Organizer: Nan Li, Northwestern Polytechnical University, Xi’an, China
Organizer: Xiucheng Liu, Beijing University of Technology, Beijing, China
Measurements of electrical & magnetic fields and electro-magnetic properties of materials are very important research topic in measurement science. The relative researches on electrical &magnetic measurements began in the 18th century. After the mid of the 20th century, the research interests have moved from classic fields to modern fields with the development of technology and the expansion of applications. Electrical & magnetic measurements provided indispensable and effective pathways for properties evaluation in materials and structures, ranging from appearance dimension, internal composition to microstructures, residual stress and defects, etc. It is a hot and attractive topic in the non-destructive testing and evaluation (NDT&E) today.
The Electrical & magnetic measurement technology has the advantages of fast in detection and strong in designability. Through tuning the operation frequency (Hz~ THz) and customizing the sensor types and configurations, the technology can be adaptive for complex structures of diverse materials, achieving higher precision and resolution. Visualization of measurement results is required recently by more and more engineering applications. Imaging results can be used to derive more comprehensive evaluation for high-quality product manufacturing and critical structural condition assessment.
This session of the measurement for NDT&E on electro-magnetic measurement and imaging focus on this topic to present recent developments in a) advanced sensors and instrumentations for imaging, b) efficient inversion and imaging algorithms, and c) new (or potential) applications. The prospective authors are invited to contribute to this special session with their research results in all aspects of above concerns. Submissions are welcome but not limited to the following topics:
- Novel electrical & magnetic sensor & instrumentation
- Advanced electro-magnetic sensing technology (magnetic flux leakage, magnetic Barkhausen noise, eddy current, etc.)
- Efficient inversion and imaging algorithms
- Intelligent signal processing
- New applications of electrical & magnetic sensing and imaging for NDT&E
- Tomography and scanning
Invited Paper/Presentation Details:
Dr. Jiabin Jia
Senior Lecturer at the Institute for Digital Communications, School of Engineering, University of Edinburgh, UK.
His research areas include electrical impedance tomography, medical imaging, and industrial process multiphase flow dynamics. His research vision aims at real-time monitoring and innovative diagnostic sensing for medical and industrial applications. To date he has more than 40 peer-reviewed journal publications and has led and contributed a range of research projects funded by from different funding councils and industrial companies. Dr Jia is a senior member of IEEE and a fellow of the UK Higher Education Academy.
Dr. Guiyun Tian
Professor of sensor technologies for the school of engineering at Newcastle University, UK.
He is EPSRC college member, fellow of the institute of technology and engineering (FIET), senior member of the institute of electronic and electrical engineers (SMIEEE), and fellow of the British institute of non-destructive testing (FInstNDT). His research interests include electromagnetic sensors, sensor array and sensor network, electromagnetic non-destructive evaluation, advanced signal processing, monitoring systems and applications.
Organizer: Lorenzo Ciani, University of Florence, Italy
Organizer: Marcantonio Catelani, University of Florence, Italy
Organizer: Loredana Cristaldi, Politecnico di Milano, Italy
Organizer: Giulio D’Emilia, University of L’Aquila, Italy
Significance of the topic: this Special Session represents an interesting opportunity for engineers and researchers who work in this area to meet and discuss about the state of the art, difficulties, innovations and improvements on instrumentation and measurement involved in components and system testing, fault diagnosis, condition monitoring, risk and safety assessment and management that allow to have more reliable devices. These topics lead to advances in technology, instrumentation and procedures that could push forward laboratory and university capabilities to develop new testing and measurement methods and their validation, the cooperation with accreditation, inspection and certification providers, the increase of accuracy and compliance analysis, with a strong impact in the quality, reliability and safety delivered to the environment, citizens and customers on the global market. Prospective authors can provide original contributions in this topic which can cover, but not only, the following aspects:
- Instrumentation and measurement methods for Testing and Diagnostics (Destructive and Non-destructive Testing, Vibration monitoring, Built-in Test Equipment and Automatic Test Equipment, etc.)
