial IoT Solutions
截稿日期: 2022-02-15

https://www.mdpi.com/journal/sensors/special_issues/proto_IIoT Dear Colleagues, The Industrial Internet of Things (I-IoT) is widely considered a key enabling technology of the fourth industrial revolution (I-4.0). The bridging of industrial assets with cloud infrastructures will allow the generation of many digital twins. I-IoT will fuel a multitude of innovation processes aimed at optimizing industrial processes and methods. However, the introduction of industrial IoT technologies into factories is a complex and cumbersome activity. Researchers, technicians, and entrepreneurs interested in bringing IoT into shop floors need to deal with reliability, scalability, compatibility, and security issues that are more complex in industrial environments than in consumer and domestic scenarios. Evolution from IoT to Industrial IoT requires a dedicated design process where the prototyping phase becomes crucial. Companies need to reduce the investment required for testing I-4.0 and I-IoT solutions, thus increasing the Return of Investment (ROI) while minimizing the impact on production and organization. Moreover, Industry 4.0 pushes companies and factories toward lean production strategies where fast prototyping in R&D processes is mandatory. For this reason, there is a strong need for reliable and secure fast prototyping solutions for Industrial IoT that, while guaranteeing a fast and cost-effective implementation of proof of concept, also guarantee future scalability toward extended, secure, stable and professional industrial setups. Prof. Dr. Daniele Mazzei Prof. Dr. Dorota Stadnicka Dr. Joan Navarro Prof. Dr. Chrysostomos Stylios Prof. Dr. Giuseppe Lannaccone Guest Editors
最后更新 Chloe Guo 在 2021-04-26
Special Issue on Advanced Sensor Networks/Seismic Networks and Monitoring for Earthquakes and Phenomena Having a Seismic Signature 
截稿日期: 2022-03-12

Dear Colleagues, The study of earthquakes is of global interest, mainly because the comprehension of such phenomena is useful to safeguard human lives. To this aim, tools (such as seismic networks and arrays, but also data analysis procedures) by which detect and localize from small to large magnitudes earthquakes quickly and accurately are fundamental. Since the last few years, advances in technology have allowed seismologists to design seismic networks more and more sophisticated (with boreholes or ocean bottom sensors). At the same time, potentially interesting seismological information can be obtained by instruments developed for different purposes (e.g., optical fiber, geophones, rotational sensors). Besides earthquakes, there are many phenomena that we are able to record with seismic networks; they are both of natural origin (as volcanic eruptions, landslides, sinkholes, weather events, meteorite impacts), and anthropogenic (as underground fluid injections, quarry blasts, nuclear explosions, etc.). In this special issue we aim to collect scientific papers focused on advanced techniques of seismic monitoring or data analysis of natural and anthropogenic events. Also, contributions from studies carried out by ‘unconventional’ seismic networks are welcome. tectonic and induced earthquakes fiber DAS networks no earthquakes seismic signature events rotational sensors off-shore seismicity location improvements seismic information from unconventional sensors Dr. Mario Anselmi Dr. Aladino Govoni Dr. Cristina Totaro Dr. Maria Adelaide Romano Guest Editors
最后更新 James Su 在 2021-04-26
Special Issue on Advanced Sensor Networks/Seismic Networks and Monitoring for Earthquakes and Phenomena Having a Seismic Signature
截稿日期: 2022-03-12

Dear Colleagues, The study of earthquakes is of global interest, mainly because the comprehension of such phenomena is useful to safeguard human lives. To this aim, tools (such as seismic networks and arrays, but also data analysis procedures) by which detect and localize from small to large magnitudes earthquakes quickly and accurately are fundamental. Since the last few years, advances in technology have allowed seismologists to design seismic networks more and more sophisticated (with boreholes or ocean bottom sensors). At the same time, potentially interesting seismological information can be obtained by instruments developed for different purposes (e.g., optical fiber, geophones, rotational sensors). Besides earthquakes, there are many phenomena that we are able to record with seismic networks; they are both of natural origin (as volcanic eruptions, landslides, sinkholes, weather events, meteorite impacts), and anthropogenic (as underground fluid injections, quarry blasts, nuclear explosions, etc.). In this special issue we aim to collect scientific papers focused on advanced techniques of seismic monitoring or data analysis of natural and anthropogenic events. Also, contributions from studies carried out by ‘unconventional’ seismic networks are welcome. tectonic and induced earthquakes fiber DAS networks no earthquakes seismic signature events rotational sensors off-shore seismicity location improvements seismic information from unconventional sensors Keywords seismic networks seismic arrays seismic monitoring earthquakes induced seismicity natural and anthropogenic events fiber DAS geophones rotational sensors https://www.mdpi.com/journal/sensors/special_issues/Seismic_network_monitoring Dr. Mario Anselmi Dr. Aladino Govoni Dr. Cristina Totaro Dr. Maria Adelaide Romano Guest Editors
最后更新 James Su 在 2021-06-15
Special Issue on Data and Privacy Management in Sensor Networks
截稿日期: 2022-03-30

