Multi-media Analytics and Cognitive Computing to Provide Safe Secure Cities (Stephen Russo...

Guidance as of 1

IBM Multi-Media Analytics & Cognitive Computing for Safer Cities IT Arena Lviv, Ukraine Oct 2016

Stephen Russo, WW Dir Public Safety Technology Solutions

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So what is Multi-media Analytics

Multi-media implies information and data coming in many formats from various

types of sensors Visual, audio, information systems

Video and Geospacial Information

Speech recognition, transcrition and contextual understanding

Computer Vision analysis and Deep Learning

Over time, cognitive systems will simulate more of how the brain actually works and

help us solve the world's most complex problems by penetrating the complexity of

Big Data


So what is cognitive computing?


Pioneers and significant events have shaped where we are

today…

1974- 1980: 1st AI “Winter”

1950s 1960s 1970s 1980s 1990s 2000s 2010…

1956: “Birth” of AI

John McCarthy coins term

artificial intelligence (AI) at

Dartmouth Conference

1965: First Expert System

Stanford team led by Ed

Feigenbaum creates DENDRAL

1987- 1993: 2nd AI “Winter” 1950: Turing Test

Turing introduces way to

test for intelligent behavior

1990s: AI on www

AI-based extraction

programs prevalent on www

1997: Deep Blue

IBM Deep Blue defeats

World Chess Champion

2011: Watson

IBM’s Watson competes

and wins on Jeopardy!

2005: Autonomous Car

Stanford-built autonomous car wins

DARPA Grand Challenge

2014: Key Market Moves

IBM formation of Watson Group and

Google acquisition of Nest Labs


The three capability areas of cognitive systems resemble the

human learning and thinking processes

Practical Industry Examples for Safety and Security

Collecting Information about what is happening in the

world around us

Index, tag and manage massive amounts of Sensor data


Surveillance systems today

7 IBM Confidential

Estimate show there are ~845 Mil surveillance cameras in use globally

~2.4M new cameras are being deployed annually (Does not include Cell, personal)

Over 10 Billion hours of footage being recorded weekly

Only 3% of those cameras and sensors have any sort of intelligence

Who is watching all this video???

Majority are passive recording devices


Times Square NYC – Face, Car, and Pedestrian Detection and tagging

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Intelligent Vision Analytics

Smarter

Analytics for Cameras in Motion

Full Event Indexing

Advanced Color Recognition

Sophisticated Behavioral Alerts

Compound Alerting

Cognitive learning “Deep Learning”

Offline file ingestion

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Improves the ability to understand and respond

Rapid investigation

Combine alerts to reduce false notifications to personnel to improve taking action

Advanced analytics developed for urban environments and mass transportation to identify individuals versus “blobs”

Months to hours

Reduce the investigation time from months to hours based on finding matches to indexed data

Operational optimization Situational awareness


Data Analytics: Objective and Continuous Interpretation

Camera Docking

Sensor Data

High Value Intelligence Exploration (Lead Generation)

Intelligent Object Redaction

Easy Retrieval of incident videos

Collect Capture Analyze Manage

Captured multi-media

When a police officer returns to a precinct, • A BWC automatically connects to a cloud and uploads recorded data through a secured

Wi-Fi connection or a docking station • A set of tagging analytics automatically analyzes the data and produces Smart Insight

Tags • A set of insight analytics automatically highlights key incidents and cross links and

correlates them with other reports and social media from the same incident

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Sunglasses

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Light skin tone + bald + blue torso


Demography Attribute Tagging - Gender


Demography Attribute Tagging - Age


Demography Attribute Tagging - Asian


Demography Attribute Tagging - White


Demography Attribute Tagging - Black


Enable Easy Retrieval of Incident Videos


Enable High Value Intelligence Exploration and Discovery

Automatic Notification

No Record Located

Face Matching > Threshold Face Matching < Threshold

Enrolled Face vs. captured face


Enable Intelligent Object Redaction

The system allows selection and refinement of privacy protection for individual objects in addition to full frame redaction


Enable High Value Intelligence Exploration and Discovery

Use Cases: Investigation Based on Vehicle Appearance

Classifying Vehicles Measuring Actual Vehicle Height/Length and Speed


Extensible to Dash Cam: Object Detection


Extensible to Dash Cams


Video analytics help identify unexpected movements such as

a rapid gatherings to better manage the crowd

Monitoring with video analytics

Identify what to watch (i.e. people gathering in certain locations or any flash mob situation)

Determine the situation for awareness (i.e. certain number in one area over a period of time)

Notify personnel to address crowd management

Identify unexpected crowd movements

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