Are purely technological solutions the best answer we can get to the shortcomings our organizations are often experiencing today? The results we gathered in this work lead us to giving a negative answer to such question. Science and technology are powerful boosters, though when they are applied to the “local, static organization of an obsolete yesterday” they fail to translate in the solutions we need to our problems. Our stance here is that those boosters should be applied to novel, distributed, and dynamic models able to allow us to escape from the local minima our societies are currently locked in. One such model is simulated in this paper to demonstrate how it may be possible to tap into the vast basins of social energy of our human societies to realize ubiquitous computing sociotechnical services for the identification and timely response to falls. Accompanying paper available at https://arxiv.org/abs/1508.06655

1. Tapping Into the Wells of
Social Energy:
A Case Study Based on Falls Identification
Vincenzo De Florio and Arianit Pajaziti
MOSAIC/Universiteit Antwerpen & MOSAIC/iMinds
vincenzo.deflorio@uantwerpen.be
UNIVERSITY OF ANTWERP
MOSAIC Research Group

2. "We are greatly frustrated
by all our local, static organization
of an obsolete yesterday."
Richard Buckminster Fuller,
Synergetics I

3. It is the axioms that make up the system…
• Regardless of its nature, any system is affected by its
design assumptions.
Our organizations and services are no exception.
• “Wrong” assumptions  inefficiency & fragility

4. Challenge
• Being able to (safely!) mutate our organizational paradigms
and assumptions
• Move from
“a local, static organization of an obsolete yesterday”
to the
distributed, dynamic organization for our turbulent
nowadays
• New ingredients: organizational approaches that enable the
utilization of the full potential of our societies
→ Why do we need that? What’s the benefit from social
energy?

5. Case study: Falls Identification
• Falls:
• “most significant cause of injury for elderly persons“
• “most serious life-threatening events" in the 65+ age group.
• Technological lock-in
• Despite the continuing technological progress, there is no
monitoring system that is able to determine precisely whether
a person has actually fallen or, for instance, he or she has
changed their position very quickly.
• In some cases, the monitoring system fails.
• Two types of failures:

6. False negatives and false positives
• False positive:
• The system fires an alarm, although the event did not take place.
• False negative:
• A fall takes place and the system does not recognize the event as a fall.

7. Three big problems…
• FN: “In any safety system, false negatives are possibly
the worst kind of failure.”
• Long waiting times: “The single most important factor
influencing the long-term outcome [after a fall] is the
length of time between the fall and getting medical
attention at a hospital. A few hours more or less makes
the difference between life and death.”
(Both quotes: Tom Doris)
• High social costs!

8. How to improve the service?
• For instance, by using social energy
• Social energy = the power of the people – the use of
society for the sake of improving society’s quality of lives
• A new axiom: from device-only to
→ People as situation identifiers!
People
Devices
AND

9. The idea (1/2)
• Couple two (or more) fall detectors, F1 and F2
• Both F1 and F2 may be in either the Fallen or NotFallen
state
• Then
(F1+F2)(NotFallen) = F1(NotFallen) AND F2(NotFallen)
(F1+F2)(Fallen) = F1(Fallen) OR F2(Fallen)
Less chances to be
in NotFallen
More chances to be
in Fallen

10. The idea (2/2)
• People as an extra “detection layer”: when (F1+F2) is in
state Fallen, a cloud of volunteers is used to verify if this is
a FP
• Coupling F1 with F2 reduces FN rate
• Using social energy reduces the waste of social resources
• …and reduces waiting times!
• How do we organize this?
• How do we put together?
People
Devices
AND

11. Reasoning & coordination
11
Fractal social organization: building block
Individual &
social concerns
optimization.
Capabilities
Policies
Availability
Location…
Events
People
Devices
Bind
Member Member
Member w/
service & feature registry
Service
& feature
Publish Publish
+ Communities!

12. 12
Member Member
Service
description
Publish Publish
Bind
Local
Reasoning & coordination
Individual &
social concerns
optimization
Capabilities
Policies
Availability
Location…
Events
People
Devices MemberMember MemberMember
Exception ⇒ Event propagation
Member w/
service & feature registry
Commu-
nities!
Fractal social organization

13. An example:
iMinds project
Little Sister

14. 14
Multi-agent simulation
Participating entities:
Elderly agents (EA)
Professional carers (PC)
Informal carers(IC)
Device agents (DA)
Mobility agents (MA)
Community agents (CA)
Figure 8. A representation of the FSO structure of the second
simulation model.

15. NetLogo

16. Two families of simulations
• S1(x): we use only F1 (e.g., an accelerometer) and have a
cloud of x volunteers
• x = 0, 5, 10, …, 40
• S1(0): traditional approach
• S2(x): we use F1+F2 (e.g., accelerometer + gyroscope)
and have a cloud of x volunteers
• Again, x = 0, 5, 10, …, 40
• Each simulation run: 10,000 “ticks”

17. Coupling F1 + F2: Better FN rate

18. Social energy: >> handled requests

19. Social energy: << service costs!

20. Social energy: << waiting times!

21. Conclusions
• Challenge: Evolving the organizations while maintaining the
identity of the intended services
• FSO's dynamic hierarchical organization optimally
orchestrates all participating entities thus overcoming the
stiffness of the traditional organizations
• Major returns of social energy:
• improvement of social costs;
• better use of the social resources;
• reduction of the average time to respond to identified falls.

22. Thank you for your attention!
For more information:

23. vincenzo.deflorio@gmail.com / uantwerpen.be
Blog: eraclios.blogspot.be
LinkedIn group "Computational Antifragility"
ANTIFRAGILE workshop
twitter://@EnzoDeFlorio