Dear Colleagues, Recent years have witnessed a widespread interest in innovative sensor networks capable of providing valuable data for various applications (e.g., home automation, energy management), the connected objects and environments impact numerous application domains. From smart homes and buildings to cities, vehicle networks, and electrical grids, they have become a novel trend that is revolutionizing how people interact with their surroundings, how they accomplish their daily tasks in the workplace, and how they handle their health security, and safety. Sensor networks markets are currently booming and are projected to continue their growth for the years to come. The rising interest in intelligent connected environments (e.g., smart buildings, cities, factories) and the evolution of sensors, data management/communication technologies have paved the way for exciting and valuable applications that help users in their everyday tasks (e.g., increasing comfort, reducing energy consumption). Indeed, the sensor network ecosystem have made it easy to collect and exchange a large amount of data, connect heterogeneous systems, create complex systems for new forms of collaboration and interoperability. Typically, the sensed data are transmitted to the edge nodes, or directly to the cloud/server where it will be stored, indexed, processed and analysed to offer a new class of advanced services, such as envirenement monitoring, objects tracking, event detection, advanced data analytics, etc. Despite the progress made, however, data and privacy management in sensor networks remains a core and challenging issues. In fact, due to the nature of sensor networks, there exist complexity in gathering, aggregation, indexing, storage, processing and analysing big data generated by resource-constrained sensor nodes per unit time. Furthermore, sensor networks also impose new challenges related to knowledge discovery and decision-making automation, security, privacy, and trust. This special issue will promote the state-of-the-art research covering all aspects of the data and privacy management in sensor networks. High quality contributions addressing related theoretical and practical aspects are expected. The topics of interest for this special issue include, but are not limited to : Modelling, simulation of sensor networks Architecture and Protocols for sensor networks Data gathering, storage and aggregation in sensor networks Data processing, indexing and discovery in sensor networks Data analytics solutions for sensor networks Knowledge discovery and decision-making automation in sensor networks Modelling, analysis, simulation, and verification of security, privacy, and trustworthiness for sensor networks Detection, evaluation, and prevention of threats and attacks in sensor networks Data security, privacy, and trustworthiness in sensor networks https://www.mdpi.com/journal/sensors/special_issues/data_privacy_management_sensor_network Dr. Richard Chbeir Dr. Taoufik Yeferny Guest Editors
最后更新 James Su 在 2021-04-26
Special Issue on Data and Privacy Management in Sensor Networks
截稿日期: 2022-03-30

Dear Colleagues, Recent years have witnessed a widespread interest in innovative sensor networks capable of providing valuable data for various applications (e.g., home automation, energy management), the connected objects and environments impact numerous application domains. From smart homes and buildings to cities, vehicle networks, and electrical grids, they have become a novel trend that is revolutionizing how people interact with their surroundings, how they accomplish their daily tasks in the workplace, and how they handle their health security, and safety. Sensor networks markets are currently booming and are projected to continue their growth for the years to come. The rising interest in intelligent connected environments (e.g., smart buildings, cities, factories) and the evolution of sensors, data management/communication technologies have paved the way for exciting and valuable applications that help users in their everyday tasks (e.g., increasing comfort, reducing energy consumption). Indeed, the sensor network ecosystem have made it easy to collect and exchange a large amount of data, connect heterogeneous systems, create complex systems for new forms of collaboration and interoperability. Typically, the sensed data are transmitted to the edge nodes, or directly to the cloud/server where it will be stored, indexed, processed and analysed to offer a new class of advanced services, such as envirenement monitoring, objects tracking, event detection, advanced data analytics, etc. Despite the progress made, however, data and privacy management in sensor networks remains a core and challenging issues. In fact, due to the nature of sensor networks, there exist complexity in gathering, aggregation, indexing, storage, processing and analysing big data generated by resource-constrained sensor nodes per unit time. Furthermore, sensor networks also impose new challenges related to knowledge discovery and decision-making automation, security, privacy, and trust. This special issue will promote the state-of-the-art research covering all aspects of the data and privacy management in sensor networks. High quality contributions addressing related theoretical and practical aspects are expected. The topics of interest for this special issue include, but are not limited to : Modelling, simulation of sensor networks Architecture and Protocols for sensor networks Data gathering, storage and aggregation in sensor networks Data processing, indexing and discovery in sensor networks Data analytics solutions for sensor networks Knowledge discovery and decision-making automation in sensor networks Modelling, analysis, simulation, and verification of security, privacy, and trustworthiness for sensor networks Detection, evaluation, and prevention of threats and attacks in sensor networks Data security, privacy, and trustworthiness in sensor networks Dr. Richard Chbeir Dr. Taoufik Yeferny Guest Editors
最后更新 James Su 在 2021-06-15
Special Issue on Lifetime Extension Framework for Wireless Sensor Networks
截稿日期: 2022-03-30

