5. Smart Cities: From Senseable…
• Sensing what’s
happening
– Via ICT devices Sense%
– And social
networks
• To better
understand (via
data analysis) Understand %
– City and social (compute)%
dynamics
– At a global level
6. …To Actuable
• We can “shape”
other than
understand Sense% Act
%
(Steer)
%
– Actuating ICT
devices
– Steering human
actions
• Closing the loop Understand %
that enables (compute)%
finalized urban
behaviors possible
7. …To Actuable
• We can “shape”
other than
understand Sense% Act
%
(Steer)
%
– Actuating ICT
device
– Steering human
actions
• Closing the loop Understand %
that enables (compute)%
finalized urban
behaviors possible
8. Urban Superorganisms: ICT Side
• An ICT-enriched urban environment with rich
sensing, actuating, and computing (SAC) capabilities
– Sensing: sensor networks, tags, smart objects,etc.
– Actuating: traffic controllers, public digital displays,
critical infrastructures
– Computing: highly distributed and decentralized, with
inter-connected computational engines everywhere
9. Urban Superorganisms: Human Side
• People with smart phones or alike (or whatever will
appear in the future as wearable devices) contribute
to such SAC capabilities
– Sensing: the 5 senses + smart phones
– Actuating: the body
– Computing: human & social intelligence
10. Urban Superorganisms:
Putting All Together
• The ICT and Human/Social level
blurred to the point of invisibility:
• Complementing each other in a
process of high value co-creation
• In the resulting overall “urban
organism”, we can achieve very
high-levels of collective
– Perception
– Awareness
– Action
• Dramatically changing the way we
move, live, work, and play, in our
towns
11. Living in a Superorganism
• Collective vs individual awareness
– Reflecting on ourselves as members of a community
• Be capable of understanding and acting together in real time
– Immediate feedback to/from the community
12. Collective Mobility, for Instance
• Mobility per se :: steer for car, bike, ride sharing
• Childcare :: steering & monitoting children on their way to
school
• Exhibitions :: steer to avoid crowd or suggest paths
• All of these requiring collective sensing awareness and action
• And can (should?) rely on bio-inspired solutions
13. The SAPERE Project
• SAPERE Self-aware Pervasive
Service Ecosystems
– EU FP7 FET
– Starting October 1st 2010, lasting
3 years
• Key Challenges
– To define and implement a
framework for adaptive service
ecosystems
– Models + Middleware
– Experience with pervasive urban
services and pervasive displays
14. The SAPERE Approach
• Nature-inspired (Biochemical)
– Simply metaphor for combining/aggregating services
in a spontaneous way
– Whether human or
ICT ones
• Spatially-situated
– To match the
nature of urban
scenarios
– Adaptive
– Spontaneous
reconfiguration of
activities and
interactions
15. The SAPERE Architecture
• Humans & ICT Devices
– Interact by injecting/
consuming service/data
components
• Service Components
– Execute in a sort virtual
Spatial substrate
– Moving, acting, composing,
as from eco-laws
• Eco Laws
– Rule local activities and
interactions
– Apply based on state of
local components
– Self-organization of
collective behavior
16. The SAPERE Eco-laws
• Identification of 4 primitive eco-laws
– Forming a necessary and complete set bond
– Upon which to build more complex
self-organization patterns
• The Eco-laws
– Bonding: sort of chemical bond, local
connection of LSAs – subsuming
discovery and invocation spread
– Spreading: diffusion of LSAs to
neighbors, to enable non-local
interactions
– Aggregation: sort of fusion, primitive aggr
data reduction based on ODI
functions
– Decay: evaporation and deletion of
information, to perform decentralized
garbage collection in a decentralized decay
way
17. The SAPERE Self-org Patterns
• Built upon the set of basic
eco-laws
– Which can be
considered sorts of
“primitive patterns”
• To define complex bio-
inspired self-organization
and self-composition
behaviours
– Counterproof of the
completeness and
efficacy of the basic
set
19. Programming SAPERE Apps
• Have SAPERE middleware launched
in the nodes to be involved
• Write agents that inject LSAs
– To express services/
functionalities they made
available
– To request (formal fields) the
services/data/funtionalities they
requires
• Exploit self-org patterns to realize
specific distributed functionaities
– Gradients, Chemiotaxis,
Context completion, etc.
• Let the SAPERE space react by
triggering eco-laws and react to
events (bond, spread, etc.)
21. Open Challenges
! There are many challenges to solve
! Engineering and programming tools
! Patterns of self-organization
! Top-down vs bottom-up approaches
! Incenvitives for participation
! Just to mention a few…
22. Challenge: Engineering Tools
! Designing
! How to represent collective urban situations?
! How to turn it into collective awareness?
! How to represent urban goals and plan of actions?
! Role of existing social networks in future ecosystems?
! Programming
! What programming languages and abstractions?
! How to trigger/deploy specific urban behaviors?
! How to measure the goodness/badness of behaviors?
23. Challenge: Patterns
! Given the basic sense-understand-act loop schemes
! At urban scale, multidutes of local/nested loops co-exists
! What are the architectural patterns by which such loops
can be organized?
! What is the impact of different patterns on urban
behaviors?
! Towhat extent we can “design” the shape of such
loops?
Breakpoint
Token
Next
element
to
execute
24. Challenge:Top-down/Bottom-up
! Bottom-upself-organization
and adaptation
! Driven by emergence (often
implicit, e.g., stigmergic)
feedback loop in interactions
! Very robust and efficient
! Cannot by designed by
definition
! Top-down self-adaptation
! Explicit engineering of
feedback loops
! Needed to enforce specific
behaviors?
! Howwe can make the two
co-exists?
29. Engineering the Environment
in SAPERE
• What does it means to “shape” the environment
– Shaping its perception by components
– Equivalent to the distort the way LSAs are perceived and propagate
• Very easy to
implement but…
– Still to be verified
its effectiveness
and the ease of
engineering top-
down behaviors in
this way
30. Engineering the Environment
in SAPERE
• What does it means to “shape” the environment
– Shaping its perception by components
– Equivalent to the distort the way LSAs are perceived and propagate
• Very easy to
implement but…
– Still to be verified
its effectiveness
and the ease of
engineering top-
down behaviors in
this way
31. Conclusions
• Our future cities will become sorts of superorganisms
• Human & ICT tightly coupled
• Collective participation and action
• Bio-inspired solutions at work in future cities
• How can we engineer these?
• SAPERE is doing some steps in the right direction
• Yet there are a lot of challenges to solve