implement smart city solution at no cost - june 2015

8/20/2019 Implement Smart City Solution at no cost - June 2015

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Making our cities Safer, Smarter and

more Efficient

Multi Media Analytics for Safe Cities

1

Ivy Li, Managing Director and Co-Founder

[email protected]

mailto:[email protected]:[email protected]


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Mu t - ensor Ana yt cs romiOmniscient

Video

Comprehensiv eness

Specialty with30 patents

ComplexUse Cases

BroadIndustrySolutions

Benefts

Sound & Smell

Complex

Crowded

Smart City

Smart Campus

Face Tracking

SmartVMSna!ler

"ealistic

Automated"esponse

[email protected]

#$% ndustries

Complex 'ogicna!ler

R e c o g n i t i o n +

B e a v i

o r ! n a " y s i s

(well TimeManagementAccurate Tailgating)**+%,O!ect (etection in acrowdAggressi.e /e0a.iors1

Fig0ting2Man (own34u!lic 'ia!ility5

(ri.er Matc0

7"Oncremental

Cost

http://www.iomniscient.com/mailto:[email protected]:[email protected]://www.iomniscient.com/


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Future xpansion


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Security Related Applications

#. Identification and trac$ing of sus%ects&crimina"s&veic"es '("ac$"ist

data(ase) even in a crowded and uncontro""ed environment inc"uding

trac$ing on a *I

. Create a watc "ist data(ase for anyone wo acts sus%icious"y suc as

!(andoned (ect, "oitering&tai"gating, tres%assing, vanda"ism

/. 0nderstand Crowd (eaviors 'running crowds, crowd formed & or

dis%ersed sudden"y)1

2. 0nderstand te traffic f"ows and distri(ution of %eo%"e&veic"es during

emergency to e"% wit te evacuation

3. Recognition of figting or dangerous (eaviors (y using a com(ination

of video and sound ana"ytics.

4. Driver matc to eigten te security for ig"y secured environments1

%revent any I""ega" 5ar$ing outside im%ortant infrastructure & iconic site

6. 7anda"ism and mo$e and Fire Detection and recogni8e te cu"%rits

9. 5rotect (ridges and oter critica" infrastructure

:. ound !na"ytics for gunsot & screaming sounds & g"ass (rea$ing

etc

#;. me"" !na"ytics for a8ardous cemica"s

##. urvei""ance system ea"t cec$ to %revent camera tam%ering or

sa(otage

i8-Smart City1 C0ina3 Singapore3 /a0rain3 Mexico3 6


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Operations

Safety

< 5revent aw$ers, ad %osting, graffiti, and vanda"ism< Data co""ection (efore any construction %"an and street %"anning

activities = te use of a counting system to understand te traffic

f"ows and distri(ution of %eo%"e&veic"es at different times of te day.< Manage >vents inc"uding %rotesting events

< 5revent over crowding< Detect "i%s and Fa""s< mo$e and Fire Detection for outdoor environment

i8-Smart City6


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i8-"oad & Tra9c1 Australia3 Sout0 Africa3 C0ina3ndia3 Singapore3 /a0rain3 6

Security

Operations

Safety

< mo$e and fire detection %articu"ar"y in te tunne" environment< 5rotect (ridges and oter critica" infrastructure

< urvei""ance system ea"t cec$ to %revent camera tam%ering orsa(otage

< ?raffic management< >fficient ?raffic "igt management< Res%ond uic$"y to accidents< Road maintenance< 5revent so"iciting in %roi(ited areas< F"ood Detection 'wit video ana"ytics)< Detect %o""utants&emissions 'wit sme"" sensors)

< Detect Acrossing "anes on dou("e so"id "ines in tunne" or %roi(ited

sections< Incorrect direction on one way roads

< Co""ision %revention at "eve" crossings< Detect a(andoned o(ects or fa""en o(ects< Detect %edestrian aywa"$ing, s$ate(oarding etc< 5revent %eo%"e crossing te maor igways or entering te tunne"s

< 5ar$ing vio"ations and at te Ao sto%%ing 8one< Detect i""ega" driving, e.g. s%eeding, red "igt vio"ation, near misses etc< 5revent certain veic"e ty%es on certain road sections 'e.g. (us "ane)

La Enforcement


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'ocation :se Case xamples /ene;tsFreeway Recognise the plate and car profle o any cars that have

violated the trac regulations such as speeding, illegal lanecrossing (U turn), vehicle stopped and accidents.

Law enorcementRoad saety

Understand trac ow during di!erent times o the day andcan "e "ro#en down "y the type o users (the type ovehicles). $his data can "e used to improve the roadcondition such as to divert trac "eore it gets congested.

