SlideShare a Scribd company logo

Consumer Centered Calibration End Use Water Monitoring

•
•
E
Eric Larson

Presented at WikiEnergy / NILM Workshop 2014

EngineeringBusinessTechnology
1 of 104
Download to read offline
consumer centered calibration in end-use water monitoring eric c. larson | eclarson.com Assistant Professor Computer Science and Engineering
on average, a consumer can save 15-25%
lake mead 1983
lake mead 2011
we are using water faster than it is being replenished Pacific Institute for Studies in Development, Environment, and Security, 2011
we are using water faster than it is being replenished Pacific Institute for Studies in Development, Environment, and Security, 2011
$2,994.83
more awareness
Fabricated"Unit 16 Water"Meter"Design 15 Turbine Insert Thermistor Flow image: LBNL
Fabricated"Unit 16 Water"Meter"Design 15 Turbine Insert Thermistor Flow image: LBNL
Fabricated"Unit 16 Water"Meter"Design 15 Turbine Insert Thermistor Flow image: LBNL
meters flow rate fixture flow inline water Fabricated"Unit 16
meters flow rate fixture flow inline water water pressure pressure sensor Fabricated"Unit 16
meters flow rate fixture flow inline water water pressure pressure sensor Fabricated"Unit 16
meters flow rate fixture flow inline water water pressure pressure sensor machine learning estimated Fabricated"Unit 16
HydroSense
• central sensing point • easy to install • low cost • can observe every fixture HydroSense
• central sensing point • easy to install • low cost • can observe every fixture HydroSense BelkinEcho
• central sensing point • easy to install • low cost • can observe every fixture HydroSense 40# 50# 60# 70# 80# Cold Line Pressure (Hose Spigot) 0 94.5 time (s) psi BelkinEcho
• central sensing point • easy to install • low cost • can observe every fixture HydroSense 40# 50# 60# 70# 80# Cold Line Pressure (Hose Spigot) 0 94.5 time (s) psi BelkinEcho
• central sensing point • easy to install • low cost • can observe every fixture HydroSense 40# 50# 60# 70# 80# Cold Line Pressure (Hose Spigot) 0 94.5 time (s) psi open close BelkinEcho
kitchen sink upstairs toilet downstairs toilet
kitchen sink upstairs toilet downstairs toilet days 33 33 30 27 33 events 2374 3075 4754 2499 2578 events/day 71.9 93.2 158.5 92.6 78.1 = days 33 33 30 events 2374 3075 4754 events/day 71.9 93.2 158.5
kitchen sink upstairs toilet template matching unknown event downstairs toilet
kitchen sink upstairs toilet template matching unknown event downstairs toilet
feasibility study Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., and Patel, S.N. HydroSense: infrastructure-mediated single-point sensing of whole-home water activity. Proceedings of the 11th ACM international conference on Ubiquitous computing, (2009), 235–244. Larson, E., Froehlich, J., Campbell, T., et al. Disaggregated water sensing from a single, pressure- based sensor: An extended analysis of HydroSense using staged experiments. Pervasive and Mobile Computing, (2010).
feasibility study • 10 homes Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., and Patel, S.N. HydroSense: infrastructure-mediated single-point sensing of whole-home water activity. Proceedings of the 11th ACM international conference on Ubiquitous computing, (2009), 235–244. Larson, E., Froehlich, J., Campbell, T., et al. Disaggregated water sensing from a single, pressure- based sensor: An extended analysis of HydroSense using staged experiments. Pervasive and Mobile Computing, (2010).
feasibility study • 10 homes • staged calibration Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., and Patel, S.N. HydroSense: infrastructure-mediated single-point sensing of whole-home water activity. Proceedings of the 11th ACM international conference on Ubiquitous computing, (2009), 235–244. Larson, E., Froehlich, J., Campbell, T., et al. Disaggregated water sensing from a single, pressure- based sensor: An extended analysis of HydroSense using staged experiments. Pervasive and Mobile Computing, (2010).
feasibility study • 10 homes • staged calibration • ~98% accuracy Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., and Patel, S.N. HydroSense: infrastructure-mediated single-point sensing of whole-home water activity. Proceedings of the 11th ACM international conference on Ubiquitous computing, (2009), 235–244. Larson, E., Froehlich, J., Campbell, T., et al. Disaggregated water sensing from a single, pressure- based sensor: An extended analysis of HydroSense using staged experiments. Pervasive and Mobile Computing, (2010).
70 50 30 pressure(psi) 70 50 30 pressure(psi) initial study: staged events
70 50 30 pressure(psi) 70 50 30 pressure(psi) initial study: staged events kitchen sink kitchen sink
70 50 30 pressure(psi) 70 50 30 pressure(psi) natural water use
