An IoT-Enabled Critical

Infrastructure Information Network

(ICI-IN) for a Future Resilient City

Critical infrastructures (CIs) include transportation, electricity, healthcare, information technology, emergency services, and water systems. CIs play a critical role in supporting emergency management agencies (EMAs) and affected people’s crisis response activities during disasters, such as transportation for evacuations, drinking water provision for basic needs, and electricity supply for making food. Previous studies including crisis informatics and the use of the Internet of Things (IoT) cannot include comprehensive situation awareness (SA) of CIs conditions in crisis. To resolve this gap, this project takes the first step for supporting crisis response activities of the EMAs and affected people through enhanced SA of CIs. Using Port St. Joe (PSJ) as the case study area, this study

evaluates the CIs information needs. This project investigates the affected people’s information needs of CIs’ various sectors through a questionnaire among the residents in PSJ. The findings can support the comprehensive implementation of the IoT enabled smart system for CIs such as the optimized distribution of the limited resources to CIs sectors which are in the most urgent needs of the affected people. Additionally, this project has built the fault tree model to validate the effectiveness of IoT for enhancing SA of CIs. The results demonstrate that implementing the IoT-enabled critical infrastructure information network help to enhance the SA of CIs and further improve community resilience.

The implementation flow of the ICI-IN for CIs

This project aims to answer two questions as follows:

• What are the information needs in terms of critical infrastructures (CIs) to support their responses in Hurricane Michael?

• How can the IoT-enabled CIs information network (ICI-IN) enhance community resilience?

This project not only demonstrates the effectiveness of the ICI-IN for enhancing community resilience but also reveals humans’ information needs of CIs to make their response strategies. The findings pave a way for the future design and implementation of the ICI-IN in PSJ as illustrated in Figure 1. The ICI-IN involves with identification of CIs information needs (this project), the selection and deployment of proper sensors for CIs data collection, communication, storage and analysis of CIs data, and the design of user interfaces for the emergency management agencies (EMAs) and affected people. The comprehensive implementation of the ICI-IN depends heavily on the evaluation of information needs, such as which information items are needed by the EMAs and affected humans during disasters. The findings in this project can support the selection and deployment of proper sensors for CIs data collection.

This project conducted the questionnaire among the residents in PSJ to investigate both the EMAs and affected humans’ information needs of CIs in hurricanes. The first part asks the demographic characters of the respondents, including race/ethnicity, gender, and age. The second part of the survey includes seven questions, which were described in Appendix A-Table 1. In Q1, the CIs’ impact evaluation includes four levels: not impacted (i.e., 0.00%), lightly impacted (i.e., 33.33%), impacted (i.e., 66.66%) and seriously impacted (i.e., 100.00%). In Q2 to Q6, the evaluation for the information needs of CIs various information items also has four levels including no need (i.e., 0.00%), somewhat need (i.e., 33.33%), need (i.e., 66.66%) and strongly need (i.e., 100.00%). In Q7, there are nine numbers from 1 (first recover priority) to 9 (least recover priority) for the rank of recover priority of CIs sectors.


To explore the effectiveness of the ICI-IN for enhancing community resilience, this project has designed the fault tree model of CIs for human’s crisis responses. We have built two fault tree models, one without the ICI-IN and one with the ICI-IN. By comparing the failure mechanisms of CIs and further their impacts on humans’ crisis responses in these two fault tree models, this project has demonstrated the effectiveness of the ICI-IN for enhancing community resilience.

This project conducted two-rounds of data collection through a survey among local public agencies and residents. Interviews over zoom were done with managers of the public agencies such as the Wastewater Treatment Plant in Port St. Joe and Northwest Florida Water Management District. After the online meetings we visited to survey the Port St. Joe residents. Surveys were approved by the University of Florida (UF) Institutional Review Boards (IRBs) and interviews were conducted individually.

CIs significance levels on humans’ crisis responses:
With residents’ responses in Q1, this research calculated the average impact levels for the nine CIs subsectors on their response activities. The results were illustrated in Table 2. The ranks in Table 2 reflect the significance of CIs various sectors in supporting humans’ crisis responses. For instance, the top two CIs subsectors in Table 2 are related to the affected humans’ basic needs such as the drinking water system supporting their water needs, and the electricity and fuels supporting them to make food.


