Distributed Current Source Method for Modeling of Magnetic and Eddy-Current Fields in Sensing System Design
This paper presents a distributed current source (DCS) method for modeling the eddy current (EC) fields induced in biological or non-ferrous metallic objects in two-dimensional axisymmetric and three-dimensional Cartesian coordinates. The EC fields induced in the objects, magnetic flux density (MFD) in space, and magnetic flux (MF) of the sensing coils are formulated in state-space representation. The harmonic responses of the eddy current fields and electromotive force (EMF) of the sensing coil are formulated in closed-form solutions. The proposed DCS method is applied to design two eddy current sensing systems. The Bio-Differential Eddy Current (BD-EC) sensor distinguishes biological objects, and the Metal-Coaxial Eddy Current (MC-EC) sensor classifies non-ferrous metallic objects. The simulated EC field and EMF are numerically verified by comparing results with finite element analysis. An example is utilized to illustrate the advantage of the DCS method for calculating the MFD, MF, and EMF contributed from the induced ECD in the objects directly, and the EMF generated from each material. The proposed method, along with a prototype of the BD-EC sensor, has been experimentally evaluated on sweep frequency analysis for detecting meat and bone.
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Optimal Sizing of CPP-GMR Read Sensors for Magnetic Recording Densities of 1–4 Tb/in²
Several studies have confirmed that current-perpendicular-to-the-plane giant magnetoresistance (CPP-GMR) technology is appropriate for next-generation read sensors for ultrahigh areal densities (ADs) of data storage applications. Since the physical dimension of the read sensor is a crucial factor for developing the reader to overcome its limitations, this paper proposes an optimal sizing prediction of the CPP-GMR read heads for ADs of 1-4 Tb/in 2 . Micromagnetic modelling was performed in the simulations. The appropriate length of the stripe height (SH) and the read width (RW) of the readers was estimated based on a consideration of sensor outputs including the readback signal, asymmetry parameter, dibit response and power spectral density (PSD) profile. It was found that a variation of SH and RW lengths had an influential impact on the readback signal waveform. Those affectations were further characterized through the echoes of dibit response showing that shortening the SH length or increasing the RW length could improve the resolution and reduce the distortion occurring in the readback signal. Moreover, the PSD profile indicated that the reader operation became more stable at shorter SH lengths or longer RW lengths. The head response spectrum was also examined. In addition, the magnitude of the bias current was studied in relation to the head response. Lastly, the optimal physical dimension (SH × RW) of the CPP-GMR readers for ADs of 1-4 Tb/in 2 was predicted to be ( 40×48 ) nm, ( 28×29 ) nm, ( 25×26 ) nm and ( 19×20 ) nm, respectively. The results can be utilized to design the CPP-GMR sensors at ultrahigh magnetic recording capacities.
*Published in the IEEE Magnetics Society Section within IEEE Access.
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Positioning and Navigation in Challenging Environments
Submission Deadline: 31 July 2022
IEEE Access invites manuscript submissions in the area of Positioning and Navigation in Challenging Environments.
In recent years, positioning and navigation has become a vital part of modern life especially with the continuous performance enhancement and modernization of the four global navigation satellite systems. Positioning and navigation industry has been growing quickly and has played a significant role in the industrial chain. Although great progress and many achievements have been made over the past few decades, there are a range of significant issues to be dealt with, especially in challenging environments.
In complex (e.g. large, multi-floor) indoor environments, it is a challenge to generate a valid positioning and navigation solution by a remote cloud platform with both offline and online data (e.g. WiFi and magnetic fingerprint data) recorded with smartphones The problem may become more complex if a pedestrian goes through different scenarios, such as from one floor to another floor of the same building, or from one building to another connected or neighboring building. There is a preference to avoid any interruption in the provision of valid position information. Thus, in the design of next-generation (beyond 5G) communication systems, the positioning functions need to be enabled and standardization of positioning technology such as in 3GPP should be taken into account.