how well does single point sensing work in a natural setting?
longitudinal evaluation
longitudinal evaluation
totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% data collection Larson, E., Froehlich, J., Saba, E., et al. A Longitudinal Study of Pressure Sensing to Infer Real- World Water Usage Events in the Home. Pervasive Computing, Springer (2011), 50–69.
totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% data collection Larson, E., Froehlich, J., Saba, E., et al. A Longitudinal Study of Pressure Sensing to Infer Real- World Water Usage Events in the Home. Pervasive Computing, Springer (2011), 50–69. most comprehensive labeled dataset of hot and cold water ever collected
natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi)
natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) 8AM 2 minutes
bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) 8AM 2 minutes
toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) 8AM 2 minutes
kitchen sink kitchen sink toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) 8AM 2 minutes
kitchen sink kitchen sink toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) template matching: 98% 74% 8AM 2 minutes
kitchen sink kitchen sink toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) template matching: 98% 74% 10 fold cross validation 8AM 2 minutes
kitchen sink kitchen sink toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) template matching: 98% 74% 10 fold cross validation 35% 8AM 2 minutes minimal
two step process: segmentation 70 50 30 pressure(psi) 70 50 30 pressure(psi) standard deviation smoothing operation pressure deltas local maxima (for adjustments/compound)
70 50 30 pressure(psi) 70 50 30 pressure(psi) pressure drop min pressure duration min local maxima max derivative max amplitude LPC frequency characteristics sink flow meter two step process: features extraction xs 1
70 50 30 pressure(psi) 70 50 30 pressure(psi) pressure drop min pressure duration min local maxima max derivative max amplitude LPC frequency characteristics sink flow meter two step process: features extraction xs 1 xd 2 xd 3 xd 4 xd 5 xd 6 xd 7
machine learning overview labeled RF classifier predicted fixture
machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture
machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture one or two examples per fixture
machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture one or two examples per fixture accuracy 40-60%
machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture one or two examples per fixture accuracy 40-60% need more labels!
machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture one or two examples per fixture accuracy 40-60% need more labels! but which ones?
active learning labeled classifier 1 classifier N… randomforest
active learning labeled classifier 1 classifier N unlabeled … randomforest
active learning labeled classifier 1 classifier N unlabeled disagree? … randomforest
active learning labeled classifier 1 classifier N unlabeled disagree? max margin of committee … randomforest need a label margin < 20%
active learning leveraging the homeowner
active learning leveraging the homeowner • select low confidence margin examples
active learning leveraging the homeowner • select low confidence margin examples • ask homeowner for label
active learning leveraging the homeowner • select low confidence margin examples • ask homeowner for label AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo
active learning leveraging the homeowner • select low confidence margin examples • ask homeowner for label AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
simulating labels from homeowner AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
simulating labels from homeowner AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo • ask for two labels every other day AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
simulating labels from homeowner AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo • ask for two labels every other day • one morning and one evening AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
simulating labels from homeowner AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo • ask for two labels every other day • one morning and one evening • only from 8AM-9PM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
10 15 20 25 30 35 40 45 0.65 0.7 0.75 0.8 0.85 Co−Labeling in H1 Number of Labels ValveLevelAccuracyofCoLabel−HMM Co−Labeling Random Labeling simulating labels from homeowner active learning for H1 totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% fixturepredictionaccuracy number of labeled examples
