The terms denote engineering domains that have high CPS content.
Event
HumanSys 2017
1st International Workshop on Human-centered Sensing, Networking, and Systems (HumanSys 2017) Co-located with ACM SenSys 2017
Submitted by Anonymous on July 24th, 2017
Project
CPS/Synergy/Collaborative Research: Safe and Efficient Cyber-Physical Operation System for Construction Equipment
Equipment operation represents one of the most dangerous tasks on a construction sites and accidents related to such operation often result in death and property damage on the construction site and the surrounding area. Such accidents can also cause considerable delays and disruption, and negatively impact the efficiency of operations. This award will conduct research to improve the safety and efficiency of cranes by integrating advances in robotics, computer vision, and construction management. It will create tools for quick and easy planning of crane operations and incorporate them into a safe and efficient system that can monitor a crane's environment and provide control feedback to the crane and the operator. Resulting gains in safety and efficiency will reduce fatal and non-fatal crane accidents. Partnerships with industry will also ensure that these advances have a positive impact on construction practice, and can be extended broadly to smart infrastructure, intelligent manufacturing, surveillance, traffic monitoring, and other application areas. The research will involve undergraduates and includes outreach to K-12 students. The work is driven by the hypothesis that the monitoring and control of cranes can be performed autonomously using robotics and computer vision algorithms, and that detailed and continuous monitoring and control feedback can lead to improved planning and simulation of equipment operations. It will particularly focus on developing methods for (a) planning construction operations while accounting for safety hazards through simulation; (b) estimating and providing analytics on the state of the equipment; (c) monitoring equipment surrounding the crane operating environment, including detection of safety hazards, and proximity analysis to dynamic resources including materials, equipment, and workers; (d) controlling crane stability in real-time; and (e) providing feedback to the user and equipment operators in a "transparent cockpit" using visual and haptic cues. It will address the underlying research challenges by improving the efficiency and reliability of planning through failure effects analysis and creating methods for contact state estimation and equilibrium analysis; improving monitoring through model-driven and real-time 3D reconstruction techniques, context-driven object recognition, and forecasting motion trajectories of objects; enhancing reliability of control through dynamic crane models, measures of instability, and algorithms for finding optimal controls; and, finally, improving efficiency of feedback loops through methods for providing visual and haptic cues.
1544999
Off
University of Illinois at Urbana-Champaign
Mani Golparvar-Fard
-
National Science Foundation
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1544999&HistoricalAwards=false
Mani Golparvar-Fard Submitted by Mani Golparvar-Fard on July 21st, 2017
Announcement
ACM Workshop: SafeThings 2017 Call for Papers (Co-located with SenSys)


Dear Colleagues,

Please see below the Call for Papers for ACM SafeThings 2017. We enthusiastically look forward to your submissions on advancements in the safety of the Internet of Things ecosystem.  

1st ACM Workshop on the Internet of Safe Things (SafeThings 2017)
https://www.safethings.info/
November 5, 2017 at TU Delft, The Netherlands
Co-located with ACM SenSys 2017

As the traditionally segregated systems are brought online for next generation connected applications, we have an opportunity to significantly improve the safety of legacy systems. For instance, insights from data across systems can be exploited to reduce accidents, improve air quality and support disaster events. Cyber-physical systems (CPS) also bring new risks that arise due to the unexpected interaction between systems. These safety risks arise because of information that distracts users while driving, software errors in medical devices, corner cases in data-driven control, compromised sensors in drones or conflicts in societal policies.

Accordingly, the Internet of Safe Things workshop (or SafeThings, for brevity) seeks to bring researchers and practitioners that are actively exploring system design, modeling, verification, authentication approaches to provide safety guarantees in the Internet of Things (IoT). The workshop welcomes contributions that integrate hardware and software systems provided by disparate vendors, particularly those that have humans in the loop. As safety is inherently linked with the security and privacy, we also seek contributions in security and privacy that address safety concerns. With the SafeThings workshop, we seek to develop a community that systematically dissects the vulnerabilities and risks exposed by these emerging CPSes, and create tools, algorithms, frameworks and systems that help in the development of safe systems.