As natural resources of the earth’s surface and shallow sea are becoming scarce, it is inevitable to acquire resources from deep underground, deep underwater and outer space. Regarding deep underground mining, there are currently a good number of deep mines in the world, including Mponeng Gold Mine and Tau Tona Mine, both located in South Africa with a depth of about 3.9km, and Kidd Creek Copper and Zinc Mine located in Ontario, Canada with a depth of about 2.9km. Deep underground mining is a challenging scenario which usually has high humidity and irregular space distribution, requiring stricter restrictions on the design and building of positioning and navigation systems.
Deep sea mining is promising because of abundant minerals on and under the deep seabed. For instance, a large amount of polymetallic nodules, containing rich concentrations of manganese, nickel, copper, and cobalt, are found in the Clarion-Clipperton Zone, a great abyssal plain as wide as the continental United States that lies 4 to 6 km below the surface of the eastern Pacific Ocean. Abundant naturel gas and oil also exist deep under the sea. Positioning and navigation is important for vehicles and robots to pick up the seabed surface minerals and to perform drilling and extraction of minerals under the seabed.
Space mining is currently a hot topic and should become a reality in the next few decades. , It is crucial to provide accurate and reliable positioning and navigation information for spacecraft and/or space robots which will approach and then usually land on the target planet (e.g. moon) or asteroid, followed by exploration, mining and so on; or simply catch and hold a rather small asteroid and move it back to Earth. For instance, a small Japanese space capsule carrying pristine pieces of the near-Earth asteroid Ryugu touched down on 5 December 2020, northwest of the South Australian capital of Adelaide. This was a successful initial step towards space mining on asteroids.
Positioning and navigation is vital for safe, reliable and effective operations in the scenarios of the frontier applications mentioned above. This Special Section aims to report the recent advances on positioning and navigation in such challenging scenarios. Researchers and engineers are also encouraged to perform more research and development to make advances in this area.
The topics of interest include, but are not limited to:
- Positioning and navigation in complex indoor environments
- Deep underground positioning and navigation
- Positioning and navigation for deep ocean operations and mining
- Positioning and navigation for space exploration and mining
- Cloud computing for positioning and navigation
- High sensitivity GNSS receivers
- Suppression of GNSS jamming and spoofing
- Positioning for communication systems beyond 5G
- Standardization of positioning technology
We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.
Associate Editor: Kegen Yu, China University of Mining and Technology, Mainland of China
Guest Editors:
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- Andrew Dempster, University of New South Wales, Australia
- Pau Closas, Northeastern University, USA
- Shih-Hau Fang, Yuan Ze University, Taiwan
- Guenther Retscher, Vienna University of Technology, Austria
- Ali Broumandan, Hexagon Autonomy and Positioning, Canada
Relevant IEEE Access Special Sections:
IEEE Access Editor-in-Chief: Prof. Derek Abbott, University of Adelaide
Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access
For inquiries regarding this Special Section, please contact: kegenyu@foxmail.com.
Prediction of Re-Occurrences of Spoofed ACK Packets Sent to Deflate a Target Wireless Sensor Network Node by DDOS
The Wireless Sensor Network (WSN) has evolved into a new IoT scheme, and its adoption has no restrictions at present. Sadly, security has an impact on the network of wireless sensors, and Denial-of-Service (DOS) categories of attacks are security concerns. This study therefore focuses on the distributed denial of service (DDOS), especially on DDoS-PSH-ACK (ACK & PUSH ACK Flood) in WSN. An experimental analysis was developed to predict that many spoofed ACK packets were reoccurring in order to deflate the target node. In the proposed approach, several experimental scenarios for the DDOS detection function were established and implemented. The experimental analysis draws traffic flow within the several transmission sessions involving “the normal transmission within sensor nodes and cluster head”, as well as the “transmission and retransmission scenarios within the sensor nodes and cluster head” at same time with different signal sizes. The main contribution of the paper is predicting DDoS attack by variability of transmission behavior with high degree accuracy. It was established that the most ideal delay between transmissions is 23 milliseconds in order to ensure that the receiving end is not overwhelmed. The result of the current study highlighted that when transmission session gets overwhelmed, that influence DDOS success.