- Condition monitoring and maintenance of industrial process, plants and complex systems
- Measurements and techniques for Fault detection and diagnosis
- Design and implementation of laboratory tests (Reliability test, Environmental test, Burn-in test, Vibration test, etc.) and Qualification tests for components, assemblies and process
- Measurements, methods and instrumentation for evaluation of Reliability, Availability, Maintainability and Safety (RAMS), Risk assessment and management
- Impact of RAMS requirements in the emerging technologies for Life and Society, environment and new energy sources
- Effects of measurement uncertainty on the estimation of the RAMS parameters
- Standards definition, certification and accreditation.
This special session is supported and promoted by IEEE IMS TC32 – TC-32 – Fault Tolerant Measurement Systems”. I have received the request by the organizer Lorenzo Ciani.
Invited Paper/Presentation Details:
Title: Investigating the Use of Low-cost and Low Power Millimeter Wave RADAR to Improve Quality of Tomato Harvesting
Abstract: Low power millimeter wave RADAR is a novel and promising method that is emerging in the field of sugar content analysis. As fruit ripens, its sugar content increases while starch content reduces, thus the ability to measure sugar content in a whole fruit will enable better harvest quality. RADAR provides a fast, non-destructive method that could be used to measure properties of fruit which is considered ideal compared to traditional methods of measurement involving direct contact. In this study, the measurement setup of Acconeer A111 pulsed coherent RADAR sensor was investigated and proposed. Measurements were taken to correlate the RADAR reflectance readings with the analysed soluble sugar content (SSC) from High Performance Liquid Chromatography (HPLC), a well-established destructive chemical analytical method. Linear regression was used to statistically analyse the RADAR against fructose and glucose. Out of these two SSC, fructose content proved to have a stronger correlation with RADAR measurements and should be explored for future work. Additional future work to reduce measurement variability is to utilise a different RADAR setup whereby the transmitter and receiver angles can be varied to study the effect of the energy dispersion.
Speaker: Melanie Ooi
Bio: While working in close collaboration with several leading multinational electronics companies, Melanie has developed new testing techniques and test data processing methodologies that have been adopted by the industry partners. In the recent years she has also successfully researched on new measurement uncertainty evaluation approaches and frameworks with application to a multitude of science and technology areas (medical research, structural design, mechanical systems modelling, etc.) Her work in measurement uncertainty propagation has been adopted by the South African National Accreditation System (national body responsible for conformity assessment) in their guidelines document TG 50-02 since October 2017. In the recent two years, she has contextualised her measurement and instrumentation research to focus on New Zealand’s strategic areas of development through key partnerships with the horticulture and agriculture sectors. She has been acknowledged by several awards including the 2017 Mike Sargeant Career Achievement Award from Institution of Engineering and Technology U.K., Outstanding Young Engineer Award of the Year 2014 from the IEEE Instrumentation and Measurement Society, 2014 Excellence Award from the International Education Association of Australia, 2011 Citation for Outstanding Contributions to Student Learning from the Australian Learning and Teaching Council.She is the youngest female Fellow appointed to the Institution of Engineering and Technology, and is a U.K. Chartered Engineer. Melanie is currently a Senior Member of the IEEE, an Administrative Committee Member of the IEEE Instrumentation & Measurement Society (I&MS) as well as Secretary and Member of the Technical Committee on Fault Tolerant Measurement Systems (TC-32) of the IEEE I&MS.
Organizer: Marcus Perry
Demonstrating added value is essential in overcoming barriers to the industrial deployability of sensor technologies. Multifunctional sensors and smart materials offer this added value as they allow processes to be controlled, while they are simultaneously monitored.
This special session welcomes contributions that showcase materials, sensors, or sensing methods that offer sensing with some additional functionality. This additional functionality could include aesthetics, mechanical support, system stabilisation, actuation, energy storage or self-healing. Papers should draw particular focus to the design of new sensors or sensing methods, their characterisation, and/or their field deployment.