SafeThings workshop covers safety topics as it relates to an individual’s health (physical, mental), the society (air pollution, toxicity, disaster events), or the environment (species preservation, global warming, oil spills). The workshop considers safety from a human perspective, and thus, does not include topics such as thread safety or memory safety in its scope.

Our workshop will cover, but not limit itself to, the following subject categories:
- Verification of safety in IoT platforms
- Privacy preserving data sharing and analysis
- Compliance with legal, health and environmental policies
- Integration of hardware and software systems
- Conflict resolution between IoT applications
- Safety in human-in-the-loop systems
- Support for IoT development - debugging tools, emulators, testbeds
- Usable security and privacy for IoT platforms
- Resiliency against attacks and faults
- Secure connectivity in IoT

Our workshop will cover, but not limit itself to, the following domains: autonomous vehicles and transportation infrastructure; medical CPS and public health; smart buildings, smart grid and smart cities.

Submission Types:
We solicit two types of original submissions:
  * Regular papers for oral presentation (6 pages)
  * Technical posters and demos (1 page)

Important Dates:
Abstract Submission Deadline: July 23, 2017 (11.59 PM AoE)
Paper Submission Deadline: July 30, 2017 (11.59 PM AoE)
Poster and demo submission deadline: July 30, 2017 (11.59 PM AoE)
Acceptance Notification: August 21, 2017
Camera-ready versions: September 10, 2017

Organizing Committee:

General Chairs:
Patrick Tague (Carnegie Mellon University)
Bharathan Balaji (University of California, Los Angeles)

Program Chairs:
Mani Srivastava (University of California, Los Angeles)
Yuan Tian (Carnegie Mellon University)

Poster and Demo Chair:
Houssam Abbas (University of Pennsylvania)
Publication Chair:
Rasit Eskicioglu (University of Manitoba)

SenSys Workshop Chair:
Xiaofan (Fred) Jiang (Columbia University, USA)
Technical Program Committee:
Blase Ur (University of Chicago)
Xiao Feng Wang (Indiana Bloomington)
Xinyu Xing (Penn State)
Paulo Tabuada (University of California, Los Angeles)
Supriyo Chakraborty (IBM Research)
Muhammad Naveed (University of Southern California)
Yasser Shoukry (University of California, Berkeley)
Yuvraj Agarwal (Carnegie Mellon University)
Rajesh Gupta (University of California, San Diego)
Brad Campbell (University of Virginia)
John Stankovic (University of Virginia)
Madhur Behl (University of Virginia)
Houssam Abbas (University of Pennsylvania)
Insup Lee (University of Pennsylvania)
João Vilela (University of Coimbra)
Eric Wustrow (Colorado Boulder)
Richard Han (Colorado Boulder)
Lu Feng (University of Virginia)
Earlence Fernandes (University of Michigan)
Falko Dressler (Paderborn University)
Jie Liu (Microsoft Research)
Kay Roemer (TU Graz)
Nic Lane (University College London)
Fang-Jing Wu (NEC Lab)
Jyotrimoy Deshmukh (Toyota)
Saman Zonouz (Rutgers University)
Haixin Duan (Tsinghua University)
Yutaka Arakawa (Nara Institute of Science and Technology)
Ingrid Verbauwhede (KU Leuven)
Stefano Zanero (Politecnico di Milano)
Thorsten Holz (Ruhr University Bochum)
Amir Rahmati (University of Michigan)
Cong Zheng  (Palo Alto Networks)
Chenguang Shen (Facebook)
​Shaunak Mishra (Yahoo Research)

Steering Committee:
John Stankovic (University of Virginia)
Lorrie Faith Cranor (Carnegie Mellon University)
Srdjan Capkun (ETH Zurich)
Rupak Majumdar (Max Planck Institute for Software Systems)

General Announcement
Not in Slideshow
Submitted by Bharathan Balaji on July 18th, 2017
Project
CPS:TTP Option: Synergy: Collaborative Research: Internet of Self-powered Sensors - Towards a Scalable Long-term Condition-based Monitoring and Maintenance of Civil Infrastructure
This research investigates a cyber-physical framework for scalable, long-term monitoring and maintenance of civil infrastructures. With growth of the world economy and its population, there has been an ever increasing dependency on larger and more complex networks of civil infrastructure as evident in the billions of dollars spent by the federal, state and local governments to either upgrade or repair transportation systems or utilities. Despite these large expenditures, the nation continues to suffer staggering consequences from infrastructural decay. Therefore, paramount to the concept of a smart city of the future is the concept of smart civil infrastructure that can self-monitor itself to predict any impending failures and in the cases of extreme events (e.g. earthquakes) identify portions that would require immediate repair, and prioritize areas for emergency response. A goal of this research project is to make significant progress towards this grand vision by investigating a framework of infrastructural Internet-of-Things (i-IoT) using a network of self-powered, embedded health monitoring sensors. The collaborative and interdisciplinary nature of this research would provide opportunities for unique outreach programs involving undergraduate and graduate students in technical areas, e.g., sensors, IoTs and structural health monitoring. The project would also provide avenues for disseminating the results of this research to stakeholders in the state governments and for translating the results of the research into field deployable prototypes. This research addresses different elements of the proposed i-IoT framework by bringing together expertise from three universities in the area of self-powered sensors, energy scavenging processors, structural health monitoring and earthquake engineering. At the fundamental level, the project involves investigating self-powered sensors that will require zero maintenance and can continuously operate over the useful lifespan of the structure without experiencing any downtime. The challenge in this regard is that sensors need to occupy a small enough volume such that an array of these devices could be easily embedded and can provide accurate spatial resolution in structural imaging. This research is also investigates techniques that would enable real time wireless collection of data from an array of self-powered sensors embedded inside a structure, without taking the structure out-of-service. The methods to be explored involve combining the physics of energy scavenging, transduction, rectification and logic computation to improve the system's energy-efficiency and reduce the system latency. At the algorithmic level the project explores novel structural failure prediction and structural forensic algorithms based on historical data collected from self-powered sensors embedded at different spatial locations. This includes kernel algorithms that can exploit the data to quickly identify the most vulnerable part of a structure after a man-made or a natural crisis (for example an earthquake). Finally, the technology translation plan for this research is to validate the proposed i-IoT framework in real-world deployment, which includes buildings, multi-span bridges and highways.
1646380
Off
Washington University in St. Louis
Shantanu Chakrabartty
-
National Science Foundation
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1646380&HistoricalAwards=false
Xuan Zhang
Submitted by Shantanu Chakrabartty on July 12th, 2017
Project
CPS: Synergy: Collaborative Research: Towards Dependable Self-Powered Things for the IoT
Scaling the Internet of Things (IoT) to billions and possibly trillions of "things" requires transformative advances in the science, technology, and engineering of cyber-physical systems (CPS), with none more pressing or challenging than the power problem. Consider that if every device in a 1 trillion IoT network had a battery that lasted for a full five years, over 500 million batteries would need to be changed every day. Clearly, a battery-powered IoT is not feasible at this scale due to both human resource logistics and environmental concerns. There is a need for a battery-less approach that dependably meets functionality requirements using energy harvested from the physical world. This project brings together experts in materials, devices, circuits, and systems to pursue a holistic approach to self-powered wireless devices deployed in real-world environments and IoT systems and applications. In addition, educational and outreach activities will help develop the workforce for this relatively new field with the holistic, materials-to-systems perspective that will be necessary to lead innovation in this space.A critical challenge that this project addresses is that both optimal device operation and energy harvester efficiency are heavily dependent on physical world dynamics, and thus, self-powered devices that are statically configured or that just respond to instantaneous conditions are unlikely to provide the dependability required for many IoT systems and applications. To address this fundamental and critically enabling challenge, data collections will be performed to study the physical world dynamics that impact device operation and harvester efficiency, such as ambient conditions, electromagnetic interference, and human behavior. This scientific study will lead to the development of dynamic models that will, in turn, be used to develop algorithms to dynamically configure devices and harvesters based not only on past and current conditions but also on predictions of future conditions. These algorithms will then be used to dynamically configure technological innovations in ultra-low power device operation and ultra-high efficiency energy harvesting to engineer and operate dependable self-powered things for the IoT.