%perational&ciencyRoad 'lanning

ntersection

Recognise the plate and car profle o any cars that haveviolated the trac regulations such as red light violation,vehicle stopped at the yellow "o, illegal lane use (change

lane when there is dou"le solid line* turn on a no u+turn lane*go straight on a let turn lane)

Law enorcementRoad aety

Understand the trac ow inormation o "oth pedestrianand vehicles* gather the near misses data etc to improve thetrac light re-uency as well as the road saety

%perational&ciency

'edestrianal#way

Recognise person o interests using /Facial Recognition in a0rowd1*

ecurity

Recognise suspicious "ehaviours and enrol these aces intothe watch list data"ase and trac# them around

ecurity

$unnel Recognise the plate and car profle o any cars that haveviolated the trac regulations such as vehiclestopped2accidents* allen o"3ects4lert or any "icycles and pedestrian in the tunnel

Law &norcementRoad aety

5etect 4verage peed Road aety

5etect smo#e and fre Road aety

%verall 0amera 6ealth 0hec# (alert or tem erin , lost si nal, etc)

i8-"oad & Tra9c1 Sample :se Cases


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Security

< 5etection o people loitering near an 4$:

< Let o"3ect detection in their lo""y areas

< :an down detection or their own guards< mmediate identifcation o suspects2criminals using acial recognition (even in

uncontrolla"le and crowded environment)

< ;etter access control including the prevention o tail gating or highly securedareas (such as the room "ehind 4$: to replenish cash)

< 'rotection o assets (e.g. re+possessed vehicles)

< 9rati and nance Customer ervices = e.g. immediate identification of 7I5 customers using facia" recognition

Counting and demogra%ics to o(tain re"evant mar$eting data

ueue Management to understand te average waiting time for eac ueue and to a"ert inc"uding drive-in

management for o%ening additiona" service counters during te (usy ours

urvei""ance system ea"t cec$ to %revent camera tam%ering and sa(otage

Safety

Detecting if someone is "ingering or stationing at te !?M area for a "onger %eriod of time 'e.g. (eggar s"ee%ing

inside te !?M area)

Detection of vigi"ance and A%erson of interest using Facia" Recognition in a crowd

Detection of water s%i""s


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< T0eft from ATM skimming is approac0ing


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Anti-skimming

5etection o oreign o"3ect2s#imming devices on card slot> pin pad.

4in S0ield5etection o pin shield wearing out

Cas0 (ispenser5etection o cash trapping device 'revent tailgating activity during cash replenishment

'oitering around ATM

5etection o suspicious human "ehavior around the 4$:. 'eft O!ect (etection

5etection o let o"3ect at 4$: area including2detecthomeless people.

Face (etection

mmediate 4lert or people who wear mas#s2helmets

2sunglasses when entering the "an# > near an 4$: Facial "ecognition for V43 @atc0list etc

< dentiying potential threats near the 4$:

< dentiying "lac#listed individuals near the 4$:

< 5etect person attempting to loo# over the shoulder

Camera ealt0 C0eck

ATM and Asset 4rotection


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Security

Operations

Safety

< !ccess Contro" e.g. DriverMatc< Many-to-many Face Recognition system

< License 5"ate Recognition< 5erimeter 5rotection & Border Contro"< !sset 5rotectionE %revent ?eft&vanda"ism 'e.g. stoc$ room or

wareouses tat (ui"d firearms)< and More

< Rea" time video ana"ysis and forensic ca%a(i"ities to %rocess

"arge uantities of arcived video< Mo(i"e video ana"ysis system< urvei""ance system ea"t cec$ to %revent camera tam%ering

or sa(otage

< mo$e and Fire detection in wareouses wit ig cei"ings< Detection of a(andoned o(ects< 5rotect air force runways to ensure tey are c"ear of o(struction

i8-(efence1 Singapore3 Australia3 gypt3 /a0rain3 Borea36


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• "i% G fa""s & Man-Down

• vercrowding and congestion detection

• mo$e and Fire detection

< Face or 5"ate Recognition for $nown sus%ects&veic"es

< !(andoned (ects in crowded %"aces

< 7anda"ism detection

< ?res%assing and ?ai"gating

< Intrusion detection

%perations

aety

• ?raffic Management&dwe"" time

• License %"ate recognition or DriverMatc

• 5ar$ing 7io"ations

• 7eic"e Counting

ecurity

conic Sites 2 Criticalnfrastructure1o >m%ire tate Bui"ding, ydney Har(or Bridge, !(u Da(i '!DI!), uc"ear5"ants,


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9eniusi?+@AB2@CB

%"3ect detection in

crowded comple scenes(patented)

%nlyi%mniscient

marti?+@@D2@EB

4dvanced ;ehavior4nalysis

E + companies

4veragei?+@BB2@@B

;ehavior 4nalysis("ased on


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1"

#ace Recognition in a crodMulti$lingual License %late

Recognition

Compre0ensi.e "ecognitionCapa!ilities


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i?+6aw# (nternationally patented)

5etection G Recognition

... %n the same camera

$$ times Sa.ings on Dmegapixel Camera for

Storage & /andwidt0

Automated

Sur.eillance

' a t e n t e d


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4 4 ' I(4utomated urveillance 4ction 'latorm)

@ i n n e r $

= E

T 0 e A u

s t r a l i

a n & n n o

. a t i o

n

C 0 a l l

e n g e

' a t e n t e d


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ndustry Trends


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&1

Complex :se Cases

/ig (ata Analysis

'atterns o correlations "etween weather data, near"y ma3or event and incidents(or eample) can show possi"le cause o incidents.