Multifunctional materials are engineered to exhibit two or more properties or functions. These materials encompass composites, coatings, dispersions, multi-phase materials, and metamaterials. Conventional materials and phases of matter can also be made multifunctional by using an appropriate doping / sensor additive strategy, or novel methods of electronic and optical interrogation.
Examples of multifunctional sensing methods and materials that span medical and engineering fields across I2MTC2020 topics include:
- Structural and Aerospace: Self-sensing magnetorheological dampers, or smart composites in which glass (or carbon) fibres provide both a reinforcement and optical (electrical) monitoring pathway.
- Medical: Conformable electronic temporary tattoos, smart bandages and mechanically supportive printed hydrogels for human health monitoring.
- Civil: Self-sensing concrete repair materials, detectable grouts, tensoresitive sensor- enabled geogrids for soil stabilisation, online monitoring of electrodesalination.
- Industrial processes: Smart labels for packaging, online evaluation of laser ablative cleaning from scattered light.
- Environmental: Nanomaterials for simultaneous water purification and monitoring, and wearable sensor technologies.
- Geological extraction and storage: Smart drills, and smart drilling fluids.
Organizer: Shibin Wang, Xi’an Jiaotong University, China
Organizer: Weihua Li, South China University of Technology, China
Organizer: Gaigai Cai, Xidian University, China
Industrial equipment health monitoring has attracted increasing attention in both academic and industrial communities. Dynamical changes in industrial equipment have to be captured in time for safe and reliable operations. These tasks are typically realized by using measurement technologies in combination with data analytics algorithms. Recent advances in the theory and methodology for measurement and data analytics have provided viable tools for dealing with the issue of industrial equipment health monitoring. This invited session is seeking papers on recent research, development and applications in industrial equipment prognostic and health monitoring with theoretical and/or applied nature. Suitable topics for this special session include but are not limited to:
- New measurement methodology for equipment health monitoring
- Wireless sensor networks
- Multi-sensor fusion methodology for equipment health monitoring
- Advanced signal processing for equipment health monitoring
- Advanced time scale/frequency analysis
- Sparsity-assisted equipment health monitoring
- Machine learning for intelligent prognostic and health monitoring
- Non-linear time series analysis
Invited Paper/Presentation Details:
Title: Machine Fault Diagnosis in the Era of Artificial Intelligence
Author: Ruqiang Yan, Ph.D. Professor & Executive Director, International Machinery Center School of Mechanical Engineering Xi’an Jiaotong University 28 Xianning West Road, Xi’an, 710049, Shaanxi, China
Abstract: The new generation artificial intelligence (AI) technology, especially deep learning, has shown great advantage in feature learning and knowledge mining, which provides a new way for machine fault diagnosis. This invited talk first provides a brief overview of deep learning. Then applications of some typical deep network models, especially the recently developed wavelet kernel embedded deep convolutional neural network model from our group, in machine fault diagnosis are discussed, followed by new trend of deep learning theory and development.
Organizer: Tuan Guo, Jinan University, China
Organizer: Yong Zhao, Northeastern University, China
In-situ and label-free fiber optic sensors (FOSs) are gaining large acceptance for applications in several branches of biomedical and chemical applications. They have good metrological properties, including high sensitivity, fast speed, immune to electromagnetic interferences, fine spatial resolution and nondestructive nature, are promising options for continuous investigation of biomedical and chemical interactions in situ (at micro & nano scale) and even in vivo.
In recent years, there have been a number of exciting developments that promise to make significant improvements to fiber-optic biomedical & chemical measurements and applications. The aim of this special session is to survey the current state-of-the-art FOSs technology and the significant advances in these fields.
