Distributed and heterogeneous data analysis for smart urban planning
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Transcript of Distributed and heterogeneous data analysis for smart urban planning
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Distributed and heterogeneous data analysis for smart urban
planning
Eduardo Oliveira Michael Kirley
Tom Kvan Justyna Karakiewicz
Carlos Vaz
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Outline
• Living Campus Project
• Research Ques:ons
• Related Work: an introduc:on to middleware
• Device Nimbus
• Case Study: proof of concept demonstra:on
• Conclusions and Future work
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Living Campus
University campuses represent an urban space that in many circumstances reflects what is happening on a larger scale across a city.
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Living Campus
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Living Campus: an interdisciplinary perspec:ve
[architecture]
• Architects, planners, and urban designers typically require access to spa:al and temporal data, which considers how people perceive, behave and interact with their environment
• Data collec:on and analysis is rarely pitched at the `micro’ scale
[computer science]
• PaSS = People as Sensors
• Large amounts of data from social networks, mobile devices and sensors
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Guiding research ques:ons
Is it possible to automa:cally collect, combine and analyze data from sensors (e.g. environmental sensors) and crowd-‐sourcing (e.g. using mobile devices)? Can this data be stored and processed, in order to extract useful informa:on to aid planning and decision-‐making?
This leads to:
(i) What is the most effec:ve way to integrate and organize mul:ple heterogeneous, autonomous sub-‐systems and sensors data?
(ii) How can data mining techniques be used to provide `smart’ outputs for urban planners, architects and designers when proposing small interven:ons?
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Computing!Urban Planning !
Architecture!
Middleware data collection data integration data analysis
Social Network Twitter Facebook*
Weather Station Arduino Crawler
Other NFC GPS Tracking
MSD Analysis [space] Behaviour Analysis [people] Survey/Interview Media
Video Image
Living !Campus!
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Source: IoT Tech World
Smart Ci:es
Smart Campus
Middleware
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Middleware
• Middleware refers to the software that is common to multiple applications and builds on the network transport services to enable ready development of new applications and network services.
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Middleware: Device Nimbus
Concept
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Middleware: Device Nimbus
Design Architecture
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Middleware: Device Nimbus
Prototypes
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Middleware: Device Nimbus
Prototypes
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Technologies used
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Case Study: The Living Campus project
Case study area
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Case Study: The Living Campus project
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Case Study
Methodology
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Case Study
Case study area
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Case Study
Research Data Collec:on
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Case Study: Analysis
Research Data Collec:on
VIDEO [MSD Building]
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Case Study: Analysis
Research Data Collec:on
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Case Study: Analysis
hum
idity
tem
pera
ture
lumino
sity
NFC
noise
PIR
Twitt
er
è
è
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Case Study: Analysis
#unimelb
• keywords
[0, 'dale', 176.2412992020248] [1, 'melbourne', 84.96667087748327] [2, 'cartilage', 67.16367302941084] [3, 'info', 63.22857982073028] [4, 'footscray', 49.39121003122881] [5, 'anisotropy', 49.39121003122881] [6, 'melb', 49.39121003122881] [7, 'unimelb', 49.39121003122881] [8, 'uni', 45.847364141486885] [9, 'lawn', 39.54234371115054] [10, 'exhibition', 38.41879050304468] [11, 'hyperelastic', 32.92747335415254] [12, 'mentoring', 32.92747335415254] [13, 'alumni', 32.92747335415254] [14, 'music', 28.579490109712147] [15, 'adventures', 26.19895312931797] [16, 'cars', 21.81943844754072] [17, 'volunteering', 20.62029663783727] [18, 'park', 19.880551254825853] [19, 'geometry', 19.34844564484119]
Research Data Collec:on
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Case Study: Analysis
#unimelb
• ngrams
[(14, (u'dale', u'robinson', u'phd', u'seminar')), (11, (u'http', u'dale', u'robinson', u'phd')),
(10, (u'biomechanics', u'engunimelb', u'unimelb', u'http')), (8, (u'unimelb', u'http', u'dale', u'robinson')),
(8, (u'engunimelb', u'unimelb', u'http', u'dale')), (5, (u'your', u'troubles', u'music', u'in')),
(5, (u'when', u'there', u'no', u'cars')), (5, (u'war', u'is', u'now', u'open')),
(5, (u'up', u'your', u'troubles', u'music')), (5, (u'uni', u'it', u'nice', u'when')),
(5, (u'troubles', u'music', u'in', u'the')), (5, (u'there', u'no', u'cars', u'in')), (5, (u'the', u'great', u'war', u'is')),
(5, (u'south', u'lawn', u'car', u'park')), (5, (u'park', u'at', u'melbourne', u'uni')), (5, (u'pack', u'up', u'your', u'troubles')), (5, (u'our', u'exhibition', u'pack', u'up')),
(5, (u'open', u'more', u'info', u'http')), (5, (u'now', u'open', u'more', u'info')),
(5, (u'no', u'cars', u'in', u'it')), (5, (u'nice', u'when', u'there', u'no')), (5, (u'music', u'in', u'the', u'great')),
(5, (u'more', u'info', u'http', u'unimelb')), (5, (u'melbourne', u'uni', u'it', u'nice')),
(5, (u'lawn', u'car', u'park', u'at')), (5, (u'it', u'nice', u'when', u'there')), (5, (u'is', u'now', u'open', u'more')),
(5, (u'info', u'http', u'unimelb', u'http')), (5, (u'in', u'the', u'great', u'war')), (5, (u'in', u'it', u'unimelb', u'http')), (5, (u'great', u'war', u'is', u'now')),
(5, (u'exhibition', u'pack', u'up', u'your')),
Research Data Collec:on
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Weather Ruby Crawler
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Case Study: Analysis
hum
idity
tem
pera
ture
lumino
sity
NFC
noise
PIR
Twitt
er
è
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Conclusions and Future Work
• The Device Nimbus middleware can be used to collect/combine data from heterogeneous sources.
• Device Nimbus can be used to build a richer understanding of urban systems, based on data collected, leading to improved tools for planning and policymaking.
• The full implementa:on of Device Nimbus will provide the means to effec:vely monitor users’ rou:nes – help us to understand the use of small open spaces, providing important feedback of collec:ve experience.
• We also plan to scale-‐up our ini:al inves:ga:on to include data collec:on from a diverse range of loca:ons distributed across the main university campus.
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Distributed and heterogeneous data analysis for smart urban
planning
Eduardo Oliveira – [email protected] Michael Kirley Tom Kvan Justyna Karakiewic Carlos Vaz