scott davidoffdissertation defense familycontrolsmarthome the project on routine as resource for the...
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Scott DavidoffDissertation Defense
THE PROJECT ON
Routine as Resource for the Design of Learning SystemsScott Davidoff Dissertation Defense
Scott DavidoffDissertation Defense
A pattern of behavior that is followed repeatedly, but is subject to change if conditions change
Winter 1964
“
“”2
Scott DavidoffDissertation Defense
Koestler 1967
Routines reduce our attention needs
3
Scott DavidoffDissertation Defense
Zerubavel 1981
Reduce attention needed for tasks
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Scott DavidoffDissertation Defense
Wakkary & Maestri 2007
Free attention for bigger challenges
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Scott DavidoffDissertation Defense
Wolin + Bennett 1984
6
Scott DavidoffDissertation Defense
The cyclic nature of routine makes it a natural target for machine learning
Scott DavidoffDissertation Defense
Machine learning can use this order
8
Scott DavidoffDissertation Defense
Suchman 1983, Tolmie et al. 2002
Idiosyncrasies are hard to model
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Scott DavidoffDissertation Defense
Certain human routines can be modeled, increasing the scope of activity recognition
Machine learning
Opportunities
10
Scott DavidoffDissertation Defense
The ability to use learned routines in end-user applications would solve a variety of human problems
HCI
Opportunities
11
Scott DavidoffDissertation Defense
Dual-income family logistics
12
Scott DavidoffDissertation Defense
Sequence of place and transportation (rides) that occur on daily, weekly, and seasonal cycles
“
“”13
Scott DavidoffDissertation Defense
Darrah et al. 2000
Managing details can be difficult
14
Scott DavidoffDissertation Defense
Frissen 2000
Routines give a feeling of control
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Scott DavidoffDissertation Defense
Beech et al. 2004
Life does not always follow routines
16
Scott DavidoffDissertation Defense
Breakdowns lead to loss of control
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Scott DavidoffDissertation Defense
Perry et al. 2001, Ling + Campbell 2003
A constant need to follow updates
18
Scott DavidoffDissertation Defense
Gneezy + Rustichini 1998, Darrah 2009
A constant source of anxiety
19
Scott DavidoffDissertation Defense
We can learn a model of family logistical routines, and present that information to families to help them feel more in control of their lives
20
Scott DavidoffDissertation Defense 21
Scott DavidoffDissertation Defense 22
Scott DavidoffDissertation Defense
2We can use sensing and modeling to synthesize missing information resources
3Show how to use the model and evaluate the impact of the information
1We can use fieldwork to identify missing but needed information resources
Fieldwork Modeling Validation
23
Scott DavidoffDissertation Defense
Create an ordered list of places and rides
Attend to the details of a plan as it unfolds
Planning and coordinationLogistics
Coordinate
Plan
24
Scott DavidoffDissertation Defense
Fieldwork1
25
Scott DavidoffDissertation Defense
1805
22 Davidoff et al Ubicomp 2006Months
Months
Months0606
12Families
Families
Families
Davidoff et al Ubicomp 2007
Davidoff, Dey + Zimmerman CHI 2009
45 Months24Families
26
Scott DavidoffDissertation Defense
Semi-Structured Interviews
Davidoff et al. Ubicomp 2006
27
Scott DavidoffDissertation Defense scott davidoff, min kyung lee, anind dey + john zimmerman
Needs Validation
Scott DavidoffDissertation Defense
Davidoff et al. Ubicomp 2007
User Enactments
29
Scott DavidoffDissertation Defense
User Enactments
Davidoff et al. Ubicomp 2007
30
Scott DavidoffDissertation Defense
GPS
Phone Calls
SMS
CalendarsDavidoff, Dey + Zimmerman CHI 2009
31
Scott DavidoffDissertation Defense
528 phone interviews
109 activity Interviews
108 calendar months
Davidoff, Dey + Zimmerman CHI 2009
32