10 15 20 25 30 35 40 45 0.65 0.7 0.75 0.8 0.85 Co−Labeling in H1 Number of Labels ValveLevelAccuracyofCoLabel−HMM Co−Labeling Random Labeling simulating labels from homeowner active learning for H1minimaltrainingset totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% fixturepredictionaccuracy number of labeled examples
10 15 20 25 30 35 40 45 0.65 0.7 0.75 0.8 0.85 Co−Labeling in H1 Number of Labels ValveLevelAccuracyofCoLabel−HMM Co−Labeling Random Labeling simulating labels from homeowner active learning for H1minimaltrainingset totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% fixturepredictionaccuracy number of labeled examples
10 15 20 25 30 35 40 45 0.65 0.7 0.75 0.8 0.85 Co−Labeling in H1 Number of Labels ValveLevelAccuracyofCoLabel−HMM Co−Labeling Random Labeling chosen labels random labeling iteration 1 iteration 3 iteration 5 iteration 10 simulating labels from homeowner active learning for H1minimaltrainingset totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% fixturepredictionaccuracy number of labeled examples
totals totals 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 valve fixture category error bars=std err. active learning iteration accuracy
totals totals 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 valve fixture category error bars=std err. active learning iteration accuracy
totals totals 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 valve fixture category error bars=std err. active learning iteration accuracy
totals totals 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 valve fixture category error bars=std err. active learning iteration accuracy
usion is the secondary bathroom shower for the master bathroom shower. -374 8.5 1.5 -3 6.1 72 1.1 0.8 5.0 0.7 1.5 0.6 -7 18 92 0.6 5.4 2.6 4.9 3.4 2.3 3.5 0.9 5.1 -7 18 0.9 92 1.4 4.9 0.7 4.4 1.4 1.4 7.3 1.0 0.7 3.2 -753 2.1 -1 4.2 67 0.6 2.4 0.8 31 2.5 5.2 -5 1.2 5.0 0.6 18 4.2 88 1.8 7.5 1.5 1.6 5.7 1.0 -5 1.2 0.5 5.3 4.6 10 1.8 89 1.7 1.7 1.4 0.7 3.2 -2 2.9 0.6 81 12 -2 0.8 94 0.6 8.1 -1 6.7 68 -2 2.8 42 -1 1.9 2.9 0.5 25 0.8 95 0.7 -1 2.2 3.1 10 1.3 96 6.6 -290 -3 1.1 0.7 59 18 -3 0.9 0.9 15 60 er close,1 open,2 k close,3 open,4 er close,5 open,6 k close,7 open,8 et close,9 open,10 r close,11 open,12 k close,13 open,14 t open,15 e close,16 open,17
usion is the secondary bathroom shower for the master bathroom shower. -374 8.5 1.5 -3 6.1 72 1.1 0.8 5.0 0.7 1.5 0.6 -7 18 92 0.6 5.4 2.6 4.9 3.4 2.3 3.5 0.9 5.1 -7 18 0.9 92 1.4 4.9 0.7 4.4 1.4 1.4 7.3 1.0 0.7 3.2 -753 2.1 -1 4.2 67 0.6 2.4 0.8 31 2.5 5.2 -5 1.2 5.0 0.6 18 4.2 88 1.8 7.5 1.5 1.6 5.7 1.0 -5 1.2 0.5 5.3 4.6 10 1.8 89 1.7 1.7 1.4 0.7 3.2 -2 2.9 0.6 81 12 -2 0.8 94 0.6 8.1 -1 6.7 68 -2 2.8 42 -1 1.9 2.9 0.5 25 0.8 95 0.7 -1 2.2 3.1 10 1.3 96 6.6 -290 -3 1.1 0.7 59 18 -3 0.9 0.9 15 60 er close,1 open,2 k close,3 open,4 er close,5 open,6 k close,7 open,8 et close,9 open,10 r close,11 open,12 k close,13 open,14 t open,15 e close,16 open,17 dishwasher laundry dishwasher laundry
usion is the secondary bathroom shower for the master bathroom shower. -374 8.5 1.5 -3 6.1 72 1.1 0.8 5.0 0.7 1.5 0.6 -7 18 92 0.6 5.4 2.6 4.9 3.4 2.3 3.5 0.9 5.1 -7 18 0.9 92 1.4 4.9 0.7 4.4 1.4 1.4 7.3 1.0 0.7 3.2 -753 2.1 -1 4.2 67 0.6 2.4 0.8 31 2.5 5.2 -5 1.2 5.0 0.6 18 4.2 88 1.8 7.5 1.5 1.6 5.7 1.0 -5 1.2 0.5 5.3 4.6 10 1.8 89 1.7 1.7 1.4 0.7 3.2 -2 2.9 0.6 81 12 -2 0.8 94 0.6 8.1 -1 6.7 68 -2 2.8 42 -1 1.9 2.9 0.5 25 0.8 95 0.7 -1 2.2 3.1 10 1.3 96 6.6 -290 -3 1.1 0.7 59 18 -3 0.9 0.9 15 60 er close,1 open,2 k close,3 open,4 er close,5 open,6 k close,7 open,8 et close,9 open,10 r close,11 open,12 k close,13 open,14 t open,15 e close,16 open,17 dishwasher laundry dishwasher laundry
implications for NILM
implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp. did you plug in laptop?
implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp. did you plug in laptop? did you recently start the oven?
implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp. did you plug in laptop? did you recently start the oven? are you watching TV?
implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp. did you plug in laptop? did you recently start the oven? are you watching TV? -can potentially start using more home specific features
limitations
limitations responsive cloud architecture
limitations responsive cloud architecture multiple people in a home
limitations responsive cloud architecture multiple people in a home trust in user as “oracle” AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
consumer centered calibration in end-use water monitoring eric c. larson | eclarson.com Assistant Professor Computer Science and Engineering Thank You! eclarson.com eclarson@lyle.smu.edu @ec_larson acknowledgements Belkin, Inc. Shwetak Patel Jon Froehlich Sidhant Gupta Les Atlas