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Sensing Methodologies in Agriculture for Soil Moisture and Nutrient Monitoring
Development and deployment of sensing technologies is one of the main steps in achieving sustainability in crop production through precision agriculture. Key sensing methodologies developed for monitoring soil moisture and nutrients with recent advances in the sensing devices reported in literature using those techniques are overviewed in this article. The soil moisture determination has been divided into four main sections describing soil moisture measurement metrics and laboratory-based testing, followed by in-situ, remote and proximal sensing techniques. The application, advantages and limitations for each of the mentioned technologies are discussed. The nutrient monitoring methods are reviewed beginning with laboratory-based methods, ion-selective membrane based sensors, bio-sensors, spectroscopy-based methods, and capillary electrophoresis-based systems for inorganic ion detection. Attention has been given to the core principle of detection while reporting recent sensors developed using the mentioned concepts. The latest works reported on the different sensing methodologies point towards the trend of developing low-cost, easy to use, field-deployable or portable sensing systems aimed towards improving technology adoption in crop production leading to efficient site-specific soil and crop management which in turn will bring us closer to reaching sustainability in the practice of agriculture.
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Highly Sensitive Reflective-Mode Phase-Variation Permittivity Sensor Based on a Coplanar Waveguide Terminated With an Open Complementary Split Ring Resonator (OCSRR)
This paper presents a one-port reflective-mode phase-variation microwave sensor consisting of a coplanar waveguide (CPW) transmission line terminated with a grounded open complementary split ring resonator (OCSRR). The sensor is useful for measuring the dielectric constant of the so-called material under test (MUT), which should be placed in contact with the OCSRR, the sensitive element. The output variable is the phase of the reflection coefficient. Design guidelines for the implementation of highly sensitive sensors are derived in the paper, and validated through simulation and experiment. As compared to other reflective-mode phase-variation sensors based on open-ended sensing lines, the designed and fabricated devices exhibit a very small sensitive region by virtue of the use of an electrically small resonant element, the OCSRR. The relevant figure of merit, defined as the ratio between the maximum sensitivity and the size of the sensing area (expressed in terms of the squared wavelength), is as high as FoM
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Towards Smart Cities with IoT Based on Crowdsensing
Submission Deadline: 31 December 2020
IEEE Access invites manuscript submissions in the area of Towards Smart Cities with IoT Based on Crowdsensing.
The proliferation of Internet of Things (IoT) has paved the way for the future of smart cities. The large volume data over IoT can enable decision-making for various applications, such as smart transportation, smart parking and smart lighting. The key to the success of smart cities is data collection and aggregation over IoT. Recently, crowdsensing has become a new data collection paradigm over IoT, which can realize large-scale and fine-grained data collection with low cost for various applications. For example, we can leverage the power of the crowd to build a real-time noise map with the microphones on smartphones. Despite the advantages of crowdsensing and IoT, there are many challenges to utilize crowdsensing over IoT for smart cities, such as how to allocate tasks to appropriate users to provide high-quality sensing data, how to incentivize users to participate in crowdsourcing, how to detect the reliability of the crowdsourced data, and how to protect the privacy of users. This Special Section aims to solicit original research works that address the challenging problems in utilizing crowdsensing over IoT for smart cities.
The topics of interest include, but are not limited to:
- Collaborative sensing and computing
- Sparse mobile crowdsensing over IoT
- Task allocation/selection in crowdsensing
- Fair/long-term/quality-oriented incentive in crowdsensing
- Data collection/aggregation in crowdsensing
- Truth discovery in crowdsensing
- Security, trust and privacy protection for IoT devices
- Privacy-preserving data collection for crowdsensing
- Fog computing and edge computing
- IoT device monitoring and scheduling in smart city
- Analysis for IoT-based Big Data
- Vehicular crowdsensing networks in smart city
- Resource management of IoT devices for smart city
- Quality measurement of crowdsourced data for smart city
- Crowdsourced data enabled applications in smart city
We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.