Scott DavidoffDissertation Defense
Less than 20% of days go exactly as planned1Routines are not documented
People have incomplete knowledge of other people’s routines
People make plans that depend on incorrect information
2
3
4
33
Scott DavidoffDissertation Defense 34
Scott DavidoffDissertation Defense
Family E
Routine
Deviation, Scheduled
Deviation, Unscheduled
35
Scott DavidoffDissertation Defense
Family EAll Families
Routine
Deviation, Scheduled
Deviation, Unscheduled
36
Scott DavidoffDissertation Defense
Less than 20% exactly as planned
37
Scott DavidoffDissertation Defense
Routineness of Family E Activities
38
Scott DavidoffDissertation Defense
Routineness of Family E Activities
39
Scott DavidoffDissertation Defense
Routineness of Family E Activities
40
Scott DavidoffDissertation Defense
Routines are not documentedFieldwork Finding
Davidoff, Dey + Zimmerman CHI 2010
41
Scott DavidoffDissertation Defense
Davidoff, Dey + Zimmerman CHI 2010
August September October November
42
Scott DavidoffDissertation Defense
People have incomplete knowledge of other people’s routines
Fieldwork Finding
Davidoff, Dey + Zimmerman CHI 2010
43
Scott DavidoffDissertation Defense
Davidoff, Dey + Zimmerman CHI 2010
44
Scott DavidoffDissertation Defense
Davidoff, Dey + Zimmerman CHI 2010
45
Scott DavidoffDissertation Defense
Davidoff, Dey + Zimmerman CHI 2010
46
Scott DavidoffDissertation Defense
Davidoff, Dey + Zimmerman CHI 2010
47
Scott DavidoffDissertation Defense
Davidoff, Dey + Zimmerman CHI 2010
48
Scott DavidoffDissertation Defense
Davidoff, Dey + Zimmerman CHI 2010
49
Scott DavidoffDissertation Defense
Davidoff, Dey + Zimmerman CHI 2010
50
Scott DavidoffDissertation Defense
Davidoff, Dey + Zimmerman CHI 2010
51
Scott DavidoffDissertation Defense
People make plans that depend on incorrect informationFieldwork Finding
Davidoff, Dey + Zimmerman CHI 2010
52
Scott DavidoffDissertation Defense
Orthodontist
Scouts
School
Dad Work
Home
4:00 5:00 6:00 7:003:002:00 8:00
S16Dad
View of Plan: Dad
Check-up
Track Practice
53
Scott DavidoffDissertation Defense
Orthodontist
Scouts
School
Dad Work
Home
4:00 5:00 6:00 7:003:002:00 8:00
S16Dad
View of Plan: S16
Paper Route
Track Practice
54
Scott DavidoffDissertation Defense
Orthodontist
Scouts
School
Dad Work
Home
4:00 5:00 6:00 7:003:002:00 8:00
S16Dad
Who Will do the Paper Route?
Check-up
Track Practice
55
Scott DavidoffDissertation Defense
Information gaps can break down coordination
No resources exist to find needed information
Davidoff, Dey + Zimmerman CHI 2010
56
Scott DavidoffDissertation Defense
Modeling2
57
Scott DavidoffDissertation Defense
2 31 Ride Detection
Driver Prediction
Predict Lateness
58
Scott DavidoffDissertation Defense
In Situ Observation
In Situ Observation
Maintain Current Behaviors
Maintain Current Behaviors
Ubiquitous Sensing
Ubiquitous Sensing
GPS
59
Scott DavidoffDissertation Defense
Parent drives kid to an activity
Parent drives kid from activity
Pick-ups and drop-offsRide
Pick-up
Drop-off
60
Scott DavidoffDissertation Defense
Ride Detection
Scott DavidoffDissertation Defense
Day Care
Work
Using GPS to Sense a Drop-Off
Parent Child 62
t3 t4 t5 t6t2t1 t7
Scott DavidoffDissertation Defense
Day Care
Work
Using GPS to Sense a Drop-Off
Parent Child 63
t3 t4 t5 t6t2t1 t7
Scott DavidoffDissertation Defense
Day Care
Work
Using GPS to Sense a Drop-Off
Parent Child 64
t3 t4 t5 t6t2t1 t7
Scott DavidoffDissertation Defense
t3
Day Care
t4 t5 t6t2
Work
t1 t7
Using GPS to Sense a Drop-Off
Parent Child 65
Scott DavidoffDissertation Defense
Day Care
Work
Using GPS to Sense a Pick-Up
Parent Child 66
t3 t4 t5 t6t2t1 t7
Scott DavidoffDissertation Defense
Day Care
Work
Using GPS to Sense a Pick-Up
Parent Child
t3 t4 t5 t6t2t1 t7
Scott DavidoffDissertation Defense
Day Care
Work
Using GPS to Sense a Pick-Up
Parent Child
t3 t4 t5 t6t2t1 t7
Scott DavidoffDissertation Defense
GPS Ride Detection EvaluationFamily Precision Recall
How many of the sensed ridesare right
How many of the total ridesare sensed?
Pick-up Drop-off Pick-up Drop-off
A .991 .987 .912 .910
B .966 .962 .979 .981
C .913 .824 .971 .921
D .878 .873 .980 .944
E .931 .684 .959 .985
Mean .936 .866 .960 .950
.901 .955
69
Scott DavidoffDissertation Defense
Smarter power management
Wi-Fi, Bluetooth, cell tower ID
Apply heuristics to modelingCultural norms, Individual Behavior
Single Location Sensor
GPS Sampling Rate
70
Scott DavidoffDissertation Defense
Driver Prediction
Scott DavidoffDissertation Defense
Name Meaning Values
Ln Location of pick-up or drop-off Place ID
RType Ride type Pick-up, Drop-off
DoW Day of week 0,1,2,3,4,5,6
ToD Discretized time of day (15 min) 1,2,3…96
drivert-j Driver for the last 5 rides to Ln Mom, Dad
Driver distribution model [0,1]
Driver Prediction Model Features
72
Scott DavidoffDissertation Defense
Driver Prediction Performance x Number of Training Weeks of Data
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
73
Scott DavidoffDissertation Defense
Driver Prediction Performance x Number of Training Weeks of Data
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
74
Scott DavidoffDissertation Defense
Driver Prediction Performance x Number of Training Weeks of Data
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
1 24
75
Scott DavidoffDissertation Defense
Lateness Prediction
Scott DavidoffDissertation Defense 77
TnowTideal
Lateness in Minutes
Number of Examples
Distribution of Parent Late Arrivals
N = 83
Scott DavidoffDissertation Defense
Name Meaning Values
R Whether the parent remembers
True, False
Lchild Location of the child Place ID
Lcurr Current location of a parent
Place ID
J Driver prediction model Mom, Dad
78
Scott DavidoffDissertation Defense
Name Meaning Values
R Whether the parent remembers
True, False
Lchild Location of the child Place ID
Lcurr Current location of a parent
Place ID
J Driver prediction model Mom, Dad
T If the parent is traveling True, False
Lstart Starting location of a parent
Place ID
79
Scott DavidoffDissertation Defense
Name Meaning Values
R Whether the parent remembers
True, False
Lchild Location of the child Place ID
Lcurr Current location of a parent
Place ID
J Driver prediction model Mom, Dad
T If the parent is traveling True, False
Lstart Starting location of a parent
Place ID
Empirical cumulative distribution (ecdf) of
on-time arrivals to Lchild
at time TnowTideal
[0,1]
80
Scott DavidoffDissertation Defense
Name Meaning Values
R Whether the parent remembers
True, False
Lchild Location of the child Place ID
Lcurr Current location of a parent
Place ID
J Driver prediction model Mom, Dad
T If the parent is traveling True, False
Lstart Starting location of a parent
Place ID
Empirical cumulative distribution (ecdf) of
on-time arrivals to Lchild
at time TnowTideal
[0,1]
D Destination of a parent Place ID
81
Scott DavidoffDissertation Defense
Name Meaning Values
R Whether the parent remembers
True, False
Lchild Location of the child Place ID
Lcurr Current location of a parent
Place ID
J Driver prediction model Mom, Dad
T If the parent is traveling True, False
Lstart Starting location of a parent
Place ID
Empirical cumulative distribution (ecdf) of
on-time arrivals to Lchild
at time TnowTideal
[0,1]
D Destination of a parent Place ID
82
Scott DavidoffDissertation Defense 83
tideal - 30
A’ = 0.659
.6
.5
Scott DavidoffDissertation Defense 84
tideal
A’ = 0.801
Scott DavidoffDissertation Defense 85
tideal +10
A’ = 0.826
Scott DavidoffDissertation Defense
We can learn a model of family logistical routines, and present that information to families to help them feel more in control of their lives
86
Scott DavidoffDissertation Defense
Validation3
87
Scott DavidoffDissertation Defense 88
Scott DavidoffDissertation Defense
Do parents understand the view?
Do parents perceive that the information is valuable?
Do parents feel more in control having this view?
89
Scott DavidoffDissertation Defense
1257
45 Davidoff et al Ubicomp 2006Davidoff et al Ubicomp 2007Davidoff, Dey + Zimmerman CHI 2009Davidoff et al. CHI 2010Months
Months24
24Families
Families
Families
Davidoff et al. Ubicomp 2011(in preparation)
90
Scott DavidoffDissertation Defense
Davidoff et al. Ubicomp 2011 in preparation
Experience prototype: Doctor
91
Scott DavidoffDissertation Defense 92
Scott DavidoffDissertation Defense 93
Scott DavidoffDissertation Defense
Davidoff et al. Ubicomp 2011 in preparation
Experience prototype: Kitchen
94
Scott DavidoffDissertation Defense
It's nice to have a map of the day. I don't literally write all this stuff down, so sometimes it's just hard to keep in my head.
Visual Distills Details
“
95
−P2“”
Scott DavidoffDissertation Defense
Because the calendar [is] all words and numbers, so you have to really think about …how long everything takes…
Visual Simplifies Calculation
“
96
−P10
Scott DavidoffDissertation Defense
…With the visual you can see who's doing what at what time. You can make a decision about who's activity to change.
Visual Simplifies Calculation
97
−P10“”
Scott DavidoffDissertation Defense
I would be able to know where everyone was gonna be, instead of having to ask around.
Visual Clarifies Intentions
“”98
−P11
“
Scott DavidoffDissertation Defense
Venkatesh + Davis 2003Technology Acceptance Model-3
99
Scott DavidoffDissertation Defense
…helps me do my job “as a parent.”
…would want my family to use it.
…more in control of details, more ready for changesPerception of Control
Behavioral Intention
Perceived Usefulness
100
Scott DavidoffDissertation Defense 101
Perceived Usefulness
Behavioral Intention
Perception of Control
Supports Planning
Supports Awareness
7
6
5
4
3
2
1
Scott DavidoffDissertation Defense
We can learn a model of family logistical routines, and present that information to families to help them feel more in control of their lives
102
Scott DavidoffDissertation Defense
Contributions
103
Scott DavidoffDissertation Defense
Suchman 1983, Tolmie et al. 2002
Certain routines can be modeled
104
Scott DavidoffDissertation Defense
2 31 Ride Detection
Driver Prediction
Predict Lateness
105
Scott DavidoffDissertation Defense
Commodity GPS with real power constraints
106
Scott DavidoffDissertation Defense 107
Scott DavidoffDissertation Defense
Breakdowns lead to loss of control
108
Scott DavidoffDissertation Defense 109
Perceived Usefulness
Behavioral Intention
Perception of Control
Supports Planning
Supports Awareness
7
6
5
4
3
2
1
Scott DavidoffDissertation Defense
Gneezy + Rustichini 1998, Darrah 2009
A constant source of anxiety
110
Scott DavidoffDissertation Defense
Empower Parents
Davidoff et al. Ubicomp 2007
111
Scott DavidoffDissertation Defense
Future Work
112
Scott DavidoffDissertation Defense
Improve algorithms
Use algorithms to enable other family coordination systems
Add additional sensor inputs
Extend to other forms of routine
113
Scott DavidoffDissertation Defense Neustaedter + Brush CHI 2006 114
Scott DavidoffDissertation Defense
6pmOrthodontist6pmOrthodontist
Neustaedter + Brush CHI 2006 115
Scott DavidoffDissertation Defense
6pmOrtho6pmOrthoPaper RoutePaper Route
Neustaedter + Brush CHI 2006 116
Scott DavidoffDissertation Defense Brown et al. Ubicomp 2007
Baseball
117
Scott DavidoffDissertation Defense
Baseball
Brown et al. Ubicomp 2007 118
Scott DavidoffDissertation Defense
The project on
Scott DavidoffDissertation Defense
Thanks for your time, brain power, and support
Scott DavidoffDissertation Defense
Thanks to our sponsors
NSF IIS 1017429
Google Research Award
Scott DavidoffDissertation Defense
Thanks to our supporters
Scott DavidoffDissertation Defense
Thanks to my collaborators
Scott DavidoffDissertation Defense
Thanks to my committee
Scott DavidoffDissertation Defense
Thanks to my advisors
Scott DavidoffDissertation Defense
Questions
Scott DavidoffDissertation Defense
Image Credits
127
Scott DavidoffDissertation Defense
QUESTIONSLIDES
128
Scott DavidoffDissertation Defense
ROUTINE MODELINGRELATED WORK
129
Scott DavidoffDissertation Defense
FORMULAS
130
Scott DavidoffDissertation Defense
Driver Distribution
131€
φ =
driver = P1Ln ,Rtype,DoW
∑
driver = P1Ln ,Rtype,DoW
∑ + driver = P2Ln ,Rtype,DoW
∑
Scott DavidoffDissertation Defense
LWDT
132€
d(y)LWq =
y ie− j
i xij −q j( )
2
∑
i∈labeled data,i≠q
∑
e− j
i xij −q j( )
2
∑i=q∑
Scott DavidoffDissertation Defense
Bayesian Network
133
€
P(Rd | Lstartd ,Lstart
m ,Lcurrd ,Lcurr
m ,Lchild ,Td ,Tm ,φ)
Scott DavidoffDissertation Defense
RIDE SENSING TECHNICAL VERSION
134
Scott DavidoffDissertation Defense
Davidoff, Dey & Zimmerman CHI 2011
135
Scott DavidoffDissertation Defense
Two Kinds of Drop-Offs
136
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
Two Kinds of Drop-Offs
t3t2 ,t1 ,
137
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
Two Kinds of Drop-Offs
t3t2 ,t1 ,
138
Scott DavidoffDissertation Defense
Two Kinds of Pick-Ups
139
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
Using GPS to Sense a Pick-Up
t3t2 ,t1 ,
140
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
Using GPS to Sense a Pick-Up
t3t2 ,t1 ,
141
Scott DavidoffDissertation Defense
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
Using GPS to Sense a Drop-Off
142
Scott DavidoffDissertation Defense
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }Using GPS to Sense a Drop-Off
143
Scott DavidoffDissertation Defense
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
Using GPS to Sense a Drop-Off
144
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
Using GPS to Sense a Drop-Off
145
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
Using GPS to Sense a Drop-Off
€
(t1,P,CoT)∧(t1,C,CoT)∧
146
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
Using GPS to Sense a Drop-Off
€
(t2,P,Ln )∧(t2,C,Ln )∧
€
(t1,P,CoT)∧(t1,C,CoT)∧
147
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
Using GPS to Sense a Drop-Off
€
(t2,P,Ln )∧(t2,C,Ln )∧
€
(t3,P,¬CoT)∧(t3,C,Ln )
€
(t1,P,CoT)∧(t1,C,CoT)∧
148
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
Using GPS to Sense a Drop-Off
€
(t2,P,Ln )∧(t2,C,Ln )∧
€
(t3,P,¬CoT)∧(t3,C,Ln )
€
(t1,P,CoT)∧(t1,C,CoT)∧
149
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
€
(t1,P,¬CoT)∧(t1,C,Ln )∧
Using GPS to Sense a Pick-Up
150
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
€
(t1,P,¬CoT)∧(t1,C,Ln )∧
Using GPS to Sense a Pick-Up
151
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
€
(t1,P,¬CoT)∧(t1,C,Ln )∧
€
(t2,P,Ln )∧(t2,C,Ln )∧
Using GPS to Sense a Pick-Up
152
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
€
(t1,P,¬CoT)∧(t1,C,Ln )∧
€
(t2,P,Ln )∧(t2,C,Ln )∧
€
(t3,P,CoT)∧(t3,C,CoT)
Using GPS to Sense a Pick-Up
153
Scott DavidoffDissertation Defense
P C
5:15
Day Care
5:30 5:45 6:005:00
Work
4:45 6:15
€
States = Ln,T |CoT,else{ }
€
People = P,C{ }
€
(t1,P,¬CoT)∧(t1,C,Ln )∧
€
(t2,P,Ln )∧(t2,C,Ln )∧
€
(t3,P,CoT)∧(t3,C,CoT)
Using GPS to Sense a Pick-Up
154
Scott DavidoffDissertation Defense
SCHOOL HALF DAY BREAKDOWN
155
Scott DavidoffDissertation Defense
Baseball
School
Dad Work
Home
4:00 5:00 6:00 7:003:002:00 8:00
S16Dad
View of Plan: S16
Track Practice
156
Scott DavidoffDissertation Defense
Baseball
School
Dad Work
Home
4:00 5:00 6:00 7:003:002:00 8:00
S16Dad
View of Plan: S16
Track Practice
157
Scott DavidoffDissertation Defense
Baseball
School
Dad Work
Home
4:00 5:00 6:00 7:003:002:00 8:00
S16Dad
Dad Started Baseball League
Track Practice
158
Scott DavidoffDissertation Defense
OTHER APPLICATIONS
159
Scott DavidoffDissertation Defense
Orthodontist
Scouts
School
Dad Work
Home
4:00 5:00 6:00 7:003:002:00 8:00
S16Dad
Detect conflict with unlabeled routine
Track Practice
Check-up
Paper Route
160
Scott DavidoffDissertation Defense
Baseball
School
Dad Work
Home
4:00 5:00 6:00 7:003:002:00 8:00
S16Dad
Dad Started Baseball League
Track Practice
161
Scott DavidoffDissertation Defense
ACTIVITY SCATTERPLOT
162
Scott DavidoffDissertation Defense
RIDE SENSING ERRORS
163
Scott DavidoffDissertation Defense
Smarter power managementGPS Sampling Rate
164
Scott DavidoffDissertation Defense
Smarter power management
Wi-Fi, cell tower, bluetoothSingle Location Sensor
GPS Sampling Rate
165
Scott DavidoffDissertation Defense
5:15
Home
5:30 5:45 6:005:00
Work
4:45 6:15
Simultaneous Departure Errors
School
Parent Child 166
Scott DavidoffDissertation Defense
Smarter power management
Wi-Fi, cell tower, bluetooth
Apply heuristics to modelingCultural norms, Individual Behavior
Single Location Sensor
GPS Sampling Rate
167
Scott DavidoffDissertation Defense
1:00pm
Home
2:00 3:00 4:0012:00
Work
11:00 5:00
Lost Signal During Daytime
School
Parent Child 168
Scott DavidoffDissertation Defense
DRIVER PREDICTION ERRORS
169
Scott DavidoffDissertation Defense
Driver Prediction Performance x Number of Training Weeks of Data
170
Scott DavidoffDissertation Defense
USER ENACTMENT PICS
171
Scott DavidoffDissertation Defense
User Enactments
Davidoff et al. Ubicomp 2007
172
Scott DavidoffDissertation Defense
User Enactments
Davidoff et al. Ubicomp 2007
173