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Hierarchical Cloud-Fog Platform forCommunication in Disaster Incident Coordination

Duo Jiang, Rui Huang, Prasad Calyam, John Gillis, Olivia Apperson,Dmitrii Chemodanov, Fatih Demir, Salman Ahmad

University of Missouri-Columbia, Northern Illinois University; USA{calyamp, gillisj}@missouri.edu; {dj963, rh4m8, oamr6, dycbt4}@mail.missouri.edu; fdemir@niu.edu; ahmadsa@health.missouri.edu

Abstract—Communication and coordination in a mass casualtydisaster scenario is limited and difficult for medical personnel inthe absence of necessary communication infrastructure and tech-nologies that enable situation awareness. This leads to misdirectedand delayed triage of scene-wide critically injured patients, espe-cially when there are large numbers of patients needing diversecare levels. A hierarchical cloud-fog setup involving a core cloudand edge clouds (i.e., fogs) can help the patient triage related real-time data movement challenges. It can create visual situationalawareness and overcome infrastructure limitations at the wirelessnetwork edge. In this paper, we describe our “Panacea’s Cloud”,a hierarchical cloud-fog platform that provides augmented realitybenefits with real-time human communication and geolocationservices through the integration of a standardized IncidentCommand System (ICS) with smart devices such as heads-updisplays, virtual beacons, and wireless mesh network elements.We show how the ICS can run using a core cloud as an intelligentdashboard that leverages fog resources and data collection closeto the incident scenes. In addition, we describe experimentresults from evaluations of Panacea’s Cloud dashboard usabilityand platform performance that show benefits and issues inhierarchical cloud-fog service management in support of ICScommunication during disaster incident coordination.

Index Terms—hierarchical cloud-fog platform, fog benefits inhealth care, disaster medical triage, smart geolocation tracking

I. INTRODUCTION

Disaster incident response is a complex task due to tra-ditional infrastructure assumptions that may fail given thedamage made by man or natural causes. Additionally, there isa need to handle large amounts of data from multiple incidentscenes and from disaster relief co-ordination efforts betweenfirst responder agencies such as fire, police, hospitals [1].

In our previous work [2], [3], we have shown the need fora mobile ad-hoc wireless network (MANET) that needs to beoperational for quickly transferring media-rich data from thedisaster scene to enable communication in disaster incidentcoordination. Data in a disaster incident response applicationcontext corresponds to the transfer of real-time high-definitionvideo streams generated by paramedics’ wearable heads-updisplays (HUDs) and other video devices from the disastertriage scene to an intelligent dashboard. We have also found inour prior work that incident response and resource allocationdecision making (e.g., ambulance routing to scene, medicalsupply replenishment) requires significant computational re-sources, particularly for multiple simultaneous incident cases

This material is based upon work supported by the National ScienceFoundation under Award Number CNS-1647182 and the Coulter Foundation.Any opinions, findings, and conclusions or recommendations expressed in thispublication are those of the author(s) and do not necessarily reflect the viewsof the National Science Foundation or Coulter Foundation.

Edge Cloud(e.g., Mobile Cloud)

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Fig. 1: Illustration to show how during disaster-incidents, data is typicallygenerated at sites where there is not abundant computation/storage resourcesavailable. Consequently, data needs to be transferred to an edge cloud or fog,and to a core cloud for pertinent decision making computations.

with a large numbers of patients. The main hypothesis of theresearch in this paper is that a hierarchical cloud-fog setupinvolving a core cloud and edge clouds (i.e., “fogs”) can helpthe patient triage related real-time data movement challengesfor creating visual situational awareness and overcome infras-tructure limitations at the wireless network edge.

In this paper, we present our investigations for building ahierarchical cloud-fog platform viz., “Panacea’s Cloud” thatsupports an Incident Command System (ICS) application.Figure 1 illustrates our hierarchical cloud-fog setup for adisaster incident-supporting application we are developing formedical triage communications between paramedics and otherfirst responders. We address the design challenges of thehierarchical cloud-fog setup for the analytics and dissemina-tion of application’s real-time data with location-awarenessand its usability in austere edge network health conditions.Specifically, we describe a novel geotracking service andour new Panacea’s Dashboard features that use core cloudcapabilities to integrate smart devices (heads-up displays,virtual beacons and wireless mesh network elements) and theirdata collection in the fogs. Our approach is innovative becauseit transforms an ICS application setup and enables real-timetriage coordination between incident commanders and firstresponders simultaneously across multiple incident scenes.