4redicti.e Tool $he latest accident highlights that this was a dangerous 3unction. $he system cananalyJe all the near misses that have occurred in that area over the last month,

providing the road trac management team the inormation necessary todevelop strategies or mitigating the pro"lem.

4rompt "esponse4n accident is detected on the 00$< camera at a road 3unction. t highlights thatthere is a fre in one o the vehicles. $he video o the accident scene and itslocation is automatically sent "y the system to the nearest Fire ;rigade and also

to the nearest 'olice vehicle.


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4utomatic ystem in a controlled environment E5 'hoto to 'hoto comparison Full rontal view

'erson has to stand still %ne ace at a time with a very "ig ace >

high resolution (up to BB piels "etweenthe eyes)

4utomatic ystem in an un+controlledenvironment

Using urveillance 0ameras ider ace angle (B degrees in anydirection)

5


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@. Use o data"asesK 4gainst nownFaces2'lates Using photos (good or controlled environment) Using


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&!

7ideo

Cost ecti.e Smart Arc0itecture1 SmartVMS na!ler

mplement ntelligent System at 7"Oncremental Cost

http://var/www/apps/conversion/tmp/Videos/IQ-Hawk%20(Loitering%20and%20LPR).avihttp://var/www/apps/conversion/tmp/Videos/IQ-Hawk%20(Loitering%20and%20LPR).avi


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'(e )ideo *tility

' a t e n t e

d

t St tG


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@. 4gree on 0ustomer8s wish list and 'riorities (primaryo"3ectives)

E. 5&97 to accommodate or uture epansion(secondary o"3ectives)

. 0hoose the right applications, sotware and systemsA. 4gree with the re-uired processes > operational

approach (i.e. automated responses)D. 'lace the devices or cameras accordingly to meet the

re-uired o"3ectivesH. 5esign the networ# (0ost e!ective solution withmart


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:479 ;9 54$4 :4LL > :&4779FUL

< i%mniscient mart 0ity deploymentuses video data to complement tetand numerical to provide "ig dataanalytics or a city environment

< $he wide range o i%mniscienttechnologies or smarter, saer citiesand the integration with otherhardware and sotware systems isshown in the diagram

< 4ll current ;ig 5ata analysis uses $et5ata

< i%mniscient can capture MeaningfulMultimedia Metadata )MMM) romvideo, sound and smell sensors

< iOmniscient tec0nology ;lls a gap

for !ig data engines

< ;y intelligently etracting meaningulmetadata, the system reduces theresources re-uired or ;ig 5ata4nalysis

< $his is particularly useul in large

comple systems that are processinglarge volumes o data as smart city


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< $echnology leader in /4nalytics1 solutions using video, sound and smell

analytics. ell renowned in the mar#et as technology leader* "ac#ed "ynumerous industry awards and testimonials rom high profle customersaround the world

< orld8s most comprehensive, relia"le and mature 5* 'rotectcustomer8s investment as the product never "ecomes o"solete* 9row withcustomers + a"le to address today8s pro"lems as well as tomorrow8s

< n+depth eperience in large deployment o comple use cases includingmany smart city and transit pro3ects

< %ngoing engineering through A 0entres in ydney, $oronto, 0hennai andingapore. %ver ABB person years o development e!ort. 'rovide EANsupport worldwide

&+

A!out iOmniscient


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Disc"aimerE ?e information contained

in tis document is intended on"y for te

use during tis %resentation and sou"d

not (e disseminated or distri(uted to%arties outside tis %resentation. o

:

%LU$%7


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-ompre(ensive solutions from

iOmniscient for t(e Oil /as industry


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-ompre(ensive Safety System from iOmniscient

1000km of track t(e train takes 2 km to stop

t(e system provides early arning of largeo34ects on t(e track


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iOmniscient protecting tourists and orkers

System ensures no 3ags5 parcels are a3andoned

in t(e pu3lic areas t(e system looks for 3lacklisted people of interest


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iOmniscient tec(nology used to improve safetyand efficiency across + s(ip 3uilding yards


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iOmniscient systems protect t(evalua3le assets at t(e facility

'(e system ensures t(at t(e

perimeter is ell protected and t(at

unaut(ori6ed personnel cannot

enter t(e facilities


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Antalya Airport on t(e Aard for t(e 7est Midsi6e Airport in

Europe 3ased in part on its intelligent security system


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Ontario %oer /eneration (as 8i i9


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Samsung Stadium, Seoul, (as 8i i9


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iOmniscient systems protect A'Ms

against skimming and fraud across 9atar


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Com%"ete %ac$age for video (ased

ana"ytics for Convention Centers and

>i(ition Ha""s from imniscient

untec City, inga%ore as Hi I


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:u3ai Electricity and ;ater Aut(ority (as 8i


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iOmniscient reduces t(e costs ofmanaging prisons in )ancouver


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?uestions

> 7et teps

ContactE [email protected]
mailto:[email protected]:[email protected]

implement smart city solution at no cost - june 2015

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