Associate Editor:
Kun Wang, University of California, Los Angeles, USA
Zhibo Wang, Wuhan University, China
Guest Editors:
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- Ye-Qiong Song, University of Lorraine, France
- Dejun Yang, Colorado School of Mines, USA
- Shibo He, Zhejiang University, China
- Wei Wang, Amazon Inc, USA
Relevant IEEE Access Special Sections:
- Urban Computing & Well-being in Smart Cities: Services, Applications, Policymaking Considerations
- Data Mining for Internet of Things
- Security, Privacy, and Trust Management in Smart Cities
IEEE Access Editor-in-Chief: Prof. Derek Abbott, University of Adelaide
Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access
For inquiries regarding this Special Section, please contact: zbwang@whu.edu.cn.
Emerging Approaches to Mobile Cooperative Sensing and Its Applications in Smart Environments
Submission Deadline: CLOSED
IEEE Access invites manuscript submissions in the area of Emerging Approaches to Mobile Cooperative Sensing and Its Applications in Smart Environments.
Mobile cooperative sensing is becoming a popular paradigm to collect information and outsource tasks to mobile users. Detected events are then reported continuously through the integration and cooperation of sensors, actuators, controllers, and artificial intelligence. Mobile cooperative sensing refers to estimating the event information and simulating the situation of smart environments through the analysis of data from sensor networks deployed in the environment. The systems are able to actively obtain information of occupancy, such as identification, activity, and even gestures with mobile cooperative sensing. For instance, intrusion detection and human identification help to detect intruders automatically. In smart environments, light and temperature can be adjusted according to the occupancy, which conserves the energy. For children and the elderly, activities such as falling can be monitored to prevent potential hazards. Mobile cooperative sensing is becoming a vital part of the fvarious emerging applications in smart environments, such as energy consumption estimation, security surveillance, and human behavior analysis. Generally speaking, mobile cooperative sensing provides an active detected input for smart systems, so it can make judgment or feedback accordingly.
At present, with the increasing mobile cooperative sensing technology in the field of Mobile Internet of Things (M-IoT) and the continuous improvement and upgrading of the current internet infrastructure, application and business model innovations are constantly emerging. Mobile cooperative sensing is further penetrating traditional fields, such as finance, transportation, medical treatment, education, etc… Mobile cooperative sensing technology can already be found in the fields of intelligent transportation, internet finance, and intelligent medical treatment, for example. In the future, some preliminary application results can be expected to be used in other fields, especially in the application areas of smart environments (e.g., smart homes and cities), which will have a far-reaching impact. Mobile cooperative sensing technology is not just about the detection via sensor networks; it is also about enabling a wide range of new capabilities, architectures, and service paradigms. The development of mobile cooperative sensing is set to have major economic, social, and environmental impacts, the intersection of which forms future sustainable growth.
As a result, the development of mobile cooperative sensing in smart environments is fundamentally important; however, many problems still remain.. For example, how to construct and improve the framework and platform for mobile cooperative sensing; how to collect, measure, process, analysis, and optimize mobile cooperative sensing data; and how to improve the effectiveness and decrease the energy in mobile cooperative sensing. These are all vital but unavoidable problems for mobile cooperative sensing in smart environments.
This Special Section is intended to provide a specific opportunity to argue the state-of-the-art technologies around mobile cooperative sensing in smart environments and invite researchers in the relevant fields to share the latest progress, novel methodologies, and potential research topics.
The topics of interest include, but are not limited to:
- Construction and improvement of framework and platform for mobile cooperative sensing
- Collection, measurement, processing, analysis, and optimization of mobile cooperative sensing data
- Improvement of effectiveness and decrease of energy in mobile cooperative sensing
- Evaluation of performance relevant to mobile cooperative sensing systems
- Adaptability of mobile cooperative sensing systems in complex and variable environments
- Emerging technologies in smart environments
- Artificial intelligence in smart environments
- Smart environment-based machine learning for mobile cooperative sensing
- Security and privacy of mobile cooperative sensing in smart environments
- Quality of Service (QoS) and Mobile Internet of Things (M-IoT) services in mobile cooperative sensing systems
We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.