In addition, we present our usability evaluation and platformexperiments of our Panacea’s Cloud in terms of communi-cation and situational awareness (i.e., patient, responder andsupply status). Our usability evaluation experiments considera realistic Tornado disaster incident scenario, and characterizethe task completion success rate (effectiveness) and time(efficiency) with human subjects. Our platform experimentshighlight the issues in hierarchical cloud-fog service manage-ment in terms of HUD heating during ICS communications,and communication quality in HUD-to-device, HUD-to-routerand router-to-router communication cases. Thus, our work onPanacea’s Cloud as well as its realistic evaluation engendersnew possibilities for next-generation ICS systems that outper-form existing industry offerings such as Intermedix [4].

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The rest of the paper is organized as follows: In Section II,we discuss related work. Section III describes next-generationICS requirements, and our Panacea’s Cloud solution com-ponents that utilize hierarchical cloud-fog platform capabil-ities for communication in disaster incident coordination.Section IV presents our experimental evaluation results thatshow benefits and issues of our solution approach. Section Vconcludes the paper.

II. RELATED WORK

Earlier works such as WIISARD [5] proposed a systemfor response units to improve medical care of victims indisasters scenarios. Personal digital assistants that have wire-less capability are integrated with electronic medical recordsoftware to replace paper triage tags to log patient information.An Intelligent Transportation System that includes VehicularAd hoc Networks (VANETs), and mobile cloud computingresources is presented in [6]. This intelligent system is ableto gather information from multiple sources and locations,including the scene of an incident, and to suggest effectivestrategies and decisions that can be propagated to vehicles(such as ambulances) and other entities in real-time. Thesystems in these works are comparable to Panacea’s Cloudwith regards to their intelligent dashboards located in the edgecloud. Our Panacea’s Dashboard design is novel in the sensethat it enables real-time communication using a hierarchicalcloud-fog platform, and orchestrates core cloud resourcesto execute optimization algorithms for incident response re-source allocation, and decision making (e.g., ambulance rout-ing to scene, medical supply replenishment). Moreover, ourPanacea’s Cloud addresses some of the key drawbacks forinformation aggregation in disaster networks identified byauthors in recent works such as [7] and [8], where they providea comprehensive analysis of contemporary efforts to addressmobile cloud management of disasters.

Recent works such as DIORAMA [9] have similar aimsas our Panacea’s Cloud work to solve problems of medicaltriage during mass casualty incidents. The DIORAMA systemcollects spatiotemporal data to create visual analytics of patientand resource locations and their status, and also features a mapinterface that supports a set of tools for incident commandercommunications. Unlike our work, the DIORAMA does notreap the benefits of using an ad hoc wireless network and acloud-fog platform when traditional infrastructure is affectedduring a disaster occurrence. Instead, it relies on an intact tra-ditional infrastructure of cell and radio towers for its Androidsmartphone and tablet applications to interact with active RFIDreaders and tags to transmit information.

Our work is also closely related to the AID-N effort [10]conducted in 2008, where technologies such as electronictriage tags, web-portals, wearable vital sign sensors, legacyhand-held interface devices, and regular teleconferencing wereused to enable collaboration between emergency responsepersonnel. However, the data collection was conducted inan offline manner through physical device synchronization.In contrast to this and other common ICS systems such asIntermedix [4], our Panacea’s Cloud can help responders com-municate with networked wearable HUDs and to view patientand supply status using virtual beacons at the disaster scene in

real-time using a hierarchical cloud-fog platform. Further, ourwork also addresses another important issue identified in [11]that poorly designed user interfaces to provide situation aware-ness may cause obstacles for incident commanders trackingfirst responders across geographic locations with an ICS. Ourdata collection and analysis methods allows for creation ofinteractive maps within familiar ICS layouts that have beenshown to help ICs to make quick decisions [12].

III. PANACEA’S CLOUD SOLUTION

In this section, we first describe the requirements foreffective coordination between the incident commander andresponders at a disaster scene. Following this, we describethe system architecture and software design, along with thedeveloped components in our hierarchical cloud-fog solution,including a wireless mesh network communication protocol,use of HUDs, virtual beacons, and Panacea’s Dashboard.These components create the fog infrastructure at the edgenetwork, and are integrated with the core cloud computationresources to run complex optimization algorithms to effec-tively meet the ICS needs of disaster medical triage andresource allocation decision making.