Papers reporting about research related to the following topics are welcome:
- Fundamentals properties and fabrication approaches of bio & chemical FOSs
- Specialty optical fibers, devices, materials for bio & chemical FOSs
- Advanced optical fiber bio & chemical sensors
- Integration and packaging of bio & chemical FOSs
- Performance of FOSs and systems in real bio & chemical applications
- Standardization efforts for FOSs biomedical and chemical industries
Invited Paper/Presentation Details:
Title Flexible Microfiber Sensors for Health Monitoring
Authors and their affiliation Prof. Fei Xu College of Engineering and Applied Sciences, Nanjing University, Nanjing 210093, China
Abstract These attachable and flexible smart devices connected to human skin for the continuous and close monitoring of an individual’s activities are commonly considered as essential components in the next generation of human-portable devices for remote diagnosis and treatment. Silica-fiber-based sensors have the advantage of being small, electrically isolated, immune to electromagnetic fields, and easily incorporated into networks. However, only few of them were used for monitoring physiological signals directly, due to their limited sensitivity, size, comfort, and safety. In this work, we will report our research on flexible microfiber devices with ultra-high sensitivity and miniature size, and their applications on real-time health monitoring of not only the human body but also living cell.
Organizer: M. Shamim Hossain, King Saud University, KSA
Organizer: Abdulmotaleb El Saddik, University of Ottawa, Canada
With the development of smart medical sensors, instruments, systems and the health care technologies, “smart health monitoring” is getting remarkable consideration from the academia, and healthcare industry. Accelerated by a tremendous increase of this healthcare data with the advent of current pandemic, it is becoming an indispensable part of today’s healthcare data analytics. Such large-scale healthcare data has opened challenges and opportunities for researchers to manage, analyze, measure, and interpret data in order to identify the best ways to deliver affordable and quality patient care. Artificial Intelligence (AI) has gained tremendous attention by utilizing its machine learning algorithms and data analytic techniques to improve healthcare diagnostics and predictive analytics for quality patient care as well health monitoring. This special session is seeking for papers on recent research, methodologies, and systems for the design, development, instrumentations, and measurement techniques on AI-enabled health monitoring for providing insights into smart healthcare service demands. Authors are solicited to submit complete unpublished papers in the following topics. Topic includes but not restricted to:
- AI-enabled health data classifiers and patient outcome predictors for smart healthcare
- Advanced AI/ML techniques for multimedia healthcare data (e.g., image, audio, video) analysis of COVID-19 and alike
- ML-enabled methods, systems, instruments, and open issues for healthcare
- AI-enabled measurement techniques for health monitoring
- AI/DL-enabled healthcare data fusion
- DL-techniques and instruments for handling Post COVID-19 crisis
- AI-driven long-term risk of pandemics prediction
- AI/ML for COVID-19 treatment and prognosis
Invited Paper/Presentation Details:
Invited presenter/speaker: Prof. Sabah Mohammed, Department of Computer Science, Lakehead University, Canada
Author and affiliation: Proposed Title “Exploration of smart health technologies in the era of COVID-19 and beyond”
Presenter’s Bio: Prof. Dr. Sabah Mohammed research interest is in intelligent systems that have to operate in large, nondeterministic, cooperative, highly connected, survivable, adaptive or partially known domains. His continuous research is inspired by his PhD work back in 1981 from Brunel University (UK) on the employment of the Brain Activity Structures for decision making (planning and learning) that enable processes (e.g. agents, mobile objects) and collaborative processes to act intelligently in their environments to timely achieve the required goals. Having trained in medicine with a computer science PhD in Artificial Intelligence (AI), Dr. Mohammed is full Professor at the department of Computer Science at Lakehead University (Ontario Canada) since 2002 and core professor at the Bio-Technology program at Lakehead. Dr. Mohammed efforts in establishing healthcare related programs at Lakehead are notable like the specialization Health informatics, Bio-Technology and the Bioinformatics programs at Lakehead. With a research background in industry and academia, he has a strong international research reputation for his work on clinical decision support systems supporting remote areas, ubiquitous and extreme environments. Prior to his work at Lakehead University, Dr. Mohammed was the chair of three computer science departments at HCT, Philadelphia and Applied Science Universities. He is the founder and Editor-In-Chief of the IGI Global International Journal of Extreme Automation and Connectivity in Healthcare (IJEACH) as well as the supervisor of the Smart Health FabLab at Lakehead University. Dr. Mohammed is currently the chair of the special interest group on Smart and Connected Health with the IEEE ComSoc eHealth TC. Dr. Mohammed is also a Professional Engineer of Ontario, Information Processing Professional with CIPS, Senior Member of IEEE and Outstanding Associate Editor with IEEE Access. Dr. Mohammed research is supported by major granting organizations like NSERC and CFI. More information on Dr. Mohammed can be found on his institution website http://flash.lakeheadu.ca/~mohammed.