Humans’ information needs of CIs conditions:
For the replies to Q2-Q6, this project has quantified the level of affected people’s information needs of CIs’ 19 information items. The results were presented in Table 3. Here takes the WWS sector as an example. In Table 3, we can see the affected citizens prioritized the drinking water system at their top needs including Drinking water system 1 and Drinking water system 2 (see details in Table 1). This phenomenon is reasonable as the drinking water system fulfills the affected people’s basic needs for drinking water. Contrary to the drinking water system, the affected people were less concerned about the sewer system (rank 12 for two sewer system items). When referring to whether the sewer system contaminates the drinking water sources (rank 7), the affected citizens presented more concerns than that to the sewer system. Additionally, the affected citizens in PSJ showed less interest in the stormwater system including stormwater system 1 (rank 11) and stormwater system 2 (rank 13).


Evaluation of ICI-IN effectiveness for community resilience:
Two fault tree models for the impacts of CIs failures on humans’ crisis response were established as illustrated in Figures 1 and 2. The example scenario is designed as follows. Hurricane Michael came to PSJ, Florida, and some roads were affected by the hurricane. Humans in PSJ needed to evacuate from their houses. Without the IoT enabled CIs information network (ICI-IN), Figure 1 shows how the lack of road/traffic conditions bring in the failures in humans’ evacuation activities. The failure in evacuation activities can further fail humans’ crisis responses. Figure 2 illustrates how the disaster impacts on the road network or traffic can impact humans’ crisis responses with the involvement of the ICI-IN. When there are disaster impacts on road network/traffic conditions and the failure of ICI-IN happened, we can see humans will lack road/traffic conditions. As a result, the implementation of the ICI-IN can reduce the probability of lack of road/traffic conditions, which can further increase community resilience.

The survey results help the future work on the identification of the affected humans’ concerns with CIs condition data. For instance, according to the affected people’s feedback on the impacts of various CIs sectors (see Table 2), CIs planners can give the priority of limited resource distribution to the ESI, WWS-drinking water system, WWS-wastewater system, IT and the TSS sectors. Specifically, the results of the affected people’s evaluation of their needs in CIs’ various information items (see Table 3), can refine the priority in the use of resources as following.
1) TSS sector: Resource use can be firstly used to monitor road and bridge conditions.
2) WWS sector: The priority in the use of resources should support the monitor of drinking water system 1 & 2, and drinking water and sewer system (see Table 1 for the information details).
3) ESI sector: The delivery of resources to support the monitor of gas and fuels, and electricity, should have the priority.
4) HPH sector: The resource use priority should be spread to the monitor of medical service centers, and temporary medical service stations and shelters 1 & 2 see Appendix A-Table 1 for the information details).
The complete implementation of the ICI-IN system for CIs in PSJ can benefit the EMAs and affected humans from various aspects such as the selection of evacuation routes, distribution of gas/fuel stations with available gas and fuels, whether the drinking water in their houses is available and the conditions of medical service centers and shelters. As a result, the implementation of the IoT enabled smart system for CIs can enhance both the EMAs and the affected people’s response capacities during disasters, which can further improve community resilience. The enhancement of community resilience helps to establish resilient cities.

This project evaluates the CIs information needs of the EMAs and affected humans during disasters. The findings in this project help set the priority in the use of limited resources to implement the IoT enabled smart system for the traditional CIs. Future work will focus on the selection of proper sensors to monitor CIs’ various information items by referring to the summarized use priority of resources in the current study. Additionally, our future work will involve with more scenarios when comparing the two fault tree models. More failure mechanisms will also be considered from the basic events. Meanwhile, interviews with experts and managers from related management agencies in various CIs sectors will be conducted, which will help to quantify the failure probability of basic and intermediate events. The probabilities can be applied to quantifying the community resilience increase by implementing the ICI-IN in PSJ.

TEAM

Rui Liu, Assistant Professor, M.E. Rinker, Sr. School of Construction Management, liurui@ufl.edu

Xiao Yu, Assistant Professor, Department of Civil and Coastal Engineering, Xiao.yu@essie.ufl.edu

Xilei Zhao, Assistant Professor, Department of Civil & Coastal Engineering, xilei.zhao@essie.ufl.edu

Student Collaborators: Faxi Yuan, PhD, M.E. Rinker, Sr. School of Construction Management, faxi.yuan@ufl.edu

Community Partners: Kevin Pettis, Manager, Port St. Joe Wastewater Treatment Plant. Paul Thorpe, Resource Planning Manager, NWFWMD and John B. Crowe, CTP Program Manager, NWFWMD. (North West Florida Water Management District).

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