A. Disaster Scene Response Requirements

A typical ICS structure is mainly comprised of the IncidentCommander who instructs three subgroups: the Logistics Sec-tion Chief, the Planning Section Chief, and the Medical BranchDirector. These staff also have authority over various othersupport personnel that are allocated to particular incidentsinitiated within the ICS. When an incident occurs, a priortemplate is used to register the incident, and appropriatestaff personnel associated with the template are automaticallynotified to respond. As responders arrive at the scenes andconduct relief activities, information is passed from thesescenes to the heads of the subgroups, and then up to theIncident Commander to interpret and provide more instructionand deploy additional resources (e.g., ambulances, medicalsupplies, domain experts). Such a personnel organizationensures that the Incident Commander receives all necessaryinformation and has situational awareness to appropriatelyrespond to the various events at the incident scenes at all times.

We recently conducted an online survey in collaborationwith EMS1 media website [14] to: (a) obtain a general senseof the scale of disaster incidents in recent times to guide thework of this paper, and (b) gauge the pain points in technol-ogy requirements for effective disaster response. The surveyattracted 1,746 responses from a population that included amajority of first responders. Survey summary indicated that60% of disaster incidents range from 5-to-30 triage patients.In addition, 35% of the responders viewed communication ingeneral (including communication with Incident Commander)as the major pain point in the response during a mass ca-sualty incident; 46% of the responders expressed the lack ofinformation or necessary resources (again can be attributedto communication challenges) as the other major pain point.Further, 70% admitted that handheld radio communication wasthe most frequently used technology to track patients and carefor patients during a mass casualty incident, and only 15%had the capability for live tracking of care status.

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Fig. 2: Panacea’s Cloud communication workflow to integrate the core cloud with data-of-interest fog in order to aid ICS decision making.

Thus, a solution such as our Panacea’s Cloud has thepotential to have a transformative effect on the state-of-the-art in terms of meeting ICS application requirements. It canbe a significant capability for disaster relief coordinationowing to its features of: (i) live tracking of multiple events’status based on data collection with smart devices at incidentlocations, and (ii) advanced communication and computationplatforms for fostering real-time mission-oriented situationalawareness through data integration and dissemination betweenthe incident commander and first responders.

B. Fog Infrastructure of Smart Devices

As the Figure 2 illustrates, there are a sequence of basicworkflow events between the disaster incident scenes (data-of-interest fog infrastructure) and the incident command center(decision making fog location). Natural or human-made masscasualty disasters generally encompass a large geographicregion as well as result in disrupted infrastructure, such asbroken-down networks, uneven terrain, collapsed buildings,and other limitations. Panacea’s Cloud provides a fog com-puting component to this situation through a compact customenclosure (i.e., a Pelican Case) that is rugged and weather-proof to protect the devices. The fog computing componentincludes a combination of a mobile RouterBOARD router,Raspberry Pi server with the corresponding database, batteryto provide power for several hours, and a touchscreen for con-figuration. Multiple enclosures or fog computing componentscan be distributed throughout the geographic region in orderto provide the adequate wireless and fog computing coveragefor the entire area depending upon the scale of the disasterresponse, and edge network constraints such as e.g., energy.

The communication component in Panacea’s Cloud foginfrastructure is comprised of two smart devices, Heads-upDisplays (HUDs) and virtual beacons (i.e., Estimote Beacons).Paramedics wearing a HUD (i.e., Recon Jet) can use virtualbeacons to mark location/status of nearby patients. Each HUDdetermines its current location via GPS and the signal strengthsof nearby virtual beacons. This raw data made up of thepatient and paramedic locations is sent to the Raspberry Pi

server i.e., the fog computing component. Then the gathereddata on the Raspberry Pi server is sent to the core cloudinfrastructure, if and when available through cellular, wi-fi orsatellite connections. The Incident Commander can observethe locations of every paramedic wearing a HUD and everypatient marked by a virtual beacon through markers on areal-time map that provides visual situational awareness ofthe triage care status. Geolocation awareness of various scenelocations can also be obtained using not only the HUDs butthrough any other Global Positioning System (GPS) equippedmobile devices (e.g., phones or tablets).

