Abstract

With the rise in frequency and magnitude of natural disasters, there is a need to break down monolithic organizational barriers and engage with community volunteers. This calls for ease of systems interoperability to facilitate communication, data-sharing and scalability of real-time response, essential for crisis communications. We propose two scalable frameworks that enable multi-agency interoperability and real-time data-sharing. The first framework harnesses the power of social media, artificial intelligence, and community volunteers to form an extended rescue-and-response network that alleviates call center burden and augments the finite capacity of dispatch units. Through an "online 9-1-1" service, affected people can request help and be automatically triaged and routed to the closest response unit registered within the system. By connecting first responders, dispatchers, victims and volunteers, this approach can enable communities to respond effectively to large-scale disasters by having humanitarian organizations be a proactive and reactive part of the Public Safety Network. Delay analysis shows that the online 9-1-1 system has an expected response time comparable to the traditional system, with the added benefit of call center and dispatch scalability. The second framework enables data sharing between different agencies by allowing on-demand access to data protected by institutional policies. This is achieved through a custom, reactive Software-Defined Networking module in the Floodlight controller that communicates with an external server to get information about registered agencies and then pushes those traffic paths automatically to the respective domain's network device flow tables. This approach eliminates the need to have a global, consistent view of the network topology, and the resulting controller-to-controller communication and coordination which can be especially challenging in large networks. This framework has applicability in many areas, including scientific data sharing among universities or research institutions, patient data sharing among hospitals or between first responders quickly accessing critical medical information on-demand at a disaster site.

Graduation Date

2020

Semester

Fall

Advisor

Yuksel, Murat

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Electrical and Computer Engineering

Degree Program

Computer Engineering

Format

application/pdf

Identifier

CFE0008309; DP0023746

URL

https://purls.library.ucf.edu/go/DP0023746

Language

English

Release Date

December 2021

Length of Campus-only Access

1 year

Access Status

Doctoral Dissertation (Open Access)

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