Journal Information
Sensors (Sensors)
http://www.mdpi.com/journal/sensors
Impact Factor:
3.031
Publisher:
MDPI
ISSN:
1424-8220
Viewed:
18774
Tracked:
27
Call For Papers
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
Last updated by Jayleen Chen in 2021-03-18
Special Issues
Special Issue on Machine Learning in Human Activity Recognition
Submission Date: 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
Last updated by Chloe Guo in 2021-04-26
Special Issue on Wearables and Modern Technology for Sports Medicine: The Digital Age of Athletes
Submission Date: 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
Last updated by Chloe Guo in 2021-04-26
Special Issue on Prototyping of Industrial IoT Solutions
Submission Date: 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
Last updated by Chloe Guo in 2021-04-26
Special Issue on Advanced Sensor Networks/Seismic Networks and Monitoring for Earthquakes and Phenomena Having a Seismic Signature 
Submission Date: 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
Last updated by James Su in 2021-04-26
Special Issue on Advanced Sensor Networks/Seismic Networks and Monitoring for Earthquakes and Phenomena Having a Seismic Signature
Submission Date: 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
Last updated by James Su in 2021-06-15
Special Issue on Data and Privacy Management in Sensor Networks
Submission Date: 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
Last updated by James Su in 2021-04-26
Special Issue on Data and Privacy Management in Sensor Networks
Submission Date: 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
Last updated by James Su in 2021-06-15
Special Issue on Lifetime Extension Framework for Wireless Sensor Networks
Submission Date: 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
Last updated by James Su in 2021-06-15
Special Issue on 2D Material for Sensors Application
Submission Date: 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
Last updated by James Su in 2021-06-15
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