08. Real Time Demographics in Smart Cities_Erez Weinroth_Trendit_Smart City 2015
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Transcript of 08. Real Time Demographics in Smart Cities_Erez Weinroth_Trendit_Smart City 2015
Oct 2015
Real Time Demographics in
Smart Cities
Dr. Erez Weinroth
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Big Data insights: “Holy Grail”
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Why ?
Air pollution is increasing. How can we quantify exposure of population to the pollution clouds ?
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How?
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What?
Home zone
Traject..s
Population dispersion
Socio eco levels
Work zone
Dwelling times
OD matrix
Religion
Population size
Products and results of tempo-spatial analysis
Population quantification
Socio economic levels
Origin (home) zone
Population dispersion
• Accumulative system
• Dwell and visit times
• Specific research
• Population clustering
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Real Time Demographics
channel 2 Live
Client • National Media
• Event Headquarters
• First Responders
Challenge • Identify Crowd Control
• Population management
• Geo-Temporal alerts
• Analysis and planning
Value • Quick and Measured response.
• Effective resource allocation.
• Mitigation of spillover effects.
Social Demonstration - Summer 2011
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Festival Management – Czech Republic 2012
Client
Challenge • Monitor open venue festival
participants
• Participant profiling
Value • Near real time updated data.
• Effective resource allocation.
• Quantified participant analysis
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Urban planning – Austria 2012
Client • Local Municipality
• Regional Municipality
Challenge • Commuters patterns
• Land use profiling
Value • Population hourly/daily commute pattern
• Land use management
• Transportation planning (origin destination matrix)
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Strategic Planning – Jerusalem, Israel 2010 – 2012
Client – EDEN, Municipal company • Developing the Jerusalem city center
• Project - Light rail train (a $1 Billion project)
Challenge • Monitor influence of the new light rail train on business due to mobility changes.
• How public institutions gain KPIs to manage and monitor a streets zone of private business?
Value • Population hourly/daily commute pattern
• Ongoing survey - identify commute shift
• Support resource allocation decisions.
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Origin of city center visitors
Jerusalem
Sumeria
Other settlements
Tel Aviv - Jaffe
Biet shemesh
Maale Adomim
Mevasert Zion
Bietar Eilit
Petach Tiqwa
Modien
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Origin of city center visitors – statistical areas
ארקמ
%1.
0 - %
0.0
%3.
0 - %
2.0
%5.
0 - %
4.0
%8.
0 - %
6.0
%2.
1 - %
9.0 %
2 - %
3.1
%5.
4 - %
1.2High
Low
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Crisis Management – Israel 2012
Client • The Home Front Command - IDF
Challenge • Monitor influence of conflict on local population
Value • Ongoing survey - near real time data.
• Effective resource allocation.
• Mitigation of spillover effects.
• Population hourly/daily commute pattern
• Ongoing survey - identify commute shift
• Support resource allocation decisions.
Population
Migration
Population Difference
Values
Morning Date 2012-11-17
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Population dispersion Modien residences 06:00
Legend
% from total
residences
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Population dispersion Modien residences 12:00
Legend
% from total
residences
The information contained in this document is Proprietary and Confidential.
Duplication in whole or in part is prohibited without express written permission of trendit Ltd.
Population dispersion Modien residences 20:00
Legend
% from total
residences
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Big data vs. Privacy
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• Accuracy
• Viable assumptions about 85% of an entire population can be achieved using data
compiled from just a single integration with a mobile network operator (covering less
than 15% of the population)
• Device & Network agnostic
• No need to install software on phones or to approve access on installed applications
• All networks and devices are supported (e.g. Smart phones. Legacy phones…)
• Patented and proven technology
• System developed, implemented and working
• Anonymity and security in accordance with highest regulatory standards
Unique Advantages
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Deliverables
Real Time People Meter
Event Real time data
Sites Real time
Comparison
Alerts per predefined
patterns
Accumulative Dwell Time
Meters Land
Usage/Value Segmental Metering
Predefined areas
comparison
Simple Pattern creation
Big Data Analytics
Predictive Analytics
Advance Pattern Creation
Statistical Modeling
Real Time
• Applications
• Dashboard API
• Reports
Accumulative
• Dashboard
• Dashboard API
• Reports
• Feedback (to Real-time Alert Application)
Big Data Analytics
• Reports
• Feedback (to Real-time Alert Application)