Recommended

2018 Oregon Wine Symposium | Powdery Mildew Management - Andrew Landers
2018 Oregon Wine Symposium | Powdery Mildew Management - Andrew Landers2018 Oregon Wine Symposium | Powdery Mildew Management - Andrew Landers
2018 Oregon Wine Symposium | Powdery Mildew Management - Andrew Landers
Oregon Wine Board
 
Water Study%2c Final Draft%2c 4_15_16
Water Study%2c Final Draft%2c 4_15_16Water Study%2c Final Draft%2c 4_15_16
Water Study%2c Final Draft%2c 4_15_16Alyssa Harmon
 
How to Unlock Your Data Secrets Using ZENTRA Cloud Models
How to Unlock Your Data Secrets Using ZENTRA Cloud ModelsHow to Unlock Your Data Secrets Using ZENTRA Cloud Models
How to Unlock Your Data Secrets Using ZENTRA Cloud Models
METER Group, Inc. USA
 
Gordon Sharp Handout
Gordon Sharp HandoutGordon Sharp Handout
Gordon Sharp Handout
Hayley Pallister
 
Uppgaard EWI 5_6_16final
Uppgaard EWI 5_6_16finalUppgaard EWI 5_6_16final
Uppgaard EWI 5_6_16finalAnders Uppgaard
 
Sed 3 Equipment Procedures And Sampling
Sed 3 Equipment Procedures And SamplingSed 3 Equipment Procedures And Sampling
Sed 3 Equipment Procedures And SamplingUW Discovery Farms
 
HydroSense for Water Management Scientists
HydroSense for Water Management ScientistsHydroSense for Water Management Scientists
HydroSense for Water Management Scientists
Eric Larson
 
Repa_Resume 2015
Repa_Resume 2015Repa_Resume 2015
Repa_Resume 2015Jennifer Repa
 

Recommended

2018 Oregon Wine Symposium | Powdery Mildew Management - Andrew Landers
2018 Oregon Wine Symposium | Powdery Mildew Management - Andrew Landers2018 Oregon Wine Symposium | Powdery Mildew Management - Andrew Landers
2018 Oregon Wine Symposium | Powdery Mildew Management - Andrew Landers
Oregon Wine Board
 
Water Study%2c Final Draft%2c 4_15_16
Water Study%2c Final Draft%2c 4_15_16Water Study%2c Final Draft%2c 4_15_16
Water Study%2c Final Draft%2c 4_15_16Alyssa Harmon
 
How to Unlock Your Data Secrets Using ZENTRA Cloud Models
How to Unlock Your Data Secrets Using ZENTRA Cloud ModelsHow to Unlock Your Data Secrets Using ZENTRA Cloud Models
How to Unlock Your Data Secrets Using ZENTRA Cloud Models
METER Group, Inc. USA
 
Gordon Sharp Handout
Gordon Sharp HandoutGordon Sharp Handout
Gordon Sharp Handout
Hayley Pallister
 
Uppgaard EWI 5_6_16final
Uppgaard EWI 5_6_16finalUppgaard EWI 5_6_16final
Uppgaard EWI 5_6_16finalAnders Uppