The terms denote technology areas that are part of the CPS technology suite or that are impacted by CPS requirements.
Event
WCET 2018
18th International Workshop on Worst-Case Execution Time Analysis (WCET 2018)
co-located with the Euromicro Conference on Real-Time Systems (ECRTS 2018)
Announcement
CALL FOR PROPOSALS: International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS 2018)
CALL FOR PROPOSALS
International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS 2018)
September 30 – October 5, 2018, Torino, Italy
Event
EMSOFT 2018
International Conference on Embedded Software (EMSOFT 2018)
The ACM SIGBED International Conference on Embedded Software (EMSOFT) brings together researchers and developers from academia, industry, and government to advance the science, engineering, and technology of embedded software development.
Event
ASPLOS 2018
The 23rd ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2018)
March 24th – March 28th, Williamsburg, VA, USA
ASPLOS is the premier forum for multidisciplinary systems research spanning computer architecture and hardware, programming languages and compilers, operating systems and networking. The ASPLOS 2018 will be held in Williamsburg, Virginia, a town that combines a rich slice of American Colonial and Revolutionary history with a modern college atmosphere.
Event
RAW 2018
The 25th Anniversary of Reconfigurable Architectures Workshop (RAW 2018)
The 25th Reconfigurable Architectures Workshop (RAW 2018) will be held in Vancouver, British Columbia CANADA in May 2018. RAW 2018 is associated with the 32nd Annual IEEE International Parallel & Distributed Processing Symposium (IEEE IPDPS 2018) and is sponsored by the IEEE Computer Society and the Technical Committee on Parallel Processing.
Event
SCOPES 2018
21st International Workshop on Software and Compilers for Embedded Systems (SCOPES 2018)
A next edition of the workshop on Software and Compilers for Embedded Systems (SCOPES) will be organized in 2017. The workshop will feature a combination of research papers and research presentations (details see below). The papers and presentation abstracts will also be published in the ACM digital library. The workshop is held in cooperation with ACM SIGBED and EDAA.
The Sensors in a Shoebox project focuses on empowering urban citizens with the tools and methods necessary to observe and analyze the physical, social, and natural systems that affect their communities for improved community-based decision making. The project creates an affordable and ruggedized sensor kit that consists of solar-powered wireless sensors with Internet connectivity that can be distributed to communities to sense environmental parameters, vibrations, motion, among other parameters. Data is transmitted from community-deployed sensor kits to the cloud where sensor data is stored and managed. The community directly accesses their data from a web portal offering a suite of user-friendly analytical tools that citizens could use to extract community-relevant information from raw sensor data. Some envisioned community uses of the Sensors in a Shoebox platform include but not limited to: measuring neighborhood air quality, tracking the usage of public spaces, and observing residents' mobility choices (walking, biking, and motorized transport).
This project will provide a scientific and technological foundation to the extension of cyber-physical systems to explicitly include humans. So called cyber-physical-social systems, these human-in-the-loop systems have the potential to transform a variety of commercial application including those in transportation, building energy management, among others. The project engages the communities of Detroit, a city beginning to go through transformation after decades of dramatic population declines. Specifically, the project recruits middle- and high school students from Detroit public charter schools to serve at the front lines of the system design and deployment. In doing so, the team will closely study and rigorously assess the experiences of urban youth using the system. In particular, advancement of STEM knowledge and youth's notions of being connected citizens will be qualitatively and quantitatively assessed.
Off
University of Michigan, Ann Arbor
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National Science Foundation
Elizabeth Moje
The goal of this project is to investigate a low-cost and energy-efficient hardware and software system to close the loop between processing of sensor data, semantically high-level detection and trajectory generation in real-time. To safely integrate Unmanned Aerial Vehicles into national airspace, there is an urgent need to develop onboard sense-and-avoid capability. While deep neural networks (DNNs) have significantly improved the accuracy of object detection and decision making, they have prohibitively high complexity to be implemented on small UAVs. Moreover, existing UAV flight control approaches ignore the nonlinearities of UAVs and do not provide trajectory assurance.
The research thrusts of this project are: (i) FPGA implementation of DNNs: both fully connected and convolutional layers of deep (convolutional) neural networks will be trained using (block-)circulant matrix and implemented using custom designed universal Fast Fourier Transform kernels on FPGA. This research thrust will enable efficient implementation of DNNs, reducing memory and computation complexity from O(N2) to O(N) and O(NlogN), respectively; (ii) autonomous detection and perception for onboard sense-and-avoid: existing regional detection neural networks will be extended to work with images taken from different angles, and multi-modal sensor inputs; (iii) real-time waypoint and trajectory generation - an integrated trajectory generation and feedback control scheme for steering under-actuated vehicles through desired waypoints in 3D space will be developed. For efficient implementation and hardware reuse, both detection and control problems will be formulated and solved using DNNs with (block-)circulant weight matrix. Deep reinforcement learning models will be investigated for waypoint generation and to assign artificial potential around the obstacles to guarantee a safe distance. The fundamental research results will enable onboard computing, real-time detection and control, which are cornerstones of autonomous and next-generation UAVs.
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Syracuse University
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National Science Foundation
Amit Sanyal
Yanzhi Wang
Jian Tang
Senem Velipasalar
This proposal is for research on the Mobile Automated Rovers Fly-By (MARS-FLY) for Bridge Network Resiliency. Bridges are often in remote locations and the cost of installing electricity and a data acquisition system in hundreds of thousands of bridges is prohibitive. The MARS-FLY project will develop a cyber-physical system (CPS) designed to monitor the health of highway bridges, control the loads imposed on bridges by heavy trucks, and provide visual inspectors with quantitative information for data-driven bridge health assessment requiring no electricity and a minimum of data acquisition electronics on site. For fly-by monitoring, GPS-controlled auto-piloted drones will periodically carry data acquisition electronics to the bridge and download the data from the sensors at a close range. Larger Imaging drones carrying infrared (IR) cameras will be used to detect detail damages like concrete delamination.
The research objectives will be accomplished first, by wireless recharging of remote sensor motes by drone to enhance the sensor operational lifetime whereas wireless recharging of drone battery will extend the operational efficiency, payload, and drone range. The novel multi-coil wireless powering approach will provide an investigation of an engineered material i.e. metamaterial with the resonant link to enhance the power level and link distance, otherwise unachievable. Next, by a major scientific breakthrough in the utilization of small quantities of low quality sensor data and IR images to determine damage information at all levels: detection of a change in behavior, location, and magnitude; streamlining of reliability analysis to incorporate the new information of damage into the bridge's reliability index based on combined numerical and probabilistic approaches such as Ensemble Empirical Mode Decomposition with the Hilbert Transform; and finally detection of nonlinearities in the signals in a Bayesian Updating framework. Moreover, an instrumented drive-by vehicle will complement damage detection on the bridge. A Bayesian updating framework will be used to update the probability distribution for bridge condition, given the measurements. Image processing of the infrared images to distinguish between the environmental effects and the true bridge deterioration (e.g. delamination in concrete) will be used to develop a better method of site-specific and environment-specific calibration.
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University of Alabama at Birmingham
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National Science Foundation
Mohammad Haider
Event
IFIP 2018
First cross-domain IFIP Internet of Things (IoT) Conference
IoT is hot. Experts and organizations are addressing the topic in policy statements, papers and conferences. There are many aspects to be looked at when talking about IoT. Earlier developments were quite focused on the lower level aspects such as interfacing, communication protocols and standards, base platforms, energy efficiency and energy harvesting, smart devices and smart sensors, etc.