Pasquale Arpaia

Antonio Esposito

Telemonitoring systems based on Brain-Computer Interfaces and Augmented Reality in smart industry

Pasquale Arpaia and Antonio Esposito

Augmented Reality (AR) is a technology that overlaps computer-generated perceptual information with actual world, in order to enhance human perception of the surrounding environment. In an industrial context, the AR can help several working aspects, from training on-the-job to product design, and maintenance. Typical user interfaces for these devices are touch screens, vocal commands, or gestures. Instead, the combination of AR with a Brain-Computer Interface (BCI) can provide the solution to a hands-free user input, thus providing a novel way of gathering information from the surrounding environment. BCI is a device capable of interpreting human intentions by reading user neuronal activity. Many paradigms have been developed for BCI systems. Each paradigm requires the extraction of specific features from a set of brain signals, such as a voltage peak or the frequency of an oscillation. Some studies have shown that “steady-state visually evoked potentials”, or SSVEPs, are highly reliable in terms of accuracy and reproducibility. Furthermore, user training is not mandatory for SSVEP-based BCIs. In an SSVEP-based BCI, brain potentials are evoked with external stimuli, which can be flickering LEDs or flickering icons on a display. These brain signals do not depend on cognitive paths, thus being a useful communication channel also for people with cerebral diseases. Concerning the above discussion on hands-free AR, smart glasses LCD displays can be employed successfully for stimulus presentation.

In this tutorial, the design of a telemonitoring system integrating AR glasses with BCI is treated, with a particular focus on inspection applications in industry and healthcare. Technical issues are also addressed with the aim to build low-cost and non-invasive wearable systems for a novel interaction with wireless sensors or electronic devices in general.

Harold Kirkham

Mihaela M. Albu 

An Explicative Dictionary of Measurements in Modern Power Systems 

Harold Kirkham, Artis Riepnieks, Rod White and Mihaela M. Albu 

Measurement affects many aspects of electric power systems, including planning, operation, and markets. As the grid becomes “smarter” it becomes more automated. Measurement is removed further from human involvement. Smart grid operation, including control of the energy flow in active distribution grids, adds more challenges to the measurement problem. However, not all aspects of measurement are well-understood in the power community. 

Presently there is a gap between the measurement models assumed by most of the measurement devices deployed in power systems and the measured quantities themselves. There is a further gap between what is known from the information provided by the measurements, and what is often thought to be known. There is, in other words, a metrology gap and an epistemology gap. We intend to raise awareness of the two gaps (the metrology and the epistemology gap) for designing smart, autonomous grids, making models and running numerical simulations, and ultimately safely operate such emerging grids.

The tutorial will address:

·      The measurement paradigm in power systems; most of the quantities of interest are indirect measurements deriving from voltage and current signals furnished by instrumentation transformers. Some of the constructs used have been problematical for over a century.

·      Specific measurement requirements in smart grids.

·      Measurement codes and standards worldwide. In particular, the standard that defines four significant power quantities (power, reactive power, apparent power and power factor) is undergoing significant revision.

This tutorial will challenge and explain in-use definitions for relevant quantities and indicators in modern power systems, in alphabetical order.

Josip Marijan

Gabrijel Smoljkic 

ROS on the Edge 

Josip Marijan and Gabrijel Smoljkic 

Edge is a term coined with the recent expansion of IoT devices, sensors and platforms. Edge computing is computing that’s done at or near the source of the data, instead of relying on the cloud application to do all the work. Sending all the generated data to a centralized center causes bandwidth and latency problems. Edge computing gives us an alternative to process and analyze data closer to the point where it is created. The data processing and storing becomes more comprehensive, response time is faster which leads to improved customer experience.

ROS is a component-based framework which makes development, deployment and modification of the software application particularly easy. It implements a microservice architecture and publisher – subscriber paradigm through ROS topics. ROS is intended as a flexible framework which has set of tools, libraries and conventions to simplify writing robot software. ROS application is written as a set of distributed nodes (ROS processes).