Dear Colleagues, Over the past decades, wireless sensor networks (WSNs) have experienced exceptional growth, their success reflecting their continuously increasing areas of application (e.g., area monitoring, environmental sensing, threat detection, etc.). Besides, the integration of WSNs in the IoT allows the latter to penetrate deeply into our daily lives and provide various convenient services enabling users to access, use, and process information collected from sensors through smart devices. On the one hand, WSN devices' small size and low cost allow for development in large-scale environments. On the other hand, in the absence of infrastructure (due to their wireless nature), their operation depends on their limited batteries' energy supply. As a result of the limitations deriving from the low-capacity batteries, the lifetime of a WSN is inextricably linked to them. Thus, the framework underlying the devices' energy usage plays a vital role in the network's overall energy consumption and lifetime. For example, minimizing the number of packet transmissions among the WSN nodes or choosing a better location for the sink node can result in a lifetime extension. Apart from optimizing the energy consumption, another way to increase a WSN's lifetime is to find an optimal way to recharge its nodes' batteries. In these so-called Rechargeable Wireless Sensor Networks (RWSNs), a vehicle (e.g., an unmanned autonomous vehicle, a drone, etc.) able to recharge the nodes' batteries is implemented and moves among the nodes replenishing their batteries. To take advantage of this procedure and maximize the lifetime of the RWSN and the recharging vehicle itself, a framework (or policy) on which the recharging vehicle bases its operation must be considered. This framework has to take into account issues such as the minimization of the distance travelled by the recharging vehicle to recharge the nodes, the optimization of the number of visited (for a replenishment) nodes, the minimization of the energy consumption of the vehicle, among others. This Special Issue invites original research papers on new frameworks, algorithms, protocols, architectures, technologies, and solutions for extending the lifetime of a WSN (or RWSN). Relevant topics include, but are not limited to: - Lifetime extension - Energy consumption optimization - Energy-efficient routing - Load balancing - Optimal location of WSN nodes - Optimal location of sink node(s) - Machine learning-based WSN techniques - AI-enabled routing - Optimal data collection - Data reduction/compression - Wireless energy transfer techniques - Joint information and energy transfer - Energy harvesting - Recharging vehicles - Simulation tools - Physical layer challenges, issues, and solutions - Mobile edge/fog computing - Manuscript Submission Information - Placeholder to add info for submission process, charge, etc. Dr. Konstantinos Oikonomou Dr. Constantinos Angelis Dr. Georgios Tsoumanis Guest Editors
最后更新 James Su 在 2021-06-15
Special Issue on 2D Material for Sensors Application
截稿日期: 2022-03-31

Dear Colleagues, This Special Issue is devoted to the reports on 2D-based sensors. 2D materials is a fast-developing field of material science. Graphene and other 2D materials, such as transition metal dichalcogenides (TMDs), hexagonal boron nitride (h-BN), and transition metal oxides (TMOs), have attracted significant attention as supporting substrates in a wide variety of biosensing technologies. Due to recent success in the synthesis and engineering of 2D materials, new functionalities became possible by defect engineering, creating heterostructures with various nanomaterials as well as chemical and molecular doping. Although other nanomaterials like carbon nanotubes exhibit as well some degree of tunability, 2D materials due to their planar nature are more compatible with modern fabrication techniques and device integration. Thanks to the thin nature of 2D materials with a large area-to-volume ratio and various reaction sites they are very sensitive to the state of the surface. The 2D material family contains a variety of electronic properties, spanning from metallic/semimetallic (e.g. graphene) to semiconducting (e.g. MoS2, WS2) to insulating (e.g. h-BN). Importantly, through functionalization or defect engineering of 2D materials one can modify the surface chemistry and thus tailor them to selectively respond to certain analytes with extremely high sensitivity. Furthermore, 2D material-based sensors can be fabricated with miniaturised dimensions and feature flexibility, transparency and mechanical strength. All these unique properties make 2D materials excellent candidates for sensing applications. Dr. Dmitry K. Polyushkin Guest Editor
最后更新 James Su 在 2021-06-15
相关期刊
CCF全称影响因子出版商ISSN
Mobile Information Systems0.849Hindawi1574-017X
bACM Transactions on Sensor Networks ACM1550-4859
cSecurity and Communication Networks1.288Hindawi1939-0122
Journal of Semantics1.773Oxford University Press0167-5133
TripleCUnified Theory of Information Research Group1726-670X
IEEE Access4.098IEEE2169-3536
Journal of CheminformaticsChemistry Central1758-2946
Journal of Sensor and Actuator NetworksMDPI2224-2708
Scalable Computing Springer2194-6876
Computing and Visualization in Science Springer1432-9360
全称影响因子出版商
Mobile Information Systems0.849Hindawi
ACM Transactions on Sensor Networks ACM
Security and Communication Networks1.288Hindawi
Journal of Semantics1.773Oxford University Press
TripleCUnified Theory of Information Research Group
IEEE Access4.098IEEE
Journal of CheminformaticsChemistry Central
Journal of Sensor and Actuator NetworksMDPI
Scalable Computing Springer
Computing and Visualization in Science Springer
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