Associate Editor: Mu Zhou, Chongqing University of Posts and Telecommunications, China
Guest Editors:
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- Hongying Meng, Brunel University London, UK
- Haiying Wang, Ulster University, UK
- Lei Chen, Georgia Southern University, USA
- Kunjie Xu, Intel Corporation, USA
Relevant IEEE Access Special Sections:
- Innovation and Application of Internet of Things and Emerging Technologies in Smart Sensing
- Intelligent Information Services
- Advances in Machine Learning and Cognitive Computing for Industry Applications
IEEE Access Editor-in-Chief: Prof. Derek Abbott, University of Adelaide
Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access
For inquiries regarding this Special Section, please contact: zhoumu@cqupt.edu.cn.
Reliability in Sensor-Cloud Systems and Applications (SCSA)
Submission Deadline: 28 February 2021
IEEE Access invites manuscript submissions in the area of Reliability in Sensor-Cloud Systems and Applications (SCSA).
The sensor-cloud system (SCS) integrates sensors, sensor networks, and cloud for managing sensors, collecting data, and decision-making. The integration provides flexible, low-cost, and reconfigurable platforms for monitoring and controlling the applications, including emerging applications of the Internet of things (IoT), machine to machine, and cyber-physical systems. Though the SCS has received tremendous attention from both academia and industry because of its numerous exciting applications, it suffers from issues with reliability.
The reliability of the SCS is the ability to perform required functions at or below a given failure rate for a given period of time. The required functions are identified as correctly providing measurement results. Sensor data can be faulty due to system faults or security attacks during the sensor data acquisition and collection, and data processing/decision-making on the cloud. There is also the possibility of not receiving the data at all or received data is compromised. Sensor data is also susceptible to errors and interference such as noise. Furthermore, to save sensor resources, end-users are becoming more dependent on cloud processing and decision-making. This enables significant interactions between sensors and between sensors and the cloud. As a result, the required functions can be extended to cover more concerns, including system design and integration, system continuity, real-time responsiveness, data security, and prevention of privacy intrusions, etc. This is why practitioners and engineers must also be able to measure imprecision and true reliability for both the data and the system that deals with the data. When designing and developing the SCS for real applications, the reliability verification at any level is required.
This Special Section aims to collect and publish state-of-art research results to solve the reliability concerns of sensor-cloud systems.
The topics of interest include, but are not limited to:
- Reliability theory, standardization, modeling, and architecture for SCSA
- Reliability in sensor design and integration in SCSA
- Reliability in communication and networking in SCSA
- Reliability in sensor data privacy processing, computing, and control in SCSA
- Reliability in applying machine learning models and methods for SCSA
- Reliability through data security, privacy, and trust for SCSA
- Reliability concerns in monitoring diverse applications of SCSA
- Reliability through QoS in application monitoring in SCSA
- Reliability issues (e.g., cloud storage, computing, decision-making) in SCSA
- Reliability in fog and edge computing in SCSA
- Reliability in mobile sensing, offloading and tracking in SCSA
- Reliability assessment, measures, and testbeds for SCSA
- Reliability levels and relations, metrics, and measures for SCSA
- Data quality assurance and quality control in SCSA
- Effective network design and development of SCSA
- Smartphone-based and heterogeneous design of SCSA
- Reliability through fault-tolerance and reliability in SCSA
We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.
Associate Editor: Md Zakirul Alam Bhuiyan, Fordham University, USA
Guest Editors:
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- Arafatur Rahman, University Malaysia Pahang, Malaysia
- Liu Qin, Hunan University, China
- Xuyun Zhang, Macquarie University, Australia
- Taufiq Asyhari, Coventry University, UK
Relevant IEEE Access Special Sections:
- Additive Manufacturing Security
- Advanced Sensor Technologies on Water Monitoring and Modeling
- The convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things
IEEE Access Editor-in-Chief: Prof. Derek Abbott, University of Adelaide
Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access
For inquiries regarding this Special Section, please contact: zakirulalam@gmail.com.
