Here are the details of the next-gen emergency-aware platform.

1. Next-Gen Emergency-Response Platform Based
on Microservices and Smart Computing

2. Confidential & Restricted
9-1-1 has long been the standard emergency response system in the US
Started in 1967, 9-1-1 emergency number was
made available to 50% of the population in next 25
years.
By 1999, the availability was 93% and by 2014,
99%.
An estimated 240 million calls are made to
9-1-1 in the US each year. In many areas,
70% or more are from wireless devices.
The client supports three million 9-1-1
emergency calls a year and delivers more
than
40 million next-generation (wireless) 9-1-1
calls.
Wire-Line
Calls
Exchange
PSTN
(Public
Switched
Telephone
Network)
SELECTIVE
ROUTER
ANI
(Automatic
Number
Information)
ANI
(Automatic
Location Information)
Location
Database
All Databases
MSAG
(MasterSheetAddress Guide)
PSAP
(PublicSafety
AnsweringPoint)
Computer-Assisted
Dispatch
System
CallerLocation
Information
CellularNetwork
Emergency Response
Wireless
Calls
GPS/A-GPS
Data
Radiolocation
Data
Network-BasedData (Phase II)
Cell-Tower LocationData
Emergency
Services
ANI
PSAP
Voice + ANI
PSAP
PSAP
Voice + ANI
911
Tandem
Local Exchange CarrierServiceVoice + ANI
911

3. Confidential & Restricted
The major issues with traditional emergency response systems are lack of relevant
and useful information and technical challenges with legacy systems
Lack of interconnectivity
Traditional emergency response had
very minimal automation because of
less connectivity. Also it was very
difficult to customize as and when the
need arises because of monolithic
architecture.
E.g., During 9/11 attack, many
fire-fighters lost their lives in a
building collapse as their systems
were not integrated with the
warning system issued by the
NYPD.
Lack of relevant Information
The amount of information received
from traditional emergency response
is limited as it is dependent on the
amount of information conveyed
through a call with some additional
supplementary location information.
E.g., The average 911 response time
to high-priority incidents is 11 minutes.
Majority of this time goes in explaining who
the victim is, giving the exact location, the
nature of the emergency, etc. Other
supplementary information, like
temperature, fire threat, etc., is also not
easily available
Lack of real-time intelligence
The traditional emergency response
could not predict a situation because
of the lack of real-time user data.
This resulted in slower communication
during emergency and non-proactive
action.
E.g., During Hurricane Katrina,
thousands of volunteers and amateur
radio operators came to the area.
However, their efforts were scattered
as there was no clear information on
the worst affected areas.
Extreme interdependence of
modules
Emergency response consisted of 3
modules – Device Module, User
Module and Service Module.
Scaling up of individual modules
is not possible.
With newer sensors and social
media information being
constantly integrated, the non-
modular nature of the
architecture causes technical
challenges.
Upgrading or altering is
difficult
Entire web application
needs to be shut down
even for a minor change
in one of the modules.
E.g., To update the location and
capacity of newly installed water
hydrants in just a couple of
blocks, the entire application
needs to be shut down which is
difficult for a mission critical
application.
Challenges With traditional
Emergency Response

4. Confidential & Restricted
The next-generation emergency response systems will address challenges
faced by traditional systems with Microservices and smart computing
Next-gen emergency-reseponse service is a
customizable, context-aware machine-to-
machine (M2M) solution, leveraging smart
objects and sensors to provide improved safety
and security, better situational awareness, and
improved risk management.
Next-gen emergency response allow for
additional information sources to be
plugged in easily because of its
Microservices architecture while
enhancing reliability and scalability.
Built-in smart computing surface relevant
information for 911 call handlers and
dispatchers. Machine learning algorithms
provide predictive information enhancing
quality of service for call handlers.
Weather
Sensor
Fire/Smoke
Sensor
SENSORDATA
Video
Chemical
Sensor
Air Quality
Sensor
THE CLIENT’S EMERGENCY-AWARECLOUD
MOBILE
DEVICE
RULE-BASED
DECISIONS
REAL-TIMESENSORS
WEB
INTERFACE

5. Confidential & Restricted
Why Microservices and smart computing
Extreme interdependency of modules
Upgrading or altering is difficult
Lack of interconnectivity
Technical
Challenges
Data-Related
Challenges
Lack of relevant Information
Lack of real-time intelligence
MICROSERVICES
SMART COMPUTING
Each Microservice is independent of
the other one – this allows for
individual altering, upgrading, and
scaling up of module without
disturbing others.
Building and managing
Microservices-based emergency
response is easier in a cloud-
based architecture.
Allows for integration of third-party
API (application programmable
interface).This gives access to third
party data sources.
Allows real-time change in data in
emergency response without
changing the entire code, unlike the
previous version.

