Designing Physical/Digital Objects for The Internet of Things: From Sensors to User Interaction

DESIGNING
PHYSICAL/DIGITAL OBJECTS
FOR THE INTERNET OF THINGS
FROM SENSORS TO USER INTERACTION
Gerd Kortuem
17 June 2009
Infolab21 | Lancaster University
gerd@kortuem.com | @kortuem | www.kortuem.com

Andy Stanford Clark (IBM)

Source: Cartoon by Peter Steiner. The New Yorker, July 5, 1993 issue (Vol.69 (LXIX) no. 20) page 61

ON THE INTERNET,
NOBODY KNOWS YOU ARE A
THING
Source: http://www.botanicalls.com/kits/

• ATmega1280, 5V
• Digital I/O Pins 54 (of which 14 provide PWM output)
• Analog Input Pins 16
• DC Current per I/O Pin 40 mA
• DC Current for 3.3V Pin 50 mA
• Flash Memory 128 KB of which 4 KB used by bootloader
• SRAM 8 KB
• EEPROM 4 KB
• Clock Speed 16 MH
Arduino is an open source microcontroller board, plus
a free software development environment, to make objects
that can sense inputs from switches, sensors, and
computers, and control motors, lights, and other physical
outputs in the real world!
ARDUINO

Source: Clive Thomas / Wired http://www.wired.com/techbiz/startups/magazine/16-11/ff_openmanufacturing
OPEN-SOURCE HARDWARE

Blogjects track and trace where they are and where they’ve been
Blogjects have self-contained (embedded) histories of their encounters and
experiences
Blogjects always have some form of agency — they can foment action and
participate; they have an assertive voice within the social web.
BLOGJECTS
A Manifesto for Networked Objects —
Cohabiting with Pigeons, Arphids and Aibos
in the Internet of Things
BY JULIAN BLEEKER

THINGS AND PEOPLE
PEOPLE AND THINGS
An Internet of Things that is more than just sensors attached to things

1. CASE STUDIES
2. HUMAN DIMENSION

BP Chemical storage facility, Saltend, Northeast England

Road maintenance crew, South England
trial users
anonymized

Breaker Circular Saw & Wacker Plate

Vibration White Finger

Vibration Dosimeter

Duration of use
(measured)
Vibration characteristics
(known for each equipment,
measured by manufacturer)
Soil condition
(assumed)
all daily trigger tim
short-term exposu
exposure action).
average daily expo
• Daily exposu
• Daily exposu
A(8) is deﬁned as
ahv = actual
Actual Exposure
Maximum Legal Exposure
?
Hand-arm vibration syndrome (HAVS)
• Neurological component
– numbness, tingling, reduced sense o
touch & temperature
– main cause of disability in advanced
cases
• Vascular component
– “vibration white finger”
– episodes of finger blanching
– typically cold-induced attacks
• Musculoskeletal component
– pain, weak grip, etc.

Static domain model
+
Dynamic world model
Operator
IN-SITU ASSISTANCE
encode rules query
REAL-TIME
ASSESSMENT
inform
CODIFICATION
Health & Safety
Policies

PERSONAL HEALTH HISTORIES
0
37.5
75.0
112.5
150.0
13:50 14:00 14:10 14:20 14:30 14:40 14:50 15:00 15:20 15:30 14:20
DailyExposureActionValue
Time
0
10
20
30
40
10:50 11:00 11:10 11:20 11:30 11:40 11:50 12:00 12:20 12:30 12:40
DailyExposureLimitValue
Time
How dangerous is work for each individual?
Daily limit Intensity limit

The recorded usage time had an average error of 3.2% against the actual
usage as recorded by the video footage.

SITE-SPECIFIC HEALTH LOGS
Where are safety hotspots?
Is health managed differently across work-sites?

ACTIVITY PATTERNS
When do safety incidents occur?
When is a task ﬁnished?
1 5 9 13 17 21
Tool 1
Tool 2
Motion
Sound
Light
Task
9:00 9:30 10:00 10:30 11:00 11:30

Model
Awarness
Interactivity
Activity-aware
Process-aware
Policy-aware
Functions
Rules
Work-Flows
POLICY-AWARE OBJECTS

Model
Awarness
Interactivity
Activity-aware
Process-aware
Policy-aware
Functions
Rules
Work-Flows
ACTIVITY-AWARE OBJECTS

RENTAL COMPANY CONSTRUCTION COMPANY
UseCost calculation
Recording usage
LeaseCost = (T "U) + Cost(m)i
i=1
|M |
#

USAGE-BASED PRICING
Rental equipment is charged per actual use, not per time
0
1
2
3
4
5
6
7
0 1 2 3 4 5 6 7
Tool
Worker
0
10
20
30
40
50
60
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Tool 3
Tool 2
Tool 1
d1
When, how, how often? By whom?
d1 d2 d3

THE SAFETY-AWARE BARREL
System
software
Sensors
Display
Application
software
Memory
Processor
Wireless
Network
Storage

THE SAFETY-AWARE BARREL
Don’t shake me so much!
I am too hot!
I shouldn’t be here!
There are too many of us!
I am standing too close
to my neighbours
Don’t put me next to
these barrels!

COOPERATIVE REASONING
Chemical A alone is ok
Chemical A next to
chemical B is not ok
Reactive chemicals may not be stored next to each other
m1 + m2 < safety limit
Total mass of a chemical must be below critical threshold
m1 + m2 + m3 > safety limit
©TECO Karlsruhe University

Chemical A next to
Chemical
knowledge

Chemical A next to
Chemical
knowledge
Spatial
awareness

DEVICE ARCHITECTURE
Domain Knowledge
reactive(<chemical>,<chemical>)
critical_mass(<chemical>,<number>)
content(me,<chemical>)
mass(me,<number>
Safety Rules
hazard:-
content(me, CH1),
content(C, CH2),
reactive(CH1, CH2),
min_dist(CH1, CH2, D1),
distance(me, C, D2),
D2 > D1.
Observational Knowledge
distance(<container>,<container>,<dist>)
Smart-Its Sensor Node
C18F6720 @ 20 MHz (5 MIPS)
Program Memory: 128KB
Data Memory: 3.8KB RAM
1KB internal EEPROM
Memory: 32 KB EEPROM

Trial at BP’s chemical plant in Hull, UK (July 2006)
Smart-its sensor node:
PIC18F6720 @ 20 MHz (5 MIPS)
Program Memory: 128KB
Data Memory: 3.8KB RAM

DESIGN PROCESS

INVISIBLE RISKS
Risk perception is poor
Goal: increasing awareness

SELF-IMAGE AND SOCIAL PRESSURE
Safety equipment often not used
Personal and social “invisibility” becomes key design goal

PAST EXPERIENCES & NARRATIVES
GPS had been experienced as surveillance technology
Technology narrative must be part of the design
= or or ?

INFORMATION DISCLOSURE
Sensing-only Awareness display
Unit w/o display was perceived as surveillance technology

TECHNOLOGY ARCHETYPES
Sensor network
(sensing + data)
Smart object
(interaction)
Developers view problem in light of well-known system models

TECHNOLOGY ARCHETYPES
Management
Operatives'
behavior
Data logs
Exception
reports
Health &
Safety Rules
Operatives
Feedback
Automatic
data capture
Enterprise
System Personal
Health &
Safety
Record
Operative's
behavior
Context-sensitive
notices
Sensor-network
inspired H&S system
(top-down)
Smart-object
inspired H&S system
(bottom-up)
Different system models imply different H&S solutions

BEHAVIOR-BASED SAFETY
Personal
Health &
Safety
Record
Operative's
behavior
Context-sensitive
notices
Personal
Health &
Safety
Record
Operative's
behavior
Context-sensitive
notices
Operatives as source of expertise and behavioral change
Collaborative safety

POINTS TO TAKE HOME
Internet of Things = Things + People

THANK YOU
Gerd Kortuem
@kortuem
kortuem@comp.lancs.ac.uk
www.comp.lancs.ac.uk/~kortuem

Press
Smart tags hail the web of things. BBC. http://news.bbc.co.uk/2/hi/technology/7207514.stm
Scientiﬁc
Daniel Fitton, Fahim Kawsar and Gerd Kortuem. Exploring The Design of a Memory Model for Smart Objects. First
International Workshop on Digital Object Memories. To appear.
Daniel Fitton, Vasughi Sundramoorthy, Gerd Kortuem, James Brown, Christos Efstratiou, Joe Finney, Nigel Davies.
Exploring the Design of Pay-Per-Use Objects in the Construction Domain. EuroSSC 2008: 192-205
Kortuem et al. Sensor Networks or Smart Artifacts? An Exploration of Organizational Issues of an Industrial Health and
Safety Monitoring System. Proceedings International Conference on Ubiquitous Computing (Ubicomp 2007), October
2007, Innsbruck, Austria
Brown et al. Network Interrupts: Supporting Delay Sensitive Applications in Low Power Wireless Control Networks.
Proceedings ACM MobiCom workshop on Challenged Networks (CHANTS 2007), September 2007, Montreal,
Canada
Efstratiou et al. Experiences of Designing and Deploying Intelligent Sensor Nodes to Monitor Hand-Arm Vibrations in
the Field. Proceedings of MobiSys 2007, San Juan, Puerto Rico
Iszatt White, M. Catching Them At It? An Ethnography of Rule Violation. Symposium on Current Developments in
Ethnographic Research in the Social and Management Sciences, 13th-14th September 2006, Liverpool, UK
Busby, J. and Iszatt-White, M. Pushing the Boundaries of HRO Thinking: Non-complex and Uncoupled but still Deadly.
SRA Annual Meeting - Risk Analysis in a Dynamic World: Making a Difference, 3rd-4th December 2006, Baltimore,
Maryland
Davies et al. Sensing Danger – Challenges in Supporting Compliance in the Field. 8th IEEE Workshop on Mobile
Computing Systems and Applications (HotMobile 2007), February 2007, Tucson, Arizona
Lowton M. and Finney, J. Finding NEMO: On the Accuracy of Inferring Location in IEEE 802.15.4 Networks.
Proceedings Workshop on Real-World Wireless Sensor Networks (RealWSN 2006), June 2006, Uppsala, Sweden
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