But in the end, a robot is nothing but a complex set of actuators, sensors and data processing algorithms. In this sense, ROS has always been on the Edge. ROS on the Edge (RoTE) is intended to be a platform which unifies ROS tools used for data processing and streaming, as well as the configuration of the underlying ROS nodes.

In this tutorial, the aim is to introduce the RoTE project to the broader audience for the first time. Here we will demonstrate use-cases of RoTE and how the system can be configured for real time data measurement and acquisition. Topics which are going to be covered with this tutorial are:

• Configuration of a device running RoTE
• Getting familiar wih the RoTE front-end
• Deploying the RoTE application on premise
• RoTE under the hood: architectural overview of a RoTE system

Jean-Charles Bolomey

Microwave-Based Imaging Systems for Medical Applications, from Proofs of Concept to Clinical Practice

Jean-Charles Bolomey

Emeritus Professor, University Paris-Saclay, France

The tutorial aims to address specific issues related to microwave-based imaging systems and their use for medical applications, a topic at the crossroad of microwave technology and medicine practice. Beyond the standard engineer viewpoints aiming to consider an imaging system, from microwave frontend sensors to data processing schemes, as a black box instrument, some emphasis is given to end-user’s, i.e. physicians, requirements and real needs in the strong competitive medical imaging landscape widely occupied by well recognized and routinely practiced imaging modalities, mostly based on X-rays, ultrasounds, magnetic resonance (MRI) and nuclear (PET) technologies. The tutorial consists of three main Parts.

The first Part briefly retraces the genesis of microwave-based imaging and its evolution since early dosimetry assessments until medical diagnosis applications exploiting the sensitivity of living tissues dielectric properties with respect to biophysical parameters of clinical relevance, such as water content, blood flow rate or temperature, etc. Such sensitivity may hence enable detecting, localizing and differentiating pathological from healthy tissues. The principles of the two major approaches to microwave diagnosis imaging are introduced. The first one aims to quantitatively retrieve the tissue dielectric permittivity thanks to solving a non-linear inverse scattering problem. The second one consists in qualitatively visualizing ‘hot spots’ resulting from local dielectric contrasts by using the radar equation. Both approaches will be compared according to their relative advantages and limitations in terms of microwave system complexity and computer power requirements. In addition, the growing use of machine learning is also briefly considered, either for image augmented post processing or direct diagnostic classification.

Part II, dealing with the impact of hereabove described microwave systems, is beginning with a short overview of the medical imaging market enabling to identify the possible access points for microwaves, thanks to their supposed specific advantages. Two examples of worldwide major health care relevance applications are more particularly considered, breast cancer and brain stroke diagnosis. Early results stemming from clinical trials enable to estimate the performances of microwave-based imaging systems in terms of sensitivity/specificity capability. The timeliness of the tutorial is that the key moment is arrived where these early, even preliminary, clinical results allow to better identify the limitations of microwave imaging systems and, hence, how their clinical acceptance could be improved.

Part III is dedicated to Specific Absorption Rate (SAR) measurements, which, aiming to quantify human exposure to electromagnetic fields, constitutes another aspect of interactions between microwaves and living tissues. It is shown how the experience gained in the development of microwave imaging systems is finding their natural application to dosimetry measurement techniques, especially to speed up standard SAR measurement procedures, a crucial issue to assess the compliance of a dramatically growing number of 5G wireless devices.

To conclude, the tutorial provides a summarized budget of the research effort dedicated to microwave-based imaging during the past four decades. The future of this ‘last comer’ imaging modality is, to the extent that it can reasonably be done, envisioned in light of microwave and computer technology expected evolution, without neglecting the already started invasion of Artificial Intelligence in existing imaging modalities and, more generally, in the medical practice.