Organizer: Luigi Rovati, University of Modena and Reggio Emilia, Italy
Organizer: Mario Ettore Giardini, University of Strathclyde, UK
The eye is the only part of the body where it is possible to gain non-invasive visual access to the blood vessels and to nervous tissue. Furthermore, vision is an essential function for daily living. For this reason, measurements on the eye are a critically important part of core medical diagnostics. Instrumentation and measurement methods in modern ophthalmology have reached an extraordinary level of complexity and performance. Major advancements in ophthalmic practice are strictly related to innovative instrumentation for diagnosis and therapy. As an example, we can consider how optical coherent tomography (OCT), in recent decades, has completely changed the diagnostic process of many ocular fundus diseases by providing high resolution cross-sectional images and dimensional details of the retina. Further advances have brought ophthalmic diagnostics from secondary care to the field and to the community, for the screening of societally important diseases, and complemented the core measurement functionalities with advanced data processing, including machine learning-based algorithms. For these measurement systems, the metrological performances must be defined with accuracy as they are the basis of critical diagnostic decisions.
The present Special Session aims to present key advances in the broad range of metrological research in the field of ophthalmic diagnostics, and give insight on the related clinical implications.
Submissions of original research that highlight novel findings related to measuring systems, instrumentation and sensors, including their characterization, for ophthalmic applications, are welcomed.
Topics covered include:
- Ophthalmic instrumentation and sensors
- Remote measuring systems for ophthalmic screening and diagnosis
- Optical instrumentation for diagnosis and therapy
- Sensors for retinal prosthesis and bionic vision
- Optical characterization of laser surgical systems
- Optoacoustic monitoring
- Measurements for vision correction
- Measurement performance and clinical implications
Invited Paper/Presentation Details:
Title: Automated algorithmic assessment of retinal images: experiences from real-world applications
Speaker: Dr Sam Philip (NHS Grampian ed University of Aberdeen) (CV attached)
Organizer: Der-Chen Huang, National Chung Hsing University, Taiwan
Organizer: Tuan Guo, Jinan University, China
Organizer: Huan Liu, China University of Geosciences, China
Organizer: Chi-Hung Hwang, Taiwan Instrument Technology Research Center, Taiwan
This special session is co-organizing by TC-18 and TC-42.
The purpose of this special session is providing a discussing platform for all colleagues who are working on the development of sensors, instruments, and systems for environmental monitoring; particular for the Envi-IoTs’ development and applications, such as the development of the algorithm for analyzing the collected field data, and the potential application of the collected data for the environmental change investigation, disaster monitoring/ forecasting, the disease-vectors survey, pandemic propagation modeling and predicting with many other applications are including into this special session. The main topics of the special session are
- The development of Physical/ Chemical/ Bio-Sensors for the field data collection;
- System integrating and validations;
- Volunteer-based distributing sensor system for Envi-IoT applications;
- Applications of robots and unmanned systems for field data collecting;
- Field data collecting, management, and identification;
- Applying artificial intelligent technologies for data analysis, classifications, modeling, and possible predication;
The topics not limited to the items mentioned previously; any subject and application associated with collecting and the application of the collected spatial/ time-domain data from the field which relate to human safety and sustainability are welcome. We also welcome PIs of the on-going projects to share experiences on implementing the Envi-IoT systems.