Emerging Trends of Energy and Spectrum Harvesting Technologies
Submission Deadline: 31 December 2020
IEEE Access invites manuscript submissions in the area of Emerging Trends of Energy and Spectrum Harvesting Technologies.
Billions of low-end wireless devices, such as sensors, are permeating into almost every aspect of personal life, such as in vehicles, washing machines, air conditioners, etc. These miniaturized and low-end devices are a promising solution to collect information and assist users for interaction with real-world objects. Frost & Sullivan reported that the global market of miniaturized devices is forecast to increase from 1.4 billion to 3.26 billion from 2014 to 2024. Unfortunately, the performance of miniaturized devices, which generally operate with limited battery power and transmit data over an unlicensed spectrum, is highly deteriorated due to the resource scarcity issues in terms of energy and spectrum. The energy scarcity issue limits the longevity of devices, and requires the operator to manually replace the depleted battery, which results in considerable maintenance costs. Even with sufficient energy supply, data transmission of devices conflicts with other networks that coexist in the unlicensed spectrum band, which creates the spectrum scarcity issue. To alleviate these energy and spectrum scarcity issues, numerous energy and spectrum harvesting technologies emerge, such as mini solar panel, piezoelectric transducers, and cognitive radio. By embedding these modules, the devices can harvest energy from the ambient energy sources and explore the idle licensed spectrum for data transmission, leading to energy and spectrum harvesting-enabled devices.
The ESH technologies have received much attention from the industry. Numerous commercial products have emerged on the global market, such as self-powered miniaturized devices produced by EnOcean, battery-free Bluetooth tags by Wiliot, and PolarFusion digital radio architecture for extreme low power by Innophase.
However, issues remain in the application of the ESH-enabled devices. First, empowering devices with ESH capabilities increases the manufacturing cost. How can one design cost-efficient, ESH-enabled, embedded architecture with promising performance? Second, considering that both the spectrum sensing and data transmission consume energy, the management of energy and spectrum resource both impact the system performance, which makes resource allocation challenging in ESH-enabled devices. Third, the energy harvesting process and activities of primary users, who own the licensed spectrum, exhibit high dynamics over time. How can one customize the communication protocol to adapt to such high dynamics and guarantee the delivery ratio?
To address these issues, this Special Section solicits original research and practical contributions in ESH technologies. We would like to provide a chance to share ideas and solutions for the enabling techniques which empower the devices with ESH capability. We also highly welcome submissions related to the joint management of energy and spectrum resources.
The topics of interest include, but are not limited to:
- Architecture design for ESH-enabled systems
- Data-driven modeling of energy and spectrum harvesting processes
- Communication protocol design for ESH-enabled networks
- Hardware design and prototyping of ESH-enabled systems
- Key scenarios/applications for ESH-enabled IoT devices
- Convergence of energy and spectrum harvesting
- Security, privacy, and trust in ESH-enabled systems
- Reliable data delivery in ESH-enabled systems
- Simulation platforms for ESH-enabled systems
We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.
Associate Editor: Guangjie Han, Hohai University, China
Guest Editors:
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- Deyu Zhang, Central South University, China
- Ning Zhang, Texas A&M University at Corpus Christi, USA
- Song Guo, The Hong Kong Polytechnic University, Hong Kong, China
- Geyong Min, University of Exeter, United Kingdom
- Shengrong Bu, University of Glasgow, United Kingdom
- Kanke Gao, Magna International Inc, USA
Relevant IEEE Access Special Sections:
- Energy Harvesting and Scavenging: Technologies, Algorithms, and Communication Protocols
- Intelligent and Cognitive Techniques for Internet of Things
- Energy Efficient Wireless Communications with Energy Harvesting and Wireless Power Transfer
IEEE Access Editor-in-Chief: Prof. Derek Abbott, University of Adelaide
Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access
For inquiries regarding this Special Section, please contact: hanguangjie@gmail.com.
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