next gen emergency-aware platform

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

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 than40 million next-generation (wireless) 9-1-1 calls.

Wire-LineCalls

Exchange

PSTN(Public

SwitchedTelephoneNetwork)

SELECTIVEROUTER

ANI(Automatic

NumberInformation)

ANI(Automatic

Location Information)

LocationDatabase

All Databases MSAG(Master Sheet Address Guide)

PSAP(Public Safety

Answering Point)

Computer-AssistedDispatchSystem

Caller LocationInformationCellular Network

Emergency Response

WirelessCalls

GPS/A-GPSData

RadiolocationData

Network-Based Data (Phase II) Cell-Tower Location Data

EmergencyServices

ANI

PSAP

Voice + ANI

PSAP

PSAP

Voice + ANI

911Tandem

Local Exchange Carrier Service

Voice + ANI

911


The major issues with traditional emergency response systems are lack of relevant and useful information and technical challenges with legacy systemsLack 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

timeto 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 becauseof 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 modulesEmergency response consisted of 3 modules – Device Module, User Module and Service Module.Scaling up of individual modulesis 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

Lenin VJ Nair

Fire hydrants?


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.

WeatherSensorFire/SmokeSensor

SEN

SOR

DAT

A

Video

ChemicalSensorAir QualitySensor

THE CLIENT’S EMERGENCY-AWARE CLOUD

MOBILEDEVICE

RULE

-BAS

EDD

ECIS

ION

S

REAL

-TIM

E SE

NSO

RS

WEB INTERFACE


Why Microservices and smart computing

Extreme interdependency of modules Upgrading or altering is difficult Lack of interconnectivity

TechnicalChallenges

Data-RelatedChallenges

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.


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 componentsDeploy and run the entire applicationas one big unit

With Microservice componentsDeploy 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

Page 1 Page 2 Page 3

Page 3 Page 5

Customer Product Cart

Rating Order Account

User Experience

Application Controller

Business Logic

Data Access

ApplicationController A

ApplicationController B

DataAccess

A

DataAccess

B

DataAccess

C



Customer Product Cart

Rating Order Account


Smart computing will provide actionable information to 911 operators and dispatchers

A new generation of integrated hardware, software, and network technologies that provide ITsystems 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

Audi

tabi

lity

Analysis Real-time analytics, big data tools

Alternatives

Business process management (BPM), rules engines, workflowMobility, smartphones, tablets

Access

Collaboration environment, dynamic case management, project portfolio management, supplier risk and performance management, BPM

Assembly

Process applications, BPM, dynamic case management

Actions

Sensors

RFID

M2M Video Monitoring

Social Media

Monitoring

GPS LocationSignals

Stat

us &

Co

ndit

ion

Iden

tity

and

Lo

cati

on

Physical Assets Human Capital Assets


Emergency response architecture – based on Microservices and smart computing

Cloud Connectivity

Gateway Connectivity

DirectConnectivity

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.

OrchestrationNode J.S

Emergency Response

Mobile

Authentication & AuthorizationSecured With

OAuth 2.0

Emergency Response

Application

Emergency Response

CoreServices

Device Management

Services

Mes

sag

e

Message

Event Services

Rule EngineServices

DataAnalytics

EventPublisher

NotificationService

Prediction Service

DataVisualization

External API

DATABASESERVICE

Dat

a

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

Lenin VJ Nair

fire hydrant info?


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 UX Touch 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

EmergencyResponse CoreDevice Management

Traditional Applications

UX

Laye

rBu

sine

ss L

ayer

Emergency Response Microservices API Within Layered Structure

Business Specific Microservices APIs


Next-generation emergency-aware services

Fully integrated communication system

Wired and wireless telephony,radio, text-based communicationfor 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 analysisSupport for reports, statistics

and operations analysis, including management dashboards

Planning toolsFor staff, vehicles, bases, and

overall equipment needed by emergency response organizations.

Highest guaranteed security standards

Backup, business continuity program (BCP), and disaster

recovery (DR)


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


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

Chennai

Johannesburg

New York

DallasTualatin

Amsterdam

London

THANK YOU!

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INDIA

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BengaluruThank You

next gen emergency-aware platform

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