6. Confidential & Restricted
Microservices will allow for easy integration with multiple systems while
maintaining a decoupled architecture
Microservices architecture is a service-oriented architecture composed of loosely coupled elements that have bounded contexts. These services
are small, highly decoupled and focus on doing a small task thereby facilitating a modular approach to system-building.
Emergency Response is built using a
Microservices architecture which is a
software architecture style in which
complex applications are composed of
small, independent processes
communicating with each other using
language-agnostic APIs.
Without Microservice components
Deploy and run the entire application
as one big unit
With Microservice components
Deploy and run individual parts of a solution
separately and independently
Microservices will also improve reliability since
individual components can continue to operate
even if parts of the system fail
Deployment Package Deployment Package
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Customer Product Cart
Rating Order Account
User Experience
Application Controller
Business Logic
Data Access
Application
Controller A
Application
Controller B
Data
Access A
Data
Access B
Data
Access C
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Customer Product Cart
Rating Order Account

7. Confidential & Restricted
Smart computing will provide actionable information to 911 operators and
dispatchers
A new generation of integrated hardware, software, and network technologies that provide IT
systems with real-time awareness of the real world and advanced analytics.
It helps in making more intelligent decisions about alternatives and actions that will optimize business processes and
business balance sheet results.
Real-time or in-memory analytics is a key technology for making sense of the transactional data coming from awareness
devices.
Accessing multiple sources of data and being able to surface the most relevant data is the focus of smart computing in emergency response.
Awareness
Sensors, radio frequency ID, video monitoring, machine-to-machine, global
positioning system data, social intelligence, data repositories
Auditability
Analysis Real-time analytics, big data tools
Alternatives Business process management (BPM), rules engines, workflow
Mobility, smartphones, tabletsAccess
Collaboration environment, dynamic case management, project portfolio
management, supplier risk and performance management, BPM
Assembly
Process applications, BPM, dynamic case managementActions
Sensors
RFID
M2M Video Monitoring
Social Media
Monitoring
GPS Location
Signals
Status&
Condition
Identityand
Location
Physical Assets Human Capital Assets

8. Confidential & Restricted
Emergency response architecture – based on Microservices and smart computing
Cloud Connectivity
Gateway
Connectivity
Direct
Connectivity
Smart Computing – Context-aware engine receives data from external sources and discovers the
category of data like law, fire, medical, etc. It then uses different algorithms to enable quick and
efficient incident response, e.g., location and distance of nearest water hydrant and its capacity.
Orchestration
Node J.S
Emergency
Response Mobile
Authentication &
Authorization
Secured With
OAuth 2.0
Emergency Response
Application
Emergency
Response Core
Services
Device
Management
Services
Messa
ge
Message
Event Services
Rule Engine
Services
Data
Analytics
Event
Publisher
Notification
Service
Prediction
Service
Data
Visualization
External API
DATABASE
SERVICE
Data
Message
Context-Aware Engine
Context-Aware Service – Receives data from external source, predicts the context
and sends notifications to the relevant user, e.g., based on the feeds coming from
building CCTV cameras, sensor information, social media, etc. it can notify fire
department of a possible fire even before somebody calls and asks for help.
External Data Source Service - Integrates third party APIs
enabling access to external sources of information like air quality,
weather information, flood levels, hydrant information

9. Confidential & Restricted
Emergency response using Microservices and smart computing - benefits
Proactive monitoring of critical infrastructure,
assets, and resources
Improved asset utilization and performance
because of layered architecture of
Microservices
Improved enterprise risk management and
situational awareness
Intelligently process multiple data elements
enabling in-depth logging, trending and
analytical capabilities
Increased safety and security of
employees and assets
Emergency Response UXTouch Point Apps/Devices
Touch-Point-Specific Microservices APIs
Map Display Social Media Feeds Notifications/SMS
Reporting/Analytics Local Storage
Alarm Event Rule Engine Context Aware
Event PublishingExternal Data Source
Emergency
Response CoreDevice Management
Traditional Applications
UXLayerBusinessLayer
Emergency Response Microservices API Within Layered Structure
Business Specific Microservices APIs

10. Confidential & Restricted
Next-generation emergency-aware services
Fully integrated communication
system
Wired and wireless telephony,
radio, text-based communication
for incoming and outgoing communications,
including new channels based on visual components
and social media.
Geographic information
systems (GIS)
Location and positioning solutions such as
call and asset location, vehicle positioning
and tracking, possibility of adding multiple
layers of information from different sources,
including 3D views, CCTV, traffic, and
weather information.
Solutions for all
operational phases
Call acceptance, resource
dispatching, and event management
to case completion and evaluation
Reporting and analysis
Support for reports, statistics and
operations analysis, including
management dashboards
Planning tools
For staff, vehicles, bases, and overall
equipment needed by emergency
response organizations.
Highest guaranteed security
standards
Backup, business continuity program
(BCP), and disaster recovery (DR)

11. Confidential & Restricted
A next-generation emergency response in action
Take the example of a hurricane hitting
the Atlantic coast. The next-gen
emergency response can integrate air
quality data, sensor data, current weather,
live-stream from nearby cameras, and
social media information.
Emergency response can directly take
input from various CCTV sources, social
media feeds, sensors etc., and identify
secure spots for relocation.
It can also integrate all the wireless and wired
communications coming its way to dispatch
the relevant help at the required places.
Based on the analytical reports from
emergency response, danger zones can be
identified and monitored. On the basis of
forecast, alerts can be issued and services
dispatched even before the incident.
EMERGENCY ALERT
SYSTEM
Issued a Tornado Warning

12. Confidential & Restricted
Future of emergency-aware services
Emergency response is evolving into a
plug-and-play architecture model where
other services can easily leverage
features of the next-generation
emergency response platform.
The future of emergency response may be
deployment of artificial intelligence
robots and a system which could provide a
more streamlined way for robots and drones
to communicate with humans in difficult
situations, including during emergency-
response operations. Real-time or in-memory
analytics is a key for making sense of the
transactional data coming from the devices.
The emergency-aware
services can be further used
across industry verticals like
manufacturing, mining, etc., for
safety and faster
communication with less/no
customizations in various
services.
Ability to communicate to 911
through any connected device and
share any form of data. This is done
using emergency services IP network
(ESInet) which in turn needs 911
services to be IP-based.
911

13. Chennai
Johannesburg
New York
Dallas
Tualatin
Amsterdam
London
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