Nonlinear Sensing: From Materials to Systems
Organizer: Dr. Bahraad Bahreyni (Simon Fraser University, Canada)
Sensors for the most part are expected to provide a linear response to their stimuli. However, significant performance improvements are possible if sensors provide a nonlinear response (e.g., logarithmic sensors) or when they are designed to be operated nonlinearly. In many cases, the sensitivity of a device to the input increases significantly as the device approaches its nonlinear operating region. Nonlinearities at micro- and nano-scales have been utilized to improve the stability of oscillators or sensitivity of sensors. Often, these nonlinearities are induced by pushing the device to the edge of the nonlinearity from transduction, mechanical, or material origins and monitoring its response to the stimulus as perturbations. On the other hand, most statistical learning (i.e., machine learning) algorithms rely on some sort of nonlinear operation on signals for transformation of data from one domain onto another to reveal high-order interdependencies between variables or to compact the ranges. Increasingly, the nonlinear response of devices at different scales is employed as the required nonlinear mapping technique using physical devices or even in-materio.
The intention of this special session is to invite leading research on enhancing the performance of materials, sensors, and sensor systems by employing inherent or designed nonlinearities.
Embedded Artificial Intelligent (AI) for Smart Sensing and IoT applications
Organizers: Sebastian Bader (Mid Sweden University, Sweden), Michele Magno (ETH Zurich, Switzerland)
The number of sensing devices drastically grows and has already exceeded the number of people on earth. We consider a 'smart sensor' as a tiny embedded system with sensing, processing, and communication capabilities which can be accessed 24/7. However, very few examples of 'smart things' are really intelligent. Blending of learning algorithms and constrained electronic devices happening today will make IoT devices even smarter by enabling cognitive functions. Although promising early results are appearing across many domains, e.g., hardware, machine learning, constrained computing platforms, the research in embedded Artificial Intelligence (AI) is still in its infancy. Progress in this area opens up a wide vista for numerous applications, including wearable computing, condition monitoring, smart security, smart home, and cities.
-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, comparisons of hardware and software 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
Flexible Sensors: Development and Applications
Organizers: Bruno Ando (Univeristy of Catania, Italy), Salvatore Graziani (University of Catania, Italy), Vincenzo Marletta (University of Catania, Italy)
Recently, alternative realizations of low-cost devices and sensors have emerged; of these, flexible structures underpinned by plastic or polymeric substrates show great promise since they are compatible with direct printing technologies. Direct printing technologies have been intensively studied because they represent a fast and low cost strategy that could replace, in specific contexts, traditional fabrication techniques (e.g. sputtering and lithography) of devices and sensors both in mass production for industries, and in the rapid prototyping for research and academic laboratories. Consequently, there is an extremely vivid interest on this subject both in the scientific and in the industrial community. Among direct printing technologies, inkjet printing seems to be a very promising solution for the rapid prototyping of low cost sensors. In spite of the numerous results available, there is still a large need for further research efforts and for novel solutions. We invite therefore original research papers on this subject with the goal to contribute to this area through a vibrant arena where novel ideas on converging subjects for the general topic of Flexible Sensors will be confronted, exchanged and set up a help in setting.
- Overview of state of the art on "Flexible Sensors"
- Development of novel flexible sensors
- Process and technologies for flexible sensors
- Rapid prototyping and fast printing of flexible sensors
- Modeling of flexible sensors
- Applications of flexible sensors