C. Computing in the Core Cloud

The core cloud resources can be rented from public cloudssuch as Amazon Web Services (AWS), and associated geolo-cation assistance services such as Google Maps and MapBoxApplication Programming Interfaces (APIs) can be leveragedthrough core cloud access. According to the solution functionsnecessary in disaster scenarios outlined earlier in Section III-A,it is necessary to migrate parts of system to the core cloud(considering real-time constraints in the ICS application usecases) to adequately process, store and protect the data. Inaddition, if the scale of number of simultaneous incidentsor number of triage patients are large in number, the datahandling, data fusion analysis and visualization have to beperformed using core cloud resources.

We have designed the Panacea’s Dashboard (whose screen-shot is shown in Figure 3) to be portable, and can be made toseamlessly be located either in the fog infrastructure or cloudinfrastructure depending upon the incident scale and IncidentCommander preference. The Panacea’s Dashboard front-endis compliant with ICS interfaces in the industry for the func-tionality expected, and is created using the Twitter Bootstrapframework and HTML 5. The back-end of the dashboardconnects to a MySQL database with the use of JavaScript,AJAX, PHP, and jQuery working in unison. The smart devicesintegration, specifically HUD integration is made possible withthe use of the WebRTC framework. The back-end is decoupledfrom the front-end, which allows custom user interfaces to bedeveloped to suit ICS user needs for disaster response.

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Fig. 3: Panacea’s Dashboard layout that creates visual situational awareness of the overall medical triage care status across multiple incident scenes.

A custom chat application that we have developed handlesall video streaming data between users and works with a serveracting like a directory (or phone book) of every availableparamedic. It uses the WebRTC framework, HUD device (i.e.,Google Glass or Recon Jet) programming APIs in order to en-able live video feeds. The chat application also handles deviceabstractions by detecting supported HUD hardware (Recon Jetor Google Glass) and maps the controls via the appropriateAPI for the device. Furthermore, the chat application alsohandles interacting with the Estimote Beacons to realize thevirtual beacon functionality. The Panacea’s Dashboard enablesIncident commanders to manage the staff directory, activeincidents, and helps organize auto-generated notifications ofimportant status items. We can see that the ‘Dashboard’ pagedisplays the entire real-time visual situational awareness ofmultiple incidents and the latest status of the patients, respon-ders and the supply at the incident scenes. Contextual markerson the map provide additional communication capabilitiessuch as for e.g., upon clicking a specific paramedic identifyingmarker on the map, the Incident Commander will have theoption to call and interact with the paramedic to provideguidance and instruction as well as to provide patient taggingoptions. We also have developed symbol sets that can becustomized for different public safety stakeholder missionssuch as e.g., search and rescue.

The computationally-intensive tasks that need to be or-chestrated between the fog infrastructure and the core cloudcorrespond to the Panacea’s Cloud Analytical Engine, whoseblock diagram is shown in Figure 4. Our implementation ofthe analytical engine within the Panacea’s Dashboard has twomodes of operation viz., ‘Active’ and ‘Passive’ in order to helpIncident Commanders analyze vast amounts of informationand make strategic decisions in allocating resources at thevarious disaster scenes. It also enables long-term data loggingand archive capabilities that are critical for training and otherdisaster incident relief analytics purposes.

The active mode refers to the operational aspect that in-volves synchronous video communication and analysis ofscene information. The scene status analysis is presented inthe form of prioritized events and graph plots are generatedand viewed via the Dashboard page. Thus, the active modecan help the Incident Commander to co-ordinate the handlingof multiple incidents occurring simultaneously. The genesisof this occurs with an incident triggering staff assignment to

various scenes. The Incident Commander thereafter can use theoutput of the Analytical Engine to assist the highest prioritizedstaff/needs. The incident is assumed to be resolved at thescene when e.g., an ambulance takes the patient away fromthe scene for in-hospital care. As seen in the active modeoperation, the status of the responders, patients, and suppliesneeds to be tracked and analyzed for the Incident Commanderasynchronously through a passive mode of operation, whichsupports visualization tools and notification functionalities.