1646399
Off
Pennsylvania State University
Susan Troiler-McKinstry
-
National Science Foundation
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1646399&HistoricalAwards=false
Submitted by Susan Troiler-McKinstry on July 12th, 2017
Event
CyPhy'17
Seventh Workshop on Design, Modeling and Evaluation of Cyber Physical Systems (CyPhy'17) Held in conjunction with ESWEEK 2017 
Submitted by Anonymous on July 11th, 2017
Event
IUI 2018
ACM IUI 2018 is the 23rd annual meeting of the intelligent interfaces community and serves as a premier international forum for reporting outstanding research and development on intelligent user interfaces. ACM IUI is where the Human-Computer Interaction (HCI) community meets the Artificial Intelligence (AI) community. We are also very interested in contributions from related fields, such as psychology, behavioral science, cognitive science, computer graphics, design, the arts, etc. 
Submitted by Anonymous on July 11th, 2017
Event
PACRIM '17
2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing Established in 1987, the Pacific Rim Conference on Communications, Computers and Signal Processing (PacRim) is the premier IEEE biennial event in the Pacific Northwest. In 2017, it will be held at the Engineering Computer Science building at the University of Victoria, Victoria, B.C., Canada, from August 21 to August 23.
Submitted by Anonymous on July 11th, 2017
Event
SASO 2017
11th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO)  SASO is part of FAS*, a common umbrella for two closely related but independent conferences (SASO and ICCAC) with shared events including workshops, tutorials, doctoral symposia, etc.
Submitted by Anonymous on July 11th, 2017
Project
EAGER: Collaborative Research: Empowering Smart Energy Communities: Connecting Buildings, People, and Power Grids
By 2050, 70% of the world's population is projected to live and work in cities, with buildings as major constituents. Buildings' energy consumption contributes to more than 70% of electricity use, with people spending more than 90% of their time in buildings. Future cities with innovative, optimized building designs and operations have the potential to play a pivotal role in reducing energy consumption, curbing greenhouse gas emissions, and maintaining stable electric-grid operations. Buildings are physically connected to the electric power grid, thus it would be beneficial to understand the coupling of decisions and operations of the two. However, at a community level, there is no holistic framework that buildings and power grids can simultaneously utilize to optimize their performance. The challenge related to establishing such a framework is that building control systems are neither connected to, nor integrated with the power grid, and consequently a unified, global optimal energy control strategy at a smart community level cannot be achieved. Hence, the fundamental knowledge gaps are (a) the lack of a holistic, multi-time scale mathematical framework that couples the decisions of buildings stakeholders and grid stakeholders, and (b) the lack of a computationally-tractable solution methodology amenable to implementation on a large number of connected power grid-nodes and buildings. In this project, a novel mathematical framework that fills the aforementioned knowledge gaps will be investigated, and the following hypothesis will be tested: Connected buildings, people, and grids will achieve significant energy savings and stable operation within a smart city. The envisioned smart city framework will furnish individual buildings and power grid devices with custom demand response signals. The hypothesis will be tested against classical demand response (DR) strategies where (i) the integration of building and power-grid dynamics is lacking and (ii) the DR schemes that buildings implement are independent and individual. By engaging in efficient, decentralized community-scale optimization, energy savings will be demonstrated for participating buildings and enhanced stable operation for the grid are projected, hence empowering smart energy communities. To ensure the potential for broad adoption of the proposed framework, this project will be regularly informed with inputs and feedback from Southern California Edison (SCE). In order to test the hypothesis, the following research products will be developed: (1) An innovative method to model a cluster of buildings--with people's behavior embedded in the cluster's dynamics--and their controls so that they can be integrated with grid operation and services; (2) a novel optimization framework to solve complex control problems for large-scale coupled systems; and (3) a methodology to assess the impacts of connected buildings in terms of (a) the grid's operational stability and safety and (b) buildings' optimized energy consumption. To test the proposed framework, a large-scale simulation of a distribution primary feeder with over 1000 buildings will be conducted within SCE?s Johanna and Santiago substations in Central Orange County.
1637258
Off
University of California-Riverside
David Corman
-
National Science Foundation
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1637258&HistoricalAwards=false
Nanpeng Yu
Submitted by David Corman on June 19th, 2017
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