
NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
Recipient: |
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Initial Amendment Date: | July 15, 2019 |
Latest Amendment Date: | July 15, 2019 |
Award Number: | 1924112 |
Award Instrument: | Standard Grant |
Program Manager: |
Ashok Srinivasan
OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
Start Date: | September 1, 2019 |
End Date: | August 31, 2023 (Estimated) |
Total Intended Award Amount: | $247,373.00 |
Total Awarded Amount to Date: | $247,373.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
1112 DALLAS DR STE 4000 DENTON TX US 76205-1132 (940)565-3940 |
Sponsor Congressional District: |
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Primary Place of Performance: |
1155 Union Circle #305250 Denton TX US 76203-5017 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): |
CyberTraining - Training-based, CYBERCORPS: SCHLAR FOR SER |
Primary Program Source: |
04001920DB NSF Education & Human Resource |
Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070 |
ABSTRACT
The combination of a network of physical devices embedded with electronics, Internet connectivity, and other hardware, such as sensors, that can communicate and interact with others over the Internet is known as the Internet of Things. One familiar application of this technology is the "smart home" in which people monitor and control their lights, thermostats and security systems remotely using smart phones or smart speakers. An Internet of Things-based framework for the healthcare industry is called the Internet of Medical Things. This technology connects patients to their physicians and supports the transfer of medical data over the Internet. Concerns about the privacy of data transmitted over the Internet and network security are challenges facing all applications of the Internet of Things concept, but they can be exacerbated by the knowledge gap between the designers of the frameworks and the end users in the medical field. As the healthcare industry grows to meet the needs of an aging population, the workforce that designs Internet of Medical Things devices and the networks that connect them must be ready to address these privacy and security concerns. The project is addressing this gap, and thus serves the national interest, as stated by NSF's mission: to promote the progress of science; to advance the national health, prosperity and welfare.
Easy-Med is a multi-disciplinary training program designed to improve core literacy of cyber infrastructure for students at the undergraduate level in northeast Texas. The six-week-long mentored program provides immersive training to increase the students' ability to develop and use secure, privacy-assured sensing healthcare frameworks. A different training module is provided each week and each day of the module includes four hours of lecture and three hours of hands-on lab exercises. Training modules introduce the students to the different aspects involved in designing devices and networks for the Internet of Medical Things. The six training modules, components of which are also provided online, include: 1) types of biosensors and Internet of Medical Things components, 2) system-level modeling of Internet of Medical Things networks, 3) signal and data analytics used in healthcare, 4) security and privacy assurance in Internet of Medical Things technology, 5) applications of biosensors in the healthcare industry, and 6) use of and ethics involved in using the Internet of Medical Things in the community setting. Students who participate in Easy-Med during the summer are encouraged to further their knowledge and provide outreach about the program by participating in a Build-a-Thon activity during the following fall semester and a research symposium in the following spring semester.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The overall goal of the project (called Easy-Med) is to develop an off-the shelf component-based Internet-of-Medical-Things (IoMT) enabled medical training frameworks to train STEM students with sensing, cybersecurity, and privacy-aspects of smart healthcare.
The key outcomes of this project include:
(1) Novel Blockchain or distributed ledger technology (DLT) based methods for pharmaceutical quality assurance in the global distribution supply chain.
(2) Novel Blockchain or distributed ledger technology (DLT) based methods for data and device privacy and security in smart healthcare.
(3) Novel Security-by-Design (SbD) or Hardware-Assisted Security (HAS) cybersecurity solutions that can provide robust security in healthcare Cyber-Physical System (H-CPS) that makes smart healthcare.
(4) Novel Physical Unclonable Function (PUF) based integrated security protocols for Internet-of-Medical-Things (IoMT) devices which are often resource-constrained and energy-constrained being small, portable, and battery driven.
(5) Machine learning based methods and devices are effectively used to significantly transform healthcare to smart healthcare in which the user is an active participant along with healthcare providers.
(6) Machine learning based smart healthcare can provide automated health monitoring and management with minimal input from the healthcare providers while present with the user round the clock.
(7) Ethical decision making in human-machine interactions in health care settings.
(8) Evaluate the role of policy and the regulatory compliance systems in the use of smart technologies in health care services.
Formal dissemination is performed through 30 peer-reviewed journal and conference publications. The PI/co-PI delivered 14 Keynotes and Invited Talks, and through the duration of the project for wider dissemination of the project outcomes. PI participated in 5 Expert Panels at various International Conferences to make IT, IoT, AI communities aware of smart healthcare technology. Participating graduate Students presented over 10 papers at various international conferences. A total of 20 modules were developed to train STEM undergraduate students in smart healthcare. The training demo module presented technical details of smart healthcare architecture to students of different disciplines, such as computer science, computer engineering, electrical engineering, biomedical engineering, rehabilitation. Overall, approximately 40 undergraduate students got trained in smart healthcare technologies and ethics during the execution of the project. A total of 7 STEM graduate students (4 of them are woman Ph.D. students) who worked on the project got exposure to smart healthcare technology and got significant boost in their employability. Students at various levels and disciplines got an opportunity for skill development in cutting-edge research areas including body sensors, machine learning, Security-by-Design (SbD), hardware-assisted security (HAS), blockchain, distributed ledger, and healthcare technologies. For public dissemination, the preprints of the publications are made available in ResearchGate page as well as many preprints are made available at public depository. Many datasets used in this project has been made available in GitHub and Kaggle for their usage of researchers around the globe. World Health Organization (WHO) listed more than 4 smart healthcare papers/articles from our group in its COVID-19 Global literature on coronavirus disease at its website.
Last Modified: 09/12/2023
Modified by: Saraju P Mohanty
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