Markus Neumayer

Stochastic Processes in Measurement Signal Analysis

Markus Neumayer

Institute of Electrical Measurement and Sensing Systems

Signal analysis and signal processing are core elements of measurement science and technology. Signals carry the information about the quantity of interest. Sufficient understanding about the nature of the signals is required, to correctly extract the desired information. Furthermore, the presence of measurement noise adds a random component to the signals. Based on a correct understanding about the nature of a signal, suitable non-parametric or parametric signal processing methods have to be selected. This tutorial discusses the treatment of signals within the framework of stochastic processes. The framework of stochastic processes maintains a probabilistic view on signals. Based on the description of random variables, the expectation operator is used to characterize signals by different metrics like moments or correlation functions.  These quantities can be related to classical signal parameters known from electrical engineering like the signal power or the DC-component, allowing a generalized view on signals. The temporal properties of these moments are used to form a classification between stationary and non-stationary stochastic processes. The distinction between these two classes is crucial for spectral analysis using the DFT based measurement system.  Based on the classification by means of the stationarity, the important class of wide sense stationary (WSS) stochastic processes can be defined. For WSS stochastic processes a unified framework relating several signal analysis methods can be derived. An important quantity is the power spectral density (PSD), which is based on the Wiener-Khinchin theorem. The PSD allows a spectral analysis of random signals, e.g. noise signals.  Furthermore, the transformation of WSS stochastic processes by linear time invariant (LTI) systems is addressed and the influence on the signal analysis methods is summarized. The tutorial covers the motivation and the aspects of considering signals within the framework of stochastic processes. The description of signals within this framework and the correct application of signal analysis methods is addressed. Furthermore, the framework allows the derivation of optimal signal estimation and signal detection techniques. Examples for the application of the framework for measurement applications will round up the tutorial.

Giovanni Battista Rossi

Francesco Crenna 

Uncertainty Evaluation Based on Measurement Modeling 

Giovanni Battista Rossi and Francesco Crenna 

Uncertainty evaluation is a major task for quality assured measurement. A systematic approach to such an evaluation, based on measurement modeling, is presented. Three main architectures for practical measurements – the device, the measuring chain and the multichannel measurement system – are considered and a general model expressed by block diagrams is developed, where uncertainty sources are represented by probabilistic variables. The solution of the uncertainty evaluation problem naturally outcomes by solving such a model in respect of the variable of interest, without the need of referring to specific statistic-probabilistic school of thought, such as the Bayesian or the frequentistic one. The standpoints of the designer/manufacturer and of the user of the measurement system are outlined and discussed.

The tutorial aims at providing practical instruction to operators involved in measurement and instrumentation on how to systematically proceed in the evaluation of  uncertainty, with an approach based on a block-diagram representation of measuring chains and systems, that should be familiar to them, since it is the one usually adopted in textbooks and handbooks, for the design, calibration and use of measurement instrumentation.

The application of the method is demonstrated by fully working out an uncertainty evaluation for an experimental test case, purposely designed and performed to outline common important issues, such as the use of repeated observations, the compensation of systematic effects and the inclusion of calibration data. The evaluation of expanded uncertainty by convolution of probability distributions is also addressed and the use of special software for its implementation is also demonstrated.

Stefan Marinca 

A Journey in the Search of the Ideal Monolithic Voltage References 

Stefan Marinca

The tutorial aims to address different issues related to design and characterization of IC silicon-based voltage references: short history, first and second order temperature errors, techniques to reduce the voltage noise, ultra-low power bias current generators and voltage references, resistorless voltage references.

Tutorial Summary

1. Basics on bipolar transistor temperature behavior. Bipolar transistor model parameters.
2. Bandgap type voltage reference. Short history: Hilbiber cell; Widlar cell, Kuijic cell; Brokaw cell; Variants of the Brokaw cell.
3. Architectures for Proportional To Absolute Temperature (PTAT) voltages.
4. Offset sensitivity of voltage references. Low offset voltage references.
5. Second order errors correction methods.
6. Very low temperature coefficient (TC) of the bandgap type voltage references.
7. Process independent voltage references. ADR35xx micropower standalone voltage reference.
8. Bias current generators, voltage references and temperature sensors without resistors.
9. Ultra-low noise voltage references and temperature sensors.
10. High precision temperature sensors based on stacked base-emitter voltage difference. ADR45xx ultra-low noise, high precision, standalone voltage reference family.
11. High precision temperature sensor with Early voltage compensation
12. Precision voltage reference based on Buried Zener Diodes.

Emiliano Sisinni

Mikael Gidlund

Aamir Mahmood

Wireless connectivity for the Industrial IoT

Emiliano Sisinni

Professor, Mid Sweden University; Department of Information and Communication Systems

Mikael Gidlund

Professor, University of Brescia; Department of Information Engineering

Aamir Mahmood

Assistant Professor, Mid Sweden University; Department of Information and Communication Systems

The tutorial will explain the field of application and the related research activities associated to wireless communication solutions for Industrial Internet of Things (IIoT) applications. The IIoT paradigm switch is mandatory for Industry 4.0 goal of improving overall industrial efficiency. The implementation of so called digital twin is only possible with the support of IIoT-like communication solutions. Wireless will play a major role, due to the intrinsic flexibility it offers.

The industrial wireless technology is not new and it has grown in recent times. In particular, two standard solutions have been proposed in the past purposely designed for process automation, i.e. WirelessHART and ISA100.11a. However, they are intended for process monitoring and control and do not fit very well with IIoT approach and the final goal of a flat automation pyramid.

By the way, in the consumer side some solutions emerged as leading technologies for wireless IoT; one for all, the Low Power Wide Area Networks – LPWANs. Currently, LoRaWAN is the most famous and diffused example of LPWAN.

One of the main intent of this tutorial is to highlight pros and cons of these solutions, especially highlighting possible limitations when used in the industrial domain, different from the original intended one (i.e. smart city scenarios)

The proposed tutorial is arranged in order to bring value to researchers, instrumentation engineers, automation professionals and influencers in the wireless automation scenario.

The tutorial will focus on these main topics:

• Basic concepts of wireless networks for industrial applications
• IoT and Industrial IoT
• Legacy wireless solutions for industrial applications: WirelessHART, ISA100.11a…
• The new LPWAN paradigm
• An example: the LoRaWAN solution and its possible applications in the industrial domain
• Modeling and performance evaluation: issues and challenges

Sebastian Yuri Catunda

Thermoresistive Sensors, Applications and Electrical Equivalence Principle

Sebastian Yuri Catunda

Thermoresistive sensors find several applications beyond temperature measurement. These include applications for measurement of fluid speed, incident radiation (solar, infrared and microwave radiation), AC power, gas detection, acceleration and gyroscopes. Sensors architectures, i.e. the analog front-end that provides excitation for generating the measurement signal, play an important role in the measurement system performance, like response time, linearity, sensitivity, power, among others. In architectures employing the electrical equivalence principle, the sensor operates near a constant temperature, in a feedback control configuration, where variations of the measurand are substituted by equivalent variations of the electrical power delivered to the sensor. Among several sensor architectures, those employing the electrical equivalence principle provide best response time and can mitigate a sensor nonlinear temperature-resistance relationship. Nevertheless, these architectures still present some shortcomings, which motivate research for improvements and for new architectures and techniques, evidencing the timeliness of the topic.

Sreeraman Rajan

Fereshteh Fakhar Firouzeh

Mohamed Abdelazez

From Compression to Recovery: An Overview of Compressive Sensing

Sreeraman Rajan, Fereshteh Fakhar Firouzeh, and Mohamed Abdelazez

The tutorial will explain the field of application and the related research activities associated to wireless communication solutions for Industrial Internet of Things (IIoT) applications. The IIoT paradigm switch is mandatory for Industry 4.0 goal of improving overall industrial efficiency. The implementation of so called digital twin is only possible with the support of IIoT-like communication solutions. Wireless will play a major role, due to the intrinsic flexibility it offers. Internet of Things (IoT) are ubiquitous and are expected to reach 18 billion device by the year 2022. An IoT device can perform a multitude of activities including providing assistance to the user through voice interactions. Over 7 billion voice assistants are anticipated to be available by the year 2022. Considering a typical sampling frequency of 48 kHz and a sample voice commands such as ’Hey, how is the weather today?’ spoken over two seconds, a voice assistant will generate 96KB. If the 8 billion devices available by the year 2023 are used once per day, a total of 768TB will be generated. Most of the voice assistants live on devices with low computational power and/or battery-powered; thereby, requiring the transmission of the data to a cloud for processing. The transmission of 768TB of data over cellular and wireless networks may lead to congestion and a decrease in the quality of the connection. Additionally, 60% of the energy in a battery-powered wireless device is used to transmit the data. Compression of the voice before transmission is, therefore, warranted to prevent network congestion and to preserve battery power. Compressive Sensing (CS) is a candidate technique that can prolong battery life by acquiring signals below the Nyquist rate and help reduce transmission bandwidth.

This tutorial will present CS as a two phase process: compression phase and the sparse recovery phase. Compression phase is presented as a “weak encryption” process. In the sparse recovery phase of CS, the sparse solution can be estimated by considering a variety of optimization techniques. In general, sparse estimation algorithms can be categorized into three classes: (1) convex relaxation, (2) non-convex methods, and (3) greedy algorithms.

In this tutorial, the aforementioned classes will be broadly discussed. Moreover, problems (e.g., small critical sparsity, low compression, and low quality of the recovered signal) of the existing algorithms will be addressed and new algorithms that can provide better recovery with high critical sparsity will be introduced. Techniques for improving the recovery will also be presented. As sparse recovery phase of CS can be computationally expensive and often done in the cloud, a method to handle security of the recovery process will also be discussed. This tutorial will also further explore the possibility of conducting detection and classification in the compressed domain without resorting to recovery. Compressed domain classification using machine learning and model-CS based will be presented.

Guglielmo Frigo 

Asja Derviskadic

Mario Paolone

Analysis of Broad-Band Signals in Reduced-Inertia Power Systems Using the Hilbert Transform

Guglielmo Frigo, Asja Derviskadic, and Mario Paolone

Modern and future power systems are at risk of largely reducing their rotating machines inertia. The consequence is that, during electromechanical transients triggered by contingencies, the transmission of electrical power may take place over a continuous and wide spectrum well beyond the sole fundamental component. In this evolving scenario, a rigorous modelling framework tailored for reduced-inertia grids is still missing. Indeed, traditional modelling approaches rely on the classical static or dynamic phasor representation derived from various algorithms all based on the use of the Fourier Transform (FT) applied to the signals of voltage and current waveforms. However, being based on a static signal model and a discrete and finite frequency resolution, the FT-based analysis may fail to accurately identify the signal parameters during non-stationary operating conditions.

The tutorial describes an alternative approach for modelling large power system electromechanical transients that goes beyond the phasor concept. The approach is inspired by the theory on analytic signals and is based on the Hilbert transform (HT). Thanks to its time-dependent formulation, the HT enables us to preserve unaltered the signal dynamics and, at the same time, extract the signal parameters for a concise and exhaustive representation. Then, it is shown how circuit laws can be solved with the HT that is able to reconstruct the electrical power transfer over the whole spectrum. These theoretical findings are supported by experimental evidence that compares FT- and HT-based analysis with respect to real-world power system operating conditions.

Daniele Fontanelli

Measurements Applications for Autonomous Systems

Daniele Fontanelli

Autonomous systems are nowadays having an undisputed pervasiveness in the modern society. Autonomous driving cars as well as applications of service robots (e.g. cleaning robots, companion robots, intelligent healthcare solutions, tour guided systems) are becoming more and more popular and a general acceptance is now developing around such systems in the modern societies. Nonetheless, one of the major problems in building such applications relies on the capability of autonomous systems to understand their surroundings and then plan proper counteractions. The most popular solutions, which are gaining more and more attention, rely on artificial intelligence and deep learning as a means to perceive the structured and complex natural environment. Nonetheless, besides the importance of such complex tools, classical concept of metrology, such as standard uncertainty, accuracy and precision, are still unavoidable for a clear and effective understanding of modern autonomous systems applications.

In this tutorial, some fundamental measurement concepts will be revised in light of the autonomous systems domain. In particular, we will cover the main concepts of the statistical approach to measurements that will then be applied to:

• Uncertainty analysis and synthesis for autonomous systems localisation
• Precision-based feedback for social robotics
• Distributed localisation

Pawel Niewczas 

Fiber-Optic Sensors and their Applications in Power and Energy Industries 

Pawel Niewczas 

Optical sensors and photonic devices have technically matured to the point that they are increasingly considered as alternatives for their electronic counterparts in numerous applications across the industry. In particular, the utilization of optical sensors has been considered for harsh, high-voltage or explosive environments where conventional transducers are difficult to deploy or where their operation is compromised by electromagnetic interference. Multi-point measurement along distributed assets is another application where fibre-optic sensors offer an advantage of a long reach and multiplexing.

This prospective tutorial will explain the motivation for research on fiber-optic sensors, highlight the basic theories underlying their operation, and present selected examples of R&D projects carried out within the Advanced Sensors Team in the Institute for Energy and Environment at the University of Strathclyde and within Synaptec – a young spin out company focussing on distributed photonic sensing for the energy sector.

The tutorial will highlight and detail specific examples of the measurement needs within the power and energy sectors and report on the novel approaches in fiber sensing to address these needs. In particular, it will cover such applications as distributed voltage and current measurement for power system metering, protection and control in the context of terrestrial and offshore energy transport infrastructure; structural health monitoring of wind turbine foundations; and measurement of the loss of loading within prestressing steel tendons used for reinforcing concrete pressure vessels and containment vessels in nuclear power stations. As the potential good solutions to these respective measurement needs, this tutorial will introduce such emerging technologies as the hybrid fiber Bragg grating (FBG) voltage and current sensors; and novel methods of fibre optic sensor packaging in metallic components for deployment in harsh industrial environments. The tutorial will present the most recent progress in these thematic areas. The goal will be to highlight great potential of optical sensors and to enrich recipients’ experience in instrumentation and measurement using alternative, non-electronic measurement methods.

Kamel Haddadi 

Microwave Microscopy for Advanced and Efficient Materials Analysis and Production 

Kamel Haddadi
 

The MMAMA project (Microwave Microscopy for Advanced and Efficient Materials Analysis and Production − www.mmama.eu) offers a nanoscale characterization platform for the European manufacturers of coatings, photovoltaic cells, and semi-conductor circuits. This project, launched on November 1, 2017, will last 3 years. It received a European funding of € 3.99 million, allocated by the Horizon 2020 research and innovation programme.

On one hand, Manufacturing industry offers a large range of organic and inorganic based materials addressing numerous applications. The quality and performance of the final manufactured products depend strongly on their chemical/electrical/optical/mechanical properties at nanoscale as well as their arrangements at macroscale (amorphous, partially isomorph, hybrid/composite, multi-layered).

On the other hand, microwave to mm-wave nondestructive testing and evaluation methods are well established for determining electrical properties of materials. A variety of methods including far to near field free-space, guided, resonant and scanning probe microscopy offers numerous solutions for Macro down to Nano scale characterization.

In this context, the objective of this tutorial is oriented towards RF to mm-wave techniques and related instruments dedicated to nondestructive evaluation applicable to wide range of emerging materials. This tutorial will afford the participant an extensive treatment of the field of microwave characterization, its foundation, theory, techniques and related instrumentations. Additionally, the tutorial will introduce the participants to the state-of-the-art as well as the state-of-the-practice. Finally, emerging and likely future trends in this field will be introduced. The discussion will be illustrated with several real-world examples. The Tutorial is intended primarily for young scientists and engineers who are interested in learning about this emerging field, but is also useful for individuals with a more advanced understanding of related concepts.

Erik Timpson 

Young Professionals Best Practices in a Variety of Measures. 

Erik Timpson

We need more young people to be interested in instrumentation and measurement. The hope is to partner with the current young professional representative again. So we can have a good turnout like in 2017 https://2017.imtc.ieee-ims.org/young-professionals-best-practices-variety-measures.html.

This tutorial is targeted for young professionals. It is intended to provide the best practices for a variety of traditional and professional measures, be interactive, and give tools for continued success. Traditional measurement best practices include electrical (voltage, current, impedance, etc.) and environmental (acceleration, temperature, humidity, pressure, etc.) parameters. Professional measures include career growth, depth and breadth of technical knowledge. As it is intended to be interactive, please come with questions and stories related to the title. Last, the tutorial will give an example of using the past instrumentation and measurement professionals (Nobel laureates) to inspire the future generation of professionals.

