“Cloud  Compu*ng  for  Public  Safety  Applica*ons  and  Communica*ons”  

Clinical Need:• When working with critical-care patients, doctors and

nurses face many co-ordination challenges • Augmented reality based technologies can

help to stay updated on the status of patients and care levels

• Need is even more critical in natural disaster scenarios

• Large volume of patients with varying states of injuries

• Effective co-ordination of limited medical staff and supplies

• Communication infrastructure may have been destroyed

Figure 1: Mercy Hospital in Joplin MO, After tornado impact in 2011

Figure 2: Incident Scene needing Situational Awareness

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Solution:• Provides an “infrastructure-independent” way for

incident commanders to communicate with first responders in an incident or natural disaster

• Easy-to-use interactive interface • Incident management • Patients status tracking • Supplies replenishment • Responder co-ordination

• Incident Command System (ICS) applications with integration of Internet of Things (IoT)

• Replaces cumbersome paper tags for triage

Contributors: John Gillis, Prasad Calyam,Olivia Apperson, Salman Ahmad, Rui Huang, and Duo Jiang

Supported by: Wallace H. Coulter Foundation and University of Missouri

Augmented Reality for Mass Casualty Disaster Triage and Co-ordination

Commercialization Pathway:• $8.3bn industry (according to IBIS World Report, 2014)

• 31.8% or $2.6bn in disaster relief and emergency services • Interest in entrepreneur space

• Wearable Technology & Augmented Reality Apps

Prasad  Calyam,  Ph.D.  Assistant  Professor,  Department  of  Computer  Science  

 October  24th  2016  

Sponsors:  Coulter  Founda1on,  Na1onal  Science  Founda1on  

Impact  of  a  Tornado  Joplin Tornado (May 22, 2011)

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The  Problem  70%  of  first  responders  admit  that  handheld  radio  communica<on  is  the  most  frequently  used  technology  during  a  mass  casualty  incident  

Our  Solu<on  Overview  •  Panacea’s  Cloud  improves  situa<onal  awareness  and  integra<on  of  medical  triage  services  – Operates  in  an  infrastructure  independent  manner  – Augmented  Reality  for  “live”  mul<ple  incident  triage  

•  Overcomes  limita<ons  with  using  hand-­‐held  radio,  paper  tags  

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Network  Edge  Compu<ng  to  support  the  “Internet  of  Things”  

•  Logical  layers  of  a  Visual  Cloud  Compu<ng  (VCC)  suppor<ng  infrastructure  showing  the  rela<onships  between  end-­‐user  things,  fog  computa<on,  and  core  cloud    

Project Description - 4

such as web browsers with interfaces to explore the outputs, or application client software that downloads the data for local exploration, or appliances that use protocols such as VNC, RDP or PCoIP [49] to access virtual desktops with the exploration software. The consumption fogs could also host caching services to bring the processed data closer to the user thin-clients and reduce the need to have round-trip requests to the cloud. It is possible that the consumption phase involving an expert analyst may result in active use of the caching services that leads to repost of data to the Fog Computation Layer for further processing as part of deep exploration activities.

Figure 2. Logical layers of a VCC supporting infrastructure showing the relationships between end-user things, fog computation, and core cloud. The management layer controls where resources are

provisioned and how data flows are routed with SDN between fogs and the core cloud.

In the Fog Computation Layer, one service manages the small instance processing in conjunction with directives from the Unified Resource Broker (URB) in the Cloud/Fog Management Layer, and another service acts as the gateway to move data from the fog to the Cloud Computation Layer via a high-performance network overlay setup with SDN. The Cloud Computation Layer leverages open/proprietary software-defined infrastructure controller technologies (e.g., VMware Horizon [11], OpenStack [12] and OpenDaylight [13]) to manage the virtualized computer and network resources in the cloud/fog infrastructure. At the Cloud/Fog Management Layer, the scalable computing services, software-defined monitoring services (enabled e.g., by Narada Metrics [15], perfSONAR [16]) as well as the URB resource allocation algorithms orchestrate the computation placement either in the fog or in the core cloud. Thus, the Cloud/Fog Management Layer transforms the core cloud and fogs into a ‘hierarchical cloud infrastructure’. It allows the management services in the public clouds to seamlessly operate close to the user collection/consumption sites for end-to-end orchestration and dynamic control of data processing locations. In addition, URB serving as the “brain of the cloud/fog infrastructure” can be enhanced with novel resource allocation algorithms to efficiently and effectively manage the dynamic distribution of the computer vision application processing workload to meet the first responders QoE requirements for visual situational awareness and processing response time.

2.2 Proposed Approach to Build the Enhanced Institutional Cloud/Fog Infrastructure Existing Science DMZ Infrastructure at MU (Supported by NSF Award #OCI-1245795): MU is one of the few U.S. research university campuses that for several years has had a separate research network “Rnet” in addition to the traditional campus enterprise network. Rnet has an autonomous set of virtual LANs (local area networks) that co-reside within the IP (Internet

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Research  Results  –  MO  Task  Force  1  Killer  Experiment  

•  Created  a  real-­‐<me  geotracking  service  for  contextual  incident  markers  in  a  search  and  rescue  training  simula<on    –  3.6X  faster  data  entry  <me  per  incident  than  the  Garmin  System  

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Testbed  Experiences  Summary  

•  Handling  scope  expansion  -­‐  Architecture  – Different  researcher  requirements  for  cloud  infrastructure  – Limita<ons  in  ‘Things’  (e.g.,  wearables,  virtual  beacons)  

•  SoSware  Sustainability  – Separate  code  bases  for  different  experiment  trials  – 10  +  students  contribu<ons  

•  Simula<on  ßà  Real-­‐world  Experimenta<on  – Scale,  Realism,  User  engagement,  Security  

• Mul<ple  stakeholder  collabora<on  – City  managers,  Public  safety  professionals,  SoZware  developers,  Hardware  vendors,  Campus  IT,  …  

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