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The Ninth International Conference on Dependability

DEPEND 2016

July 24 - 28, 2016 - Nice, France


Tutorials

T1. IoT 2.0 Sensor Innovations: Making Sense of Intelligent Sensors
Prof. Dr. Sergey Y. Yurish, International Frequency Sensor Association (IFSA), Spain

T2. Architectures for IoT Applications in the Energy Domain
Dr. Guillaume Habault, Télécom Bretagne France

T3. Surface Enhanced Raman Scattering: Substrate Design and Fabrication
Dr. Victor Ovchinnikov, Aalto University, Finland

DETAILS

T1. IoT 2.0 Sensor Innovations: Making Sense of Intelligent Sensors
Prof. Dr. Sergey Y. Yurish, International Frequency Sensor Association (IFSA), Spain

1, 2 Dr. Sergey Y. YURISH
1 International Frequency Sensor Association (IFSA), President
2 Excelera, S.L. (Barcelona, Spain), CTO & Co‐Founder

IoT devices are focused on sensing and actuating of physical environment. While the IoT represents the convergence in advances miniaturization, wireless connectivity, increased data storage capacity and batteries, the IoT wouldn’t be possible without sensors. Sensors detect and measure changes in physical world and they are necessary to turn billions of objects into data‐generating “things” that can report on their status, and in some cases, interact with their environment. 25 billion devices are expected to be connected to the Internet by 2015 and 50 billion by 2020, as predicted by Cisco's IBSG.

Today, dozens IoT hardware platforms are introduced on the market by many big companies. But in many cases the emphasis is done only on communication features and data management. With many existing hardware IoT platforms, only very limited number types of sensors can be used.

In this tutorial, we will explore how modern sensor technology is applied to specific vertical domains in the IoT space (Industry 4.0 and Smart Cities), specifically examining how the sensors are enabling the evolution from “smart” to becoming “intelligent”. To make intelligent senses not as easy as it Looks. One of the promised approach is based on the evaluation from analog informative parameters as voltage and current to quasi‐digital informative parameters of sensor’s output such as frequency, period, duty‐cycle, PWM, etc. In the tutorial, examples of self‐adaptive intelligent sensor designs for industrial IoT and Smart Cities will be discussed in details. The integration of the Series of Universal Frequency‐to‐Digital Converters (UFDC) and Universal Sensor and Transducer Interface (USTI) integrated circuit into sensor systems has the potential to greatly simplify the design of the system and contribute to further increasing of system level integration, flexibility and functionality. Such design approach for intelligent sensor systems lets to get the right data at the right time.

 

T2. Architectures for IoT Applications in the Energy Domain
Dr. Guillaume Habault, Télécom Bretagne France

Internet-of-Thing (IoT) concept consists of a set of smart "things" that are able to connect to Internet and feed other devices with their collected information. As long as these things are uniquely identi fied and provide empirical data on our environment, anything can be a "thing". As a result, numerous and a wide variety of possibilities can be considered with the IoT concept. All these possibilities makes it very promising, but at the same time very complex as it is estimated that billions of object will be connected within a 10 year span. Moreover, most of current protocols and architectures are not designed to support this amount of devices and their speci ffic traffic flows.

Energy domain is one of the many possible applications for IoT. There are several notable trends taking place in the energy market today. The majority of the changes lead towards a network where central energy production facilities - dams, nuclear power plants, etc. - must co-exist with a myriad of smaller, less reliable, systems. While at the same time energy demand for these smaller systems will show a signi significantly higher fluctuation. Because proper operation of the electrical network is based on the balance between production and consumption, this poses a great challenge for the management of the network. To properly cope with the problem, new IT systems are needed for energy actors to interconnect and better manage energy use.

For the system to be properly balanced, real-time and predictive measurement along with control capabilities are needed in a widespread management system. This necessarily involves handling the issue of controlling a large volume of distributed consumption and production. While remotely controlling and coordinating the electrical loads of homes, office buildings and industrial premises has been possible for decades already, such controls are not yet widely enough adopted to confront the challenges of new electrical networks. A key reason for this is that such adoption is still too expensive in high volume as current architectures have not been designed for these applications. All of them make it possible to connect di fferent nodes and systems, to retrieve data from endpoints, and to control the nodes. None of them however provides the type of high volume mapping and search capabilities that energy network operators are looking for to cope with the dynamism and automation requirements of modern grids.

This tutorial will overview existing IoT architectures and how they match with the requirements of IoT applications for the energy domain. As none of the known solutions address all these requirements, an new architectural model has been proposed that draws from the best practices of Internet technologies.

 

T3. Surface Enhanced Raman Scattering: Substrate Design and Fabrication
Dr. Victor Ovchinnikov, Aalto University, Finland

Surface Enhanced Raman Scattering (SERS) gave start for broad practical application of normally weak Raman scattering (bulk-phase Raman) in real world. Thirty years ago it was found that Raman signal from monolayer of analyte on roughened silver surface is unexpectedly strong. Since that SERS became a powerful spectroscopy technique that allows for highly sensitive detection of low concentration analytes through the amplification of Raman scattering on nanostructured metal surfaces.

This tutorial starts from the origin of the infrared and Raman spectra. After that absorption and scattering of light by silver and gold nanoparticles, supporting surface plasmons is discussed. Then, some fundamental processes are summarized for the metal nanoparticle – molecule interaction that provide SERS amplification. Then, the SERS setup for experiments is described. Here the concept of SERS substrate is introduced and main approaches to its design and fabrication are presented. They are classified in two groups depending on pattern generation that can be either lithography - or non-lithography based. The first group includes phase shift mask and interference lithography, while beam writing techniques and self-assembling methods belong to the second group. Pattern transfer to metal can be accomplished by direct etching, lift off, nanosphere lithography, shadow masks (templates), chemical synthesis, nanoimprint and electroplating. At the moment, there is no single commonly approved design of the SERS substrates, as there is no universal manufacturing process of them. Meanwhile, both plasmon structures and their fabrication methods are key factors of SERS substrate efficiency. Therefore, orientation in SERS substrate practical realizations is crucial for future SERS applications. Due to appearing of Raman microscopes and portable Raman spectrometers utilizing SERS substrates, SERS transitioned from a pure laboratory technique to a valuable practical method.

The motivation of the tutorial is the vast number of publications and applications on SERS that require basic introduce on method, SERS substrate design and their fabrication approaches. I believe that improved understanding of SERS substrate concept will benefit multiple fields of research, such as physics, chemistry, medicine, biology, pharmacology, microfabrication, optics both in academy and industry. The tutorial is meant for graduate and postgraduate students, researchers and scientists.

 
 

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