Organizer: Salvatore Graziani, University of Catania, Italy
Organizer: Carlo Trigona, University of Catania, Italy
During the 50th Earth Day, on 22nd April 2020, António Guterres, Secretary-general of the UN, released a message: “…Climate disruption is approaching a point of no return. We must act decisively to protect our planet from both the coronavirus and the existential threat of climate disruption”. The scientific community is asked to contribute to a switch from the grey economy to a green economy. It is estimated that 44.7*109 kg of e-wastes has been produced in 2016 – an equivalent of almost 4500 Eiffel towers, 12.3*109 kg are produced in Europe. In 2018 its production has achieved an amount of approximately 50*109 kg. Only 20% of this is formally recycled. New technologies are required to improve human-beings quality of life in the respect of the environment. The implementation of a sustainable economy requires developing greener electronics, from the choice of the raw materials to the technology used for electronics production and characterization, to end with their environmental impact after useful life.
At least three main aspects need to be considered, in search of such new sensors, transducers and conversion elements. We need low-cost and environmentally-safe raw materials, production strategies that both require low energy consumption and moderate release of pollutants in the environment, and finally, but not less important, resulting systems that can be recycled, or even better, biodegraded.
We need a multidisciplinary approach where challenges mentioned above are investigated. The Special Session will be devoted to all the aspect of the life of sensors, transducers, energy harvesters, and novel measurement systems, which are relevant to their environmental impact, from materials, to production step, and after-life fate.
Submissions are welcome but not limited to the following topics:
- Sensors, transducers based on novel materials;
- Green electronics;
- Novel methods for sensing;
- Emerging technologies for sensors and sensing methods;
- Low-cost and low-energy based production processes;
- Green-chemistry for transducer fabrication;
- Additive or low-temperature production processes;
- Ink-jet based transducers;
- Polymers and biopolymers -based transducers;
- Energy harvesting and energy accumulation;
- Low-power or non-battery based autonomous transducers;
- Disposable and biodegradable transducers;
- Models and simulations of green transducers;
- Environmental fingerprint of electronics and smart systems
Organizer: Sebastian Bader, Mid Sweden University, Sweden
Organizer: Michele Magno, ETH Zurich, Switzerland
The number of sensing devices drastically grows and has already exceeded the number of people on earth. ‘Smart sensor’ are at the edge of the Internet of Things and are supposed to be tiny embedded system with sensing, processing, and communication capabilities which can be accessed 24/7. However, very few examples of ‘smart things’ are today really intelligent as they mainly stream the data out, “delegating” the intelligence to the cloud. However, a new trend is happening today, combining learning algorithms and constrained electronic devices to make IoT devices smarter by enabling cognitive functions. Promising results are appearing across many domains, e.g., hardware, machine learning, and constrained computing platforms. Although the research in embedded Artificial Intelligence (AI) is still in its infancy, it is growing and brining fascinating challenges. Progress in this area opens up a wide vista for numerous applications, including wearable computing, condition monitoring, smart security, smart home, and smart cities. This special session focuses on Artificail intelligence for low power (range of mW) embedded systems that include onboard sensors. Papers from hardware, software, algorithms, and applications are welcome in this section.
In particular, the papers should focus on (but are not limited to):
- New techniques for data processing and inference on embedded/mobile devices.
- Adaptation and optimization of data processing algorithms for use on low power embedded systems.
- Decision making and actuation based on data from pervasive sensing.
- Human-machine interaction using wearable systems.
- Design and implementation of real-world applications and systems
- Experiences, challenges, and comparisons of platforms.
- Embedded machine learning algorithms on microcontrollers.
- Hardware and system design to enable machine learning on sensor data.
- Computer vision for resource-constrained and mobile platforms.
- Experiences from real-world low-power smart sensing applications and deployments
Invited Paper/Presentation Details:
The proposed special session will be introduced by an invited presentation delivered by Prof.
Tinnosh Mohsenin. Prof. Mohsenin is affiliated with the University of Maryland, Baltimore County, USA, and she is an internationally recognized expert in the field of Edge Intelligence. The invited presentation may be accompanied with an invited paper. This was, however, still unconfirmed at the time of submission.