Riccardo Susini 

Trends in ADAS and Autonomous Vehicle Test. 

Riccardo Susini

National Instruments embedded control and test systems run the automation factories around the world; our measurement and test cell systems ensure fuel-efficient, aerodynamic, and safe in aerospace and transportation solutions; our measurement and control systems ran traditional energy systems and have quickly evolved to be embedded in the largest wind farm deployments to-date controlling and monitoring the turbine speed and performance. Now these “things” are all connected. This connected intelligence can lead to incredible macro impact, every device could be hooked up to the Cloud to make our lives better – more efficient energy utilization, load balancing of resources, safer transportation systems and infrastructure and much more.
Autonomous vehicles will change the way we view transportation and even live our lives. The obvious main goal is to increase safety and reduce traffic deaths, but reducing emissions and providing better mobility solutions are also benefits to be realized. To accomplish this, new vehicles are integrating technology that helps them provide advanced driver assistance systems (ADAS) functionality and will eventually lead to fully autonomous operation. These technologies like radar, camera, and RF communication will work together with a sensor fusion approach to give the vehicle a more complete view of the world around it.

Autonomous driving and advanced driver assistance systems (ADAS) are drastically increasing system complexity: new radar, camera, lidar, and GNSS sensors all together to enable these new automotive technologies. This rapid change requires flexible test systems to deploy products quickly and safely. Because of the importance of data synchronization, it is necessary to ensure that your embedded software test environment is capable of generating both radar target information as well as video classification information deterministically and within the window that is acceptable for ADAS ECU operation. While today’s ECU’s have relatively loose tolerances, we can expect that the performance and jitter associated with this data will continue to shrink over time. The NI PXI platform is the only platform capable of generating both of these data streams in one system, while also being capable of running a real-time operating system for deterministic simulation of the world around the safety system.

Stephanie E. Trpkov

Frane Sesnic

Developing a sustainable technology business

Frane Sesnic and Stephanie E. Trphkov

The tutorial aims to provide participants with tools that would help them visualise the end-to-end process of developing a sustainable technology business. In this time of digital disruption, rising customer expectations and industrial transformation, closer linkages between theory and market applications help in creating opportunities and enhancing competitiveness.

The tutorial will present tools to accelerate product development that increase the speed of innovation of products and services and help companies navigate disruption. It would show the participants how to shorten the concept-to-product timeframe and effectively sell the story of the idea to users (customers) and investors. Activities that support formation of agile business models and fast track organic growth, will be carried out under the following sessions:

1. Taking advantage of available innovation ecosystems
2. Design thinking and product development
3. Business modelling 
4. Market development, investments & financing 

Outline of the tutorial content and tentative schedule

1. Taking advantage of available innovation ecosystems

This first session led by Frane, will take a macro perspective by examining the role of innovation ecosystems and ways to make them sustainable. It will present a blueprint for designing an ecosystem with global impact, and highlight the roles of major stakeholders such as government, business sector, academia, etc., while looking at elements that create lasting impact, influence of market size, country and environment risks, talent pool, as well as coordinating multi helix models.

2. Design thinking and product development

The second session led by Stephanie, will group participants into teams of around 5, they will be introduced to design thinking methodology and learn the process of lean product development through a joint problem solving task. At the end of the session, they will be divided into a group of six where they will role-play a pitching session for certain products.

3. Business modelling

The third session led by Stephanie, will be another hands-on session where participants will re-join their initial teams and will be guided through the Business Model Canvas, for a hypothetical or real product. They will be exposed to the principles of effectuation and guided towards developing clear linkages between creating value, managing costs and ensuring stable revenue streams.

4. Market development, investments & financing 

The final session led by Frane, will take a look at the company journey from idea to maturity stage. It would outline main challenges for founders and teams, market development challenges, crowd sourcing and securing strategically beneficial partnerships. On the investment and financing perspective, it would examine non-traditional financing opportunities such as crowd-financing, investment options, innovative procurement models, and ways to leverage financial instruments.

Planned format of the tutorial would be a combination of lectures and hands-on sessions.