The Fields of Urban Sensing

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The Fields of Urban Sensing Dana Cuff,
Architecture and Urban Planning Mark Hansen,
Statistics Jerry Kang, Law UCLA
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Translation
What happens when wego urban? focus not on
tech questions
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Fields and Attributes
Fields data field urban field agency field

• Attributes
• information
• modalities
• time
• space / location / mobility
• flow
• actuation
• data scale
• privacy / sensitivity

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• agency field
• What happens when the lab / natural landscape
  shifts to the urban landscape?
• human subjects
• science goes political
• shifts from top-down to decentralized
• shifts from control to pluralism

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• Data Field
• Most science-driven sensing deployments are
  organized by a central authority
• This authority dictates how the data
• are collected and organized, makes
• some guarantees about data
• quality, and regulates access
• Data formats and user interfaces
• limit the kinds of questions that can
• be asked of the data
• While many science-driven projects request
  participation from the general public, they
  retain this centralized character urban sensing
  could offer a different kind of involvement

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• Data Field
• One could approach urban sensing from existing
  data sharing tools like blogs and vlogs what are
  the incentives for sharing data?
• Semi-structured personal data about daily
• habits (reading lists, exercise routines) can
• be shared with data blogging tools
• These projects dont restrict users to
• certain types of data, and encourage the
• use of meta-tags to enable searching
• Access is on an all-or-nothing basis,
• although one could easily imagine yet
• another hybridization, this time with social
• networking software
• If blogs spawned citizen-editors and journalists,
  what might we expect from easy access to data
  collection technologies, to publishing and
  collaboration (slogging)?

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• Data Field
• If sensing technologies are easy to use, and we
  can control how data are shared, assuring some
  degree of confidentiality (we will discuss the
  flipside, privacy, shortly), a data commons could
  emerge
• At that point, who decides whats interesting?
  Who asks the
• questions? How are results presented? Are there
  new kinds of
• news readers? Map interfaces? Who ensures the
  trustworthiness
• of the data? What actions are taken as a
  result?
• The data commons will be populated with
  extremely varied
• data types recorded under possibly unreliable
  circumstances
• interpretation is challenging
• Uncovering chance relations (data mining
  restored to its
• original usage?), reasoning in the face of
  uncertainties,
• recognizing poor quality data and data sources,
  drawing
• conclusions from sparse or unrepresentative
  samples

The clever data analyst need only expose himself
to what his data is willing (or even anxious) to
tell him
John Tukey
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urban field What happens when the lab / natural
landscape shifts to the urban landscape? -isolate
d variables merge into tangled complexity -data
is embedded in meaningful situations -observation
shifts to observation response -data becomes
political, social, economic -time - space
dimensions are constitutive (reliability and
validity are dubious) -science moves toward
design -problems are wicked and cannot be tamed
(Rittel)
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Residential Location Decisions Can urban
sensing improve the way we make choices about
where we will live? What data might we want?
- standards - cost of housing - quality
of schools - security - proximity to
work - additional factors - traffic -
pollution - diversity - voting patterns
- square feet of park per capita
Dwell Magazine Prospect, Colorado - Coolest
Neighborhood in US
Seaside, Florida - birthplace of New Urbanism
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• Traffic
• traffic data is similar to scientific data
• automatic, continuous sensing possible
• e.g. traffic counts, speeds, accidents,
• noise, emissions
• Role of Common Sensing
• - Top-down traffic data is rarely current
• enough to be reliable for individual
• drivers, though it may serve traffic
• management purposes
• - P2P data from thousands of cell phones
• with GPS could be sent to individuals
• by mobile service providers

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• Preference-Related Data
• influencing residential location choice
• Social families with Boy Scouts, density
• of Green Party members,
• -Security broken window count, police
• calls per night
• -Physical modern architecture, street
• trees per block
• -Proximities bowling lanes within 1 mi,
• pawn shops in neighborhood
• -Environmental growing days per year,
• electromagnetic radiation levels

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• MicroEnvironmental Data
• influencing residential location choice
• On-site pollutants
• -Neighbor-data
• -Police calls to this address
• -Landscape water usage
• -Night time street activity

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Air Pollution tracking data (EPA)
Residential Location Decisions
Neighborhood-based sensing as geo-located,
cumulative blog / slog --commute times into
city --commute costs --water quality --air
quality --crime reports
Microenvironmental geovisualization (EPA)
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• Urban sensing attributes
• Modalities
• -product safety records on building materials
• -energy calculations submitted to building
  dept
• -Time
• - future proximate building slated in next 5
  yrs
• - past previous uses for site
• -Space/Location/Mobility
• - static record of seismic activity and
  effects
• - mobile cell phone recordings of songbirds
• Scale
• - data sets energy consumption, voting
  records
• -Actuation
• - guide me to houses heat sinks
• Privacy/sensitivity
• - who are the immediate neighbors?

Suburban infill project, Janek Bielski
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• Futures for urban sensing
• surveillance society, with privacy
• dominating debate

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Futures for urban sensing -infinite tagging
internet of things
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• Design Experimentation
• And Public Art
• responsive environments
• interactive urban interventions
• measuring and communicating
• connecting and participating

Meejin Yoon, White Noise/White Light, Athens
Lars Spuybroek, D-Tower, Netherlands
Diller Scofidio, Blur Building and Brain Coats,
Switzerlandd
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• Political Shopping
• Market Forces
• shopper profiling
• customized information
• target markets
• tagged products
• Public Sphere
• customized information on demand
• spatially embedded
• political shopping

Contents of bag
Attire
Your mother looked at this card last week
75 of shoppers like you bought this card
Last Mothers Day you bought this card
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• data field
• What happens when the lab / natural landscape
  shifts to the urban landscape?
• human subjects
• shifts in quality, accuracy
• access / slogging
• exploratory

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• Futures for urban sensing
• -embedded virtuality
• -embedded responsibility
• -embedded relevance