Invited presentation title: “Micro AI: When Intelligence Moves to the Low Power Sensors”
Abstract: Artificial intelligence is being used in a variety of edge-computing devices such as biomedical sensors, wearables and autonomous systems. Processing these sensor-level machine learning tasks come at the cost of high computational complexity and memory storage which is overwhelming for these light weight and battery constrained devices. Equally important is the need for designing smarter AI systems that can reason over in the face of a highly variable and unpredictable world. This talk overviews some research solutions that enable performing data analytics from a variety of multimodal sensors in real time while consuming low power. I will also talk about adding reasoning in these systems to improve acting and learning performance. Combining these solutions will bring exciting opportunities for future micro AI processors.
Presenter biography: Tinoosh Mohsenin is an Associate Professor in the Department of Computer Science and Electrical Engineering at UMBC and Director of the Energy Efficient High Performance Computing Lab. Prof. Mohsenin’s research focus is on designing low power processors for high computational machine learning and knowledge extraction techniques used in wearables, Interment of Things and Autonomous systems. She has over 100 peer-reviewed journal and conference publications and is the recipient of NSF CAREER award in 2017, the best paper award in the ACM Great Lakes VLSI conference 2016, and the best paper honorable award in the IEEE Circuits and Systems Symposium 2017 for developing processors in biomedical and deep learning. She has previously served as Associate Editor in IEEE Transactions on Circuits and Systems-I (TCAS-I) and IEEE Transactions on Biomedical Circuits and Systems (TBioCAS). She served at the General Chair, Program Chair of 29th and 30th Editions of ACM Great Lake VLSI conference in 2019 and 2020, respectively. She was also the Local Arrangement Chair for the 50th Edition of IEEE ISCAS conference. She has been the Plenary Speaker at the IEEE AICAS 2020, IEEE ICECS 2020, and IEEE DCAS2020 conference.
Organizer: Emanuele Zappa, Politecnico di Milano, Italy
Organizer: Paola Saccomandi, Politecnico di Milano, Italy
In the context of Industry 4.0 and current pandemic time situation worldwide, deployment for compact instrumentation able to provide advanced and non-obtrusive measurement is high. While vision-based systems are already widespread for applications in industry and research, the need to achieve additional information beyond the visible range is motivating the fast increase of non-visible imaging in industry and research. Measurements with non-visible imaging, including X-ray imaging, ultraviolet, infrared, microwave, multispectral, and hyperspectral imaging techniques, involve the capture of images across various parts of the electromagnetic spectrum, and are able to combine chemical, physical and high resolution spatial information. The improvements on metrological characteristics, size and cost, added to the development of robust and application-oriented data processing solutions, are leading factors of the adoption of non-visible imaging techniques for on-field and in-process applications such as machine sorting, food quality control, production control, environment monitoring. This Special Session aims at gathering scientific contributions focused on the current state-of-the-art of non-visible imaging techniques for industrial and scientific applications, and on valuable advances in the design, fabrication, metrological characterization, and application of innovative measurement systems.
- Multispectral – hyperspectral imaging
- Infrared and Thermal Imaging Systems
- Instrumentation for non-visible imaging
- Multichannel Imaging Systems
- Microwave imaging
- Imaging sensors and platforms
- Image processing techniques
- Applications for quality inspection in industrial fields, including food industry, manufacturing processing, material sorting
- Applications in biomedical and clinical fields
Invited Paper/Presentation Details:
Hyperspectral Imaging Applications in Different Scientific and Industrial Sectors
Prof. Silvia Serranti
Department of Chemical Engineering, Materials & Environment (DICMA),
Faculty of Civil and Industrial Engineering, University of Rome “La Sapienza”.
