Creating a Community Infrastructure for Interoperable Emergency Connectivity
Lead PI:
Kaikai Liu
Co-Pi:
Abstract
Many areas of the United States are subject to seasonal and cyclical natural disasters like floods, earthquakes and hurricanes, while all areas may experience technological or human-caused events leading to communications disruptions. Following a disaster, it is essential for professional emergency responders to have a comprehensive understanding of the damage in the community in order to prioritize resources to save lives and protect the environment. Failure to develop an accurate picture of community conditions may lead to ineffective allocation of scarce response and rescue resources. Current technologies used for day-to-day emergency response information gathering from the public, such as 9-1-1 calls and social media, are often disrupted by the disaster?s impact, which may persist for days after an event. One of the key factors enabling a coordinated emergency response and community resilience to disaster is rapid communication from community members such as residents, businesses, schools and hospitals to public safety services about community conditions, such as the location of trapped people, collapsed buildings, fires and hazardous materials accidents, highway damage, and traffic congestion. Robust and resilient communication systems incorporating and enhancing existing technologies are the solution.

The City of San Jose has recognized the likelihood of post-disaster information deficits which can be resolved through increased connectivity of diverse community elements to public safety communications. Recognizing the presence of privately-owned Smart phones throughout the community, the City is seeking an information gathering and dissemination solution that would enable Smart phone users to maintain communication with public safety services even in disaster conditions. San Jose State University, partnered with the San Jose Office of Emergency Services (OES), proposes to develop a novel method for maintaining connectivity for residents to public safety services. The proposed connectivity and networking technologies will keep citizens connected to vital services and information, and allow them to provide disaster assessment information to public safety agencies. This project will also create a cloud dashboard for emergency responders, and create a comprehensive view of community conditions which leads to an effective emergency response. The prototype system will enable the city's public safety agencies to prioritize emergency response demands and respond quickly, and minimize the catastrophic impact on the City of San Jose and its community and economy.

The prevalence of disruptive events across the United States makes the development of a resilient communication solution imperative. The available collaboration with the City of San Jose provides a real-world partner and testbed for new technology applications with nation-wide application potential. As climates change, storms become stronger, sea levels rise, the electricity grid ages and social disruptions increase, time is of the essence for creating a resilient and accessible solution to reliable communication connectivity. This Early Concept Grant for Exploratory Research (EAGER) will solve the key challenges that must be tackled to achieve this timeliness and provide strategies and system solutions to spur emergency awareness, management, and preparedness. Finally, all code and data in this project will be released openly, supporting future research, development, and training.

First responders to disasters need a complete picture of the community's status in order to accurately assess the condition of the inhabitants and organize available resources to save lives, protect the environment and prevent further damage in the community. In normal circumstances public safety services rely on 9-1-1 calls and social media to gather information from residents about community conditions. However, under disaster conditions, these normal communication methods will be interrupted, including landline and cell phones, internet connectivity and power. In these circumstances, novel systems must be available to substitute for the lost connectivity, to allow residents to connect to the public safety answering point, and to allow the Emergency Operations Center to collect and aggregate critical information across sectors to ensure that lifesaving operations are conducted expeditiously.

The solution to managing risks to disaster-prone communities includes integrating existing technologies, applications, data and e-services in sustainable networks that will support emergency communications even in catastrophic events. This research proposes to develop a community infrastructure for interoperable emergency connectivity that can operate in austere conditions, provide its own power, and create linkages throughout the community and across jurisdictional boundaries. This project will deploy the edge devices in local communities with multi-modal communication modules as well as an external long range radio. The proposed resilient and participatory networking framework on top of the remote edge devices will enable collaborative communication as well as participatory sensing. To solve current deficiencies in the ability of allowing city emergency responders to control and automate the remote edge devices, this project extends existing cloud orchestration frameworks to edge devices that are agnostic to the network media. For this demonstration project, the central cloud deployed in the City of San Jose?s Emergency Operations Center will control the remote edge devices, and be responsible for resilient quality testing, automatic validation, disaster assessment, resource allocation, and the automation of remote edge devices.
Kaikai Liu
Kaikai Liu is an Associate Professor and Cisco Corporate Chair Professor in the Department of Computer Engineering. His research interests include Intelligent and Autonomous Systems, Mobile and Cyber-Physical Systems (CPS), Artificial Intelligence of Things (AIoT), Smart Sensing, Data Mining, Next-Generation Communication and Sensing Systems. He has published over 40 peer-reviewed papers in journals and conference proceedings, 1 book, and holds 4 patents (licensed by three companies). His research has been funded by the National Science Foundation (NSF), Department of Health of Hawaii, Knight Foundation, and many industry companies including Intel, Arista, and Cisco. He was a member of the NSF Big Learning Center (previously Scalable Software Systems Laboratory). He received a Ph.D. degree in Computer Engineering from the University of Florida (UF) under the direction of Dr. Xiaolin (Andy) Li. He is a recipient of the Outstanding Achievement Award at UF (four times), the Apple WWDC Scholarship (2013 and 2014), the Innovator Award from the Office of Technology Licensing at UF (2014), the Top Team Award at NSF I-Corps Winter Cohort (Bay area, 2015), the 2015 Gator Engineering Attribute Award for Creativity at UF, IEEE SWC 2017 Best Paper Award, IEEE SECON 2016 Best Paper Award, ACM SenSys 2016 Best Demo - Runner-up, 2016 CoE Kordestani Endowed Research Professor, 2017 and 2018 CoE Research Professor Award, Faculty Mentoring Award for CSU Student Competition 2018, and 2020 College of Engineering Award for Excellence in Scholarship. He served as the technical program chair for IEEE Mobile Cloud 2020, 2023 and as a TPC member and technical reviewer for many IEEE/ACM conferences and journals.
Performance Period: 08/15/2016 - 01/31/2019
Institution: San Jose State University Foundation
Award Number: 1637371