Our design of the Analytical Engine requires a close inter-action between the active and passive modes for effective co-ordination between the Incident Commander the Responders.The Data Logger module stores information involved withthe incidents, such as video feeds, patient logs, and suppliestracking information either in the fog infrastructure or in a corecloud. Thresholds can be set for the generation of prioritizednotification importance thus influencing active mode actionse.g., ambulance routing or supply restocking. Therefore, theAnalytical Engine’s outputs will affect the overall resourceallocation, ambulance routing, and supply restoration not onlyat the scene, but also across the disaster responder eco-system.It does so by catering to the need of first responder groups suchas Fire, Police, EMS, and health services to coordinate closelyrather than act as isolated units, and thus Federal Agenciessuch as DoD and FEMA are developing new standards forsuch data sharing.

D. Geolocation Service

The geolocation service we have developed in Panacea’sCloud possesses the ability to update patient information andGPS locations automatically. In order to track all patientlocations, virtual beacons are utilized to digitally label pa-tients versus using traditional cumbersome paper triage tags.Patient movement is determined through the triangularizationof paramedic HUDs and virtual beacons. The workflow shownin Figure 5 allows the system to differentiate each virtualbeacon and its status. Each virtual beacon possesses a uniqueMedia Access Control (MAC) address that is associated withits unique human-readable identifier. Once patients arrive ata hospital or when an incident is closed, the correspondingvirtual beacons are reset in preparation for the next set ofpatients. The virtual beacon information can also be usedto automatically update first responder status events (e.g.,inactive, responding) or medical supply depletion rate events.

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Fig. 4: Analytical Engine for Panacea’s Cloud showing Active and Passive Modes for incident scene handling and care co-ordination.

Fig. 5: Geolocation Service for Virtual Beacons Tracking using Wearable Devices in the Data-of-Interest Fog Infrastructure.

As the left side of Figure 5 shows, all virtual beacon MACaddresses and the corresponding unique identifiers are storedinto a database setup either in the fog infrastructure or in acore cloud. To avoid duplicity in virtual beacon usage, eachvirtual beacon has an attribute identifying whether the virtualbeacon is currently being used or is available for use. Thestatus/availability of each virtual beacon on the dashboard isdependent on this attribute. The virtual beacons continuallybroadcast allowing paramedics to locate them with their HUDsvia Bluetooth Low Energy (BLE). When a currently beingused virtual beacon is found by any one of the active HUDusers, the patient location is automatically updated on the map.

The virtual beacons in Panacea’s Cloud are Estimote Bea-cons that are a commonly used hardware for micro-locationstatus tracking and for collecting contextually relevant infor-mation about a region of interest in a mobile setting. Thevirtual beacon information, when used on a map, can bevaluable to quickly assess the scene context and visualizeimportant places/objects allowing for the initiation of appro-priate coordination measures. To have positional accuracy andenergy efficiency in an urban environment, we found thatthe BLE variety of Estimote Beacons are the most suitabletechnology due to their low consumption of power, both on thevirtual beacon hardware and on the HUDs of paramedics thatreceive the signals. In our current implementation with virtualbeacons, we use the Recon Jet heads-up display’s capabilityto dynamically detect Estimote Beacons via BLE.

Lastly, the geolocation service reduces the amount ofmanual labor required from responders when communicat-ing visual situational awareness to the Incident Commander.Moreover, Incident Commanders can also send notificationsto a responder’s hands-free HUD with new information anddata through the service. Thus, the geolocation service helpsincrease the scale of patients being cared and tracked, animprovement to current practice of using onerous traditionaltriage tags and verbal communication via radio handsets forthe difficult task of coordination of status across multipledisaster incident scenes.

IV. EXPERIMENTS AND RESULTS

In this section, we first evaluate the Panacea’s Cloud Dash-board usability and feature set compared to readily availablesolutions demonstrating the need for the dashboard. Next, wedescribe a set of performance tests which measured the infras-tructure hardware and provide use considerations from smartdevice communications and cloud-fog computing context inthe incident scene status analysis. Web resources for Panacea’sCloud features used in the experiments can be publicly ac-cessed at [13] by readers to obtain latest information.

A. Usability Evaluation of Panacea’s Cloud Dashboard

The usability evaluation was aimed to analyze and improveuser experience of Panacea’s Cloud Dashboard. The studyincluded a design review by the research team, task-based eye-tracking data collection, and post-task surveys and interviews

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with over 10 participants who could serve as Incident Com-manders in a real disaster incident event case. Participant in-clusion criteria were: range of job experiences, specialization,experience in using digital systems, and experience in handlingmass emergency situations. In the following, we discuss theresults obtained from user studies and controlled experimentswith the Panacea’s Cloud hardware/software components, andpoint out the benefits of our Panacea’s Cloud platform.

1) Dashboard Cloud-Fog Placement Evaluation: Our firstset of experiments compared different architectures for theDashboard placement in the hierarchical cloud-fog setup. Weevaluated the usability when the Dashboard was placed ineither the edge or cloud and studied issues that affect end-users’ perception of the system and their decision whether touse the system or not. When the Dashboard was placed in aremote core cloud server instance in Amazon Web Services,human subject participants experienced intermittent difficultiesin accessing the various Dashboard features during the testingin cases where the network connection between the core cloudand the fog infrastructure was emulated to be not resilientand adequately provisioned in terms of end-to-end availablebandwidth. However, the participants experienced increasedaccessibility and unanimously preferred a hierarchical cloud-fog setup where the Panacea’s Cloud Dashboard functionalityis located in the fog infrastructure. Although there is improvedaccessibility and preference in the fog placement case owing tothe benefits of reduced latency than a cloud placement case,the participants noted that energy sources and computationresource capacity at the edge may be limited. Moreover, theyexpressed a preference of a hierarchical cloud-fog setup whena high scale of data handling is needed. Specifically, theynoted the importance of cloud-fog resource orchestration andtraffic prioritization in a disaster network for delegation of dataanalytics tasks arising from geographically-distributed fogs insimultaneously occurring multiple incident response scenarios(as illustrated in Figure 2).

2) Dashboard Usability Evaluation: To analyze thePanacea’s Dashboard related: (a) task completion success(effectiveness), and (b) task completion times (efficiency),we conducted an extensive eye tracking study with the 10participants mentioned above. The usability evaluation sce-nario focused on a Tornado disaster incident. Task 1 requiredparticipants to become familiar with Panacea’s Cloud featuresand share their initial impressions. Task 2 focused on therole of the physician at the University Hospital. The scenariopresented a situation in which a tornado caused the roof tocollapse in a nearby area. The instruction was “You wantto communicate with paramedics in the field and survey theemergency situation. Please check the current status of theincident”. Then, users needed to find the paramedics at aspecific location (Task 3) and coordinate with them to answerthe following questions (Task 4) “How many injured are atthe Hall?” and “Who needs immediate treatment?” They wereasked to add patient information into the system. Task 5informed the paramedics that one patient had a change inher health condition, and users were asked to make changes(such as change the patient’s condition from ‘delayed’ to‘immediate’). Task 6 focused on the report to the Directorof the hospital (e.g., the number of patients that needed

immediate attention in the nearby area).Our results from the data analysis showed that the partic-

ipants hit a 90% effectiveness rate in completing the taskssuccessfully with a hierarchical cloud-fog platform. The av-erage time to complete pre-defined tasks was 24:03 minutesincluding 5:55 minutes to get familiar with the system as firsttime users. Participants stayed mostly on the index page andfocused mainly on the interactive map followed by video feedpage to communicate with the paramedic. Specifically, theinteractive map was the feature on which users focused themost, and their focus levels were followed by the legend ofmarkers and the left menu bar.

B. Performance Evaluation of Panacea’s Cloud Platform

1) Heads-Up Display Heat Evaluation: One of the chal-lenges of wearable technologies has long been recognized asheating issues that may affect user experience and could causeharm due to skin burns. Hence, we evaluated the Recon Jetused as the HUD by the paramedics, and we measured thetemperature differences of this device activity at the beginningfor the next half an hour sampled after each 5 minutes asshown in Figure 6a. We observed that the Recon Jet starts with75 degrees Fahrenheit initially and escalated to 102 degreesFahrenheit after 25 minutes. Note that we are using the ReconJet released to consumers early in summer of 2015. Neverthe-less, our results demonstrate that heating issues are the majorchallenge when used for audio and video communications,and that requires developing suitable engineering solutions thathelp in countering the undesired effects on users through heatmanagement schemes, e.g., in the communication protocolsand computation orchestration with cloud-fog resources.

2) HUD-to-VirtualBeacon Communication Evaluation:

Making sure the HUDs can find the virtual beacons in thedisaster scene is important to satisfactorily track status of pa-tients, paramedics and medical supplies. Hence, we measuredthe connectivity between Recon Jet (HUD) and the virtualbeacons. We found that the maximum distance from the virtualbeacons to the HUD is 11.38± 0.48 meters. Hence, if we putthe virtual beacons closer to the HUD, it is easier for the HUDsto find the virtual beacons. If the distance between the HUDsand the virtual beacons is closer to the maximum, it will takemore time for the HUDs to find these virtual beacons dueto a higher probability of a disconnection. Such an observedvirtual beacons detection behavior of the HUD are due to thefollowing trade-off: the shorter the distance between the HUDand virtual beacons, the stronger is the signal of these virtualbeacons. For example, if we put virtual beacons within 10%of the maximum distance from the HUD, the virtual beacon’ssignal strength is �81.51 ± 1.17 dB. However, if we putvirtual beacons within 50% of the maximum distance fromthe HUD, the beacons signal strength is now �95.1± 0.9 dB.Finally, if we put virtual beacons within 90% of the maximumdistance from the HUD, the virtual beacons signal strength is�102.1± 0.5 dB.

3) HUD-to-Router Communication Evaluation: Having astable audio and video session connection between the IncidentCommander and Responders’ HUD is crucial during triagecoordination in the fog infrastructure. To this end, we mea-sured the connectivity between Recon Jet (HUD) and wirelessrouters in a wide open area hosting a fog infrastructure. The

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Fig. 6: (a) Recon Jet heat experiment results. The cumulative distribution function (CDF) of: (b) the HUD-to-router connection throughput; the router-to-routerconnection throughput, i.e., TCP (c) throughput and (d) Round-Trip Time (RTT).

results obtained from our connectivity experiments are shownin Figure 6b. We found that the maximum distance for thecommunication between a router and the HUD is 145 ± 29meters. We then performed a video streaming experiment fromthe 10%, 50% and 90% of the maximum distance betweenthe HUD and the router. Based on our experiment results(see Figure 6b), we can see how the connection throughputdegrades with the distance increase. That translates in alow quality video communication between the HUD and thePanacea’s Dashboard. Thus, the effectiveness of patients triagecan also decrease.

4) Router-to-Router Communication Evaluation: For rea-sons similar to the previous experiment scenario, we con-ducted a router-to-router communication evaluation. Basedon our result, the maximum distance for the router-to-routercommunication is 674 ± 38 meters, which means that ourwireless mesh network is a scalable solution, e.g., we can coverseveral city blocks with a few routers. In the router-to-routerexperiment scenario, we perform the 100 MB file transferringover TCP protocol using Linux SCP tool from the 10%,50% and 90% of the maximum distance between the routers.Figures 6c and 6d illustrate obtained results: we again see howthe connection throughput, i.e., TCP throughput and Round-Trip Time (RTT), degrades with the increased distance factor.Moreover, it can even lead to disconnections, e.g., 60% ofthe time the routers were disconnected when transferring datafrom a location that was 90% of the maximum distance. Basedon our experiment results, besides scalability we concludethat lower throughput leads to a lower quality of the videocommunication, and higher RTT leads to a higher commandresponse time.

V. CONCLUSION

In this paper, we described our hierarchical cloud basedreal-time Panacea’s Cloud platform that provides augmentedreality benefits regardless of any physical network infrastruc-ture available in the surrounding environment. We describedhow our solution can operate with minimal human interactionthrough integration of a standardized Incident Command Sys-tem (ICS) with smart devices such as heads-up displays, virtualbeacons, and wireless mesh network elements. Our solutionadopts a hierarchical cloud-fog paradigm that allows for: (a)orchestration of real-time video feeds between the IncidentCommander and Responders wearing HUDs, (b) dynamic real-time tracking and replenishment of medical supply levels,patient as well as responder status, paramedic and patientlocations and (c) highly-integrated intelligent dashboard pro-viding visual situational awareness. Research questions ad-

dressed in this work relate to the design consideration ofa next-generation ICS that can be used for responding tosimultaneously occurring multiple incidents via a synchronousgeolocation service, and a map interface with intuitive symbolsand analytics of large data sets of incident scenes.

Through an extensive usability evaluation and controlledplatform experiments, we showed the benefits of the hi-erarchical cloud-fog platform in terms of ease-of-use andeffectiveness for an Incident Commander. Future work is tointegrate software-defined networking principles for disaster-incident response scenarios in the hierarchical cloud-fog plat-form communications to handle media-rich datasets.

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