Raman, FT-IR and hyperspectral imaging, digital image processing (classical and hyperspectral)
Silvia Serranti is Full Professor at the Department of Chemical Engineering, Materials & Environment (DICMA), Faculty of Civil and Industrial Engineering, University of Rome “La Sapienza”. She is a PhD geologist and she has been working for 18 years at the Raw Materials Unit of DICMA. Research activity is mainly focused to primary and secondary raw material characterization and valorization in order to improve the industrial process performances and the product quality and to develop innovative on-line sorting strategies, based on different sensing techniques. The characterization of primary and secondary raw materials is carried out by different classical and advanced analytical methods: laser diffraction, spectroscopic techniques, such as Raman, FT-IR and hyperspectral imaging (VIS-NIR, NIR and SWIR wavelength field), micro-tomographic techniques, optical and electronic microscopy (SEM), classical chemical analyses (ICP, XRF), digital image processing (classical and hyperspectral).
Organizer: Federico Tramarin, University of Modena and Reggio Emilia, Italy
Organizer: Stefano Cattini, University of Modena and Reggio Emilia, Italy
Organizer: Alberto Ferrari, University of Modena and Reggio Emilia, Italy
The management of emergencies, such as the current COVID-19 pandemic, empha-sized a set of requirements and unprecedented problems for measurement systems. Such a task definitely imposes to provide answers in a short time, often directly oper-ating in the field and with the need to integrate information from multiple sources. In-accurate, or incomplete information can lead to inappropriate choices, with potentially severe consequences in emergency situations. Smart sensors and effective measur-ing systems become hence essential, and in such a scenario, they should provide for high level of reliability and robustness, fast response times, self-standing capabilities, and preferably, ease of use even by unskilled personnel.
Indeed, a relevant example is the surge, in early 2020, of requests for face masks and other Personal Protective Equipment (PPE), that was before limited to healthcare per-sonnel, whereas their use by the general population is fundamental to limit the spread of Sars-Cov-2. However, while requirements for healthcare professionals are well established, facing the increased demand from the population lead to issues for the lack of specific knowledge and regulations. Several Universities and laboratories re-sponded to the request and brought into operation, in a very short time, the necessary facilities and the relative procedures for measurement, management, and reporting tests, to the aim of assessing PPE efficacy and biocompatibility. This new use allows to provide an overview of the performance of the various PPE prototypes and products that producers or importers intended to test according to the ISO standard, and in turn
revealed unexpected limitations and inadequacies, also in terms of procedures and standard specifications that need further investigation.
Analogously, yet in a different direction, the need of integration of information from different sources imposes the adoption of new solutions for remote sensing and measuring systems. It is the case, as an example, of UV disinfection systems, whose wide-spread diffusion due to COVID-19 is leading to an ever-increasing pervasiveness of medium-to-small O3 sources that can be found, even inadvertently, in several diverse locations – workplaces, homes, hospitals, restaurants, and pubs. Since the exposure to O3 may potentially harm human health, emergency management highlighted the need for innovative and distributed monitoring systems for the measurement of O3 exposure. On the one side, there is the need to design and test innovative smart sensors, able to accurately provide meaningful measurement data, and to share data with other smart sensors and measuring systems. On the other side, new solutions, particularly exploiting the opportunities provided by the technology related to Internet of Things (IoT) need hence to be deployed, to allow an effective wide-area monitoring and real-time collection, integration, and analysis of data.
The aforementioned examples should be representative of a broader set of issues and unprecedented needs related to the management of emergencies. In this scenario, research contributions dealing with smart sensors, measuring instruments and monitoring solutions based on IoT technologies, as well as research related to the shortcomings of current standards are particularly welcome.
Topics of interest for this Special Session includes, but are not limited to:
- Innovative Smart sensors and measuring systems for the management of emergencies
- Design, characterization and testing of smart sensors and measuring systems for the management of emergencies
- Applications of IoT sensors and measuring systems to the management of emergencies
- Wireless Internet of Things solutions for smart sensors in emergencies management
- Bluetooth and BLE technologies for IoT measurements applications
- Long and Short-range wireless solutions, and LPWAN technologies for IoT measurements applications
- Large scale deployment of IoT sensors for monitoring applications
- Localization systems based on wireless sensor and IoT technologies
- Testing of face masks with respect to performance parameters related to breath- ability and bacterial filtration efficiency
- Testing of face masks with respect to biocompatibility parameters according to ISO 10993-1
- Testing of performance for others PPE