The objective of this research is to design a semi-automated, efficient, and secure emergency response system to reduce the time it takes emergency vehicles to reach their destinations, while increasing the safety of non-emergency vehicles and emergency vehicles alike. Providing route and maneuver guidance to emergency vehicles and non-emergency vehicles will make emergency travel safer and enable police and other first responders to reach and transport those in need, in less time. This should reduce the number of crashes involving emergency vehicles and associated litigation costs while improving medical outcomes, reducing property damage, and instilling greater public confidence in emergency services. At the same time, non-emergency vehicles will also be offered increased safety and, with the reduction of long delays attributed to emergency vehicles, experience reduced incident-related travel time, which will increase productivity and quality of life for drivers. Incorporating connected vehicles into the emergency response system will also provide synergistic opportunities for non-emergency vehicles, including live updates on accident sites, areas to avoid, and information on emergency routes that can be incorporated into navigation software so drivers can avoid potential delays. While the proposed system will naturally advance the quality of transportation in smart cities, it will also provide a platform for future techniques to build upon. For example, the proposed system could be connected with emergency care facilities to balance the load of emergency patients at hospitals, and act as a catalyst toward the realization of a fully-automated emergency response system. New courses and course modules will be developed to recruit and better prepare a future workforce that is well versed in multi-disciplinary collaborations. Video demos and a testbed will be used to showcase the research to the public.
The key research component will be the design of an emergency response system that (1) dynamically determines EV routes, (2) coordinates actions by non-emergency vehicles using connected vehicle technology to efficiently and effectively clear paths for emergency vehicles, (3) is able to adapt to uncertain traffic and network conditions, and (4) is difficult to abuse or compromise. The project will result in (1) algorithms that dynamically select EV routes based on uncertain or limited traffic data, (2) emergency protocols that exploit connected vehicle technology to facilitate emergency vehicles maneuvers, (3) an automation module to assist with decision making and maneuvers, and (4) an infrastructure and vehicle hardening framework that prevents cyber abuse. Experiments will be performed on a testbed and a real test track to validate the proposed research.
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Virginia Polytechnic Institute and State University
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National Science Foundation
Submitted by Tam Chantem on September 11th, 2017
This Frontier award supports the SONYC project, a smart cities initiative focused on developing a cyber-physical system (CPS) for the monitoring, analysis and mitigation of urban noise pollution. Noise pollution is one of the topmost quality of life issues for urban residents in the U.S. with proven effects on health, education, the economy, and the environment. Yet, most cities lack the resources for continuously monitoring noise and understanding the contribution of individual sources, the tools to analyze patterns of noise pollution at city-scale, and the means to empower city agencies to take effective, data-driven action for noise mitigation. The SONYC project advances novel technological and socio-technical solutions that help address these needs.
SONYC includes a distributed network of both sensors and people for large-scale noise monitoring. The sensors use low-cost, low-power technology, and cutting-edge machine listening techniques, to produce calibrated acoustic measurements and recognizing individual sound sources in real time. Citizen science methods are used to help urban residents connect to city agencies and each other, understand their noise footprint, and facilitate reporting and self-regulation. Crucially, SONYC utilizes big data solutions to analyze, retrieve and visualize information from sensors and citizens, creating a comprehensive acoustic model of the city that can be used to identify significant patterns of noise pollution. This data can in turn be used to drive the strategic application of noise code enforcement by city agencies, in a way that optimally reduces noise pollution. The entire system, integrating cyber, physical and social infrastructure, forms a closed loop of continuous sensing, analysis and actuation on the environment.
SONYC is an interdisciplinary collaboration between researchers at New York University and Ohio State University. It provides multiple educational opportunities to students at all levels, including an outreach initiative for K-12 STEM education. The project uses New York City as its focal point, involving partnerships with the city's Department of Environmental Protection, Department of Health and Mental Hygiene, the business improvement district of Lower Manhattan, and ARUP, one of the world's leaders in environmental acoustics. SONYC is an innovative and high-impact application of cyber-physical systems to the realm of smart cities, and potentially a catalyst for new CPS research at the intersection of engineering, data science and the social sciences. It provides a blueprint for the mitigation of noise pollution that can be applied to cities in the US and abroad, potentially affecting the quality of life of millions of people.
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New York University
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National Science Foundation
Claudio Silva
Roger DuBois
Juan Bello
Submitted by Anish Arora on May 26th, 2017
Event
HONET-ICT 2017
14th HONET-ICT International Conference "Smart Cities: Improving Quality of Life-Using ICT & IoT"
Scope:
Submitted by Anonymous on May 8th, 2017
Situational Awareness provides a user centric approach to security and privacy. The human factor is often recognised as the weakest link in security, therefore situational perception and risk awareness play a leading role in the adoption and implementation of security mechanisms. In this study we assess the understanding of security and privacy of users in possession of wearable devices. The findings demonstrate privacy complacency, as the majority of users trust the application and the wearable device manufacturer.
Submitted by xavier bellekens on November 17th, 2016
Motivated by the fact that the 2014 Ebola outbreak is the largest in history and there is a pressing need to understand how to improve delivery of care with the right technological interventions at the right place, this Rapid Response Research is aimed at realizing a human-in-the-loop medical cyber-physical system (CPS) for monitoring patients, insuring compliance with relevant safety protocols, and collecting data for advancing multidisciplinary research on infectious disease control. The ultimate goal is to enhance safety of Ebola workers by minimizing their contact with potentially contaminated surfaces and materials through integration of methods and technologies to realize smart and connected treatment clinics. This project could impact the response to infectious disease outbreaks by augmenting existing treatment clinics with cost-effective, modular, reconfigurable and
open-design CPS technologies. The project will train a new cadre of engineering students, researchers and innovators to be
sensitive to societal needs and national priorities by involving K-Gray, undergraduate and graduate students in all aspects of the project, especially at the co-ideation and co-design stages. The project will bring together a multidisciplinary team of engineers, scientists, technologists, medical experts, and humanitarian aid workers to develop holistic solutions to infectious disease control. The broader impacts also include operational cost savings in treatment clinics by reducing the need and use of the personal protective equipment and preserve resources such as water by reducing consumption.
In order to prevent, detect and respond to current Ebola outbreak and future similar infectious disease outbreaks, this research plan has the following interconnected aims: (1) contribute new knowledge, methods, and tools to better understand the operational procedures in an infectious disease treatment clinic, (2) design, implement and validate a treatment ward augmented with a medical CPS for patient monitoring, (3) apply intuitive control interfaces and data visualization tools for practical human-robot interaction, (4) realize traded, coordinated and collaborative shared control techniques for safe and effective mobile robot navigation inside a treatment facility, (5) assess acceptability and effectiveness of the technology among health care workers and patients. The team will develop a self-contained, modular and reconfigurable system composed of a connected sensor network for patient monitoring and a mobile robot platform for telemedicine that will primarily focus on the interoperability and integration of existing standardized
hardware and software systems to realize a testbed for verification and validation of a medical CPS. Medical, emergency response and humanitarian aid experts will be engaged to critically assess user-experiences and acceptability among medical staff to develop pathways for fielding the system in a treatment clinic. This RAPID project will lead the way in designing the next generation of human-in-the-loop medical CPS for empowering health care workers worldwide in treating patients during infectious disease outbreaks.
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Worcester Polytechnic Institute
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National Science Foundation
Sonia Chernova
Michael Gennert
Jeanine Skorinko
Submitted by Taskin Padir on September 28th, 2016
In the United States, there is still a great disparity in medical care and most profoundly for emergency care, where limited facilities and remote location play a central role. Based on the Wessels Living History Farm report, the doctor to patient ratio in the United States is 30 to 10,000 in large metropolitan areas, only 5 to 10,000 in most rural areas; and the highest death rates are often found in the most rural counties. For emergency patient care, time to definitive treatment is critical. However, deciding the most effective care for an acute patient requires knowledge and experience. Though medical best practice guidelines exist and are in hospital handbooks, they are often lengthy and difficult to apply clinically. The challenges are exaggerated for doctors in rural areas and emergency medical technicians (EMT) during patient transport.
This project's solution to transform emergency care at rural hospitals is to use innovative CPS technologies to help hospitals to improve their adherence to medical best practice. The key to assist medical staff with different levels of experience and skills to adhere to medical best practice is to transform required processes described in medical texts to an executable, adaptive, and distributed medical best practice guidance (EMBG) system. Compared to the computerized sepsis best practice protocol, the EMBG system faces a much bigger challenge as it has to adapt the best practice across rural hospitals, ambulances and center hospitals with different levels of staff expertise and equipment capabilities. Using a Global Positioning System analogy, a GPS leads drivers with different route familiarity to their destination through an optimal route based on the drivers' preferences, the EMBG system leads medical personnel to follow the best medical guideline path to provide emergency care and minimize the time to definitive treatment for acute patients. The project makes the following contributions: 1) The codification of complex medical knowledge is an important advancement in knowledge capture and representation; 2) Pathophysiological model driven communication in high speed ambulance advances life critical communication technology; and 3) Reduced complexity software architectures designed for formal verification bridges the gap between formal method research and system engineering.
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University of Illinois at Urbana-Champaign
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National Science Foundation
Submitted by Lui Sha on April 12th, 2016
In the United States, there is still a great disparity in medical care and most profoundly for emergency care, where limited facilities and remote location play a central role. Based on the Wessels Living History Farm report, the doctor to patient ratio in the United States is 30 to 10,000 in large metropolitan areas, only 5 to 10,000 in most rural areas; and the highest death rates are often found in the most rural counties. For emergency patient care, time to definitive treatment is critical. However, deciding the most effective care for an acute patient requires knowledge and experience. Though medical best practice guidelines exist and are in hospital handbooks, they are often lengthy and difficult to apply clinically. The challenges are exaggerated for doctors in rural areas and emergency medical technicians (EMT) during patient transport.
This project's solution to transform emergency care at rural hospitals is to use innovative CPS technologies to help hospitals to improve their adherence to medical best practice. The key to assist medical staff with different levels of experience and skills to adhere to medical best practice is to transform required processes described in medical texts to an executable, adaptive, and distributed medical best practice guidance (EMBG) system. Compared to the computerized sepsis best practice protocol, the EMBG system faces a much bigger challenge as it has to adapt the best practice across rural hospitals, ambulances and center hospitals with different levels of staff expertise and equipment capabilities. Using a Global Positioning System analogy, a GPS leads drivers with different route familiarity to their destination through an optimal route based on the drivers' preferences, the EMBG system leads medical personnel to follow the best medical guideline path to provide emergency care and minimize the time to definitive treatment for acute patients. The project makes the following contributions: 1) The codification of complex medical knowledge is an important advancement in knowledge capture and representation; 2) Pathophysiological model driven communication in high speed ambulance advances life critical communication technology; and 3) Reduced complexity software architectures designed for formal verification bridges the gap between formal method research and system engineering.
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Illinois Institute of Technology
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National Science Foundation
Submitted by Shangping Ren on April 11th, 2016
The National Institute of Standards and Technology (NIST) launched the 2016 Global City Teams Challenge (GCTC; see http://www.nist.gov/cps/sagc.cfm) with a kickoff meeting on November 12-13, 2015, in Gaithersburg, MD. This meeting brought together city planners and representatives from technology companies, academic institutions, and non-profits with the aim of fostering teams that will contribute to an overall vision for Smart and Connected Communities (S&CC) - effectively integrating networked information systems, sensing and communication devices, data sources, decision-making, and physical infrastructure to transform communities by improving quality of life, environmental health, social well-being, educational achievement, or overall economic growth and stability.
NIST's GCTC builds upon the National Science Foundation's (NSF) longstanding investments in cyber-physical systems (CPS). NSF established the CPS program in 2008 to develop the principles, methodologies, and tools needed to deeply embed computational intelligence, communications, and control, along with new mechanisms for sensing, actuation, and adaptation, into physical systems. The NSF CPS program, which today includes the participation of the U.S. Department of Homeland Security, U.S. Department of Transportation, National Aeronautics and Space Administration, and National Institutes of Health, has funded a strong portfolio of projects that together have pushed the boundaries of fundamental knowledge and systems engineering in core science and technology areas needed to support an ever-growing set of application domains. CPS investments are enabling systems that are central to emerging S&CC infrastructure and services, including in areas such as intelligent transportation systems (ground, aviation, and maritime), building control and automation, advanced manufacturing (including cyber-manufacturing), healthcare and medical devices, and the burgeoning Internet of Things (IoT). Dependability, security, privacy, and safety continue to be central priorities for the program in pursuing the vision of a world in which CPS dramatically improve quality of life. Along the way, the CPS program has also nurtured a vibrant CPS research community.
With this Dear Colleague letter (DCL), NSF is announcing its intention to fund EArly-Concept Grants for Exploratory Research (EAGER) proposals to support NSF researchers participating in the NIST GCTC, with the goal of pursuing novel research on the effective integration of networked computing systems and physical devices that will have significant impact in meeting the challenges of Smart and Connected Communities. Researchers must be members of, or be seeking to establish, GCTC teams that build upon the results of previous or active NSF-funded projects, and must provide evidence of active team membership and participation as part of the submission. [Note that, while this DCL is aligned with NSF’s broader efforts in Smart and Connected Communities (see http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf15120), a key requirement for this DCL is active participation in a GCTC team.] Proposals should emphasize the fundamental research inherent to the real-world problems being addressed; the manner in which the proposed solutions will be adopted by one or more local communities; and the potential challenges with respect to both research and deployment. Successful proposals will quantify the magnitude of potential societal impacts; and will result in transformative, long-term benefits rather than incremental advances. Finally, proposals must address why the work is appropriate for EAGER funding (see details below), including what key risks will be mitigated to facilitate future high-reward advances and why the timing of the project will maximize the potential for success.
The deadline for submission of EAGERs is April 1, 2016, but earlier submissions are encouraged, and decisions will be made on a first-come, first-serve basis.
Submission of EAGER proposals will be via Fastlane or Grants.gov. EAGER submissions should follow the NSF's Grant Proposal Guide (GPG) II.D.2 (see http://www.nsf.gov/publications/pub_summ.jsp?ods_key=gpg). (As noted in the GPG, EAGER is a funding mechanism for supporting exploratory work in its early stages on untested, but potentially transformative, research ideas or approaches. This work may be considered especially "high-risk/high-reward," for example, in the sense that it involves radically different approaches, applies new expertise, or engages novel disciplinary or interdisciplinary perspectives.)
An investigator may be included in only one submission in response to this DCL; if more than one is submitted, only the first one will be considered.
For further information, please contact the cognizant CPS program directors:
- David Corman, CISE/CNS/CPS, dcorman@nsf.gov
- Kishan Baheti, ENG/ECCS/EPCN, rbaheti@nsf.gov
- Sylvia Spengler, CISE/IIS/CPS, sspengle@nsf.gov
- Gurdip Singh, CISE/CNS/CSR, gsingh@nsf.gov
General Announcement
Not in Slideshow
Submitted by Anonymous on February 12th, 2016
A wide range of health outcomes is affected by air pollution. In March 2014 the World Health Organization (WHO) released a report that in 2012 alone, a staggering 7 million people died as a result of air pollution exposure, one in eight of total global deaths. A major component of this pollution is airborne particulate matter, with approximately 50 million Americans have allergic diseases.
This project will develop and field the first integrated IoT in-situ sensor package tracking pollution and pollen to provide airborne particulate mapping for Chattanooga. Longer term it is hoped that the data collection approach and initial visualization tools developed in Chattanooga can be used to support a nationwide, open access dissemination platform on the order of Google's StreetView, but called PollutionView. Such scaling of the project's pilot results through a PollutionView tool will contribute significantly to a transformation of the Environmental Public Health field in the United States. The project involves real-time big data analysis at a fine-grain geographic level. This will involve trades with sensing and computing especially if the sensor package is to be deployed at scale. The project will help determine if real-time allergen collection and visualization can improve health and wellness. Thus, this project will combine Cyber Physical Systems (CPS) and gigabit networks to address major health concerns due to air pollution. A working demonstration of this project will be presented during the Global City Teams meeting in June 2015 with an update in June 2016.
Airborne particulate matter particularly affects the citizens of Chattanooga, TN. The objectives of this project are twofold: first, to develop and deploy an array of Internet of Things (IoT) in-situ sensors within Chattanooga capable of comprehensively characterizing air quality in real time, including location, temperature, pressure, humidity, the abundance of 6 criterion pollutants (O3, CO, NO, NO2, SO2, and H2S), and the abundance of airborne particulates (10-40 µm), both pollen-sized and smaller PM2.5 (<2.5 µm) particles; and second, to have a pollen validation campaign by deploying an in-situ pollen air sampler in Chattanooga to identify specific pollen types.
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University of Texas at Dallas
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National Science Foundation
Submitted by David Lary on December 22nd, 2015
Cyber physical systems (CPSs) are merging into major mobile systems of our society, such as public transportation, supply chains, and taxi networks. Past researchers have accumulated significant knowledge for designing cyber physical systems, such as for military surveillance, infrastructure protection, scientific exploration, and smart environments, but primarily in relatively stationary settings, i.e., where spatial and mobility diversity is limited. Differently, mobile CPSs interact with phenomena of interest at different locations and environments, and where the context information (e.g., network availability and connectivity) about these physical locations might not be available. This unique feature calls for new solutions to seamlessly integrate mobile computing with the physical world, including dynamic access to multiple wireless technologies. The required solutions are addressed by (i) creating a network control architecture based on novel predictive hierarchical control and that accounts for characteristics of wireless communication, (ii) developing formal network control models based on in-situ network system identification and cross-layer optimization, and (iii) designing and implementing a reference implementation on a small scale wireless and vehicular test-bed based on law enforcement vehicles.
The results can improve all mobile transportation systems such as future taxi control and dispatch systems. In this application advantages are: (i) reducing time for drivers to find customers; (ii) reducing time for passengers to wait; (iii) avoiding and preventing traffic congestion; (iv) reducing gas consumption and operating cost; (v) improving driver and vehicle safety, and (vi) enforcing municipal regulation. Class modules developed on mobile computing and CPS will be used at the four participating Universities and then be made available via the Web.
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SUNY at Stony Brook
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National Science Foundation
Submitted by Shan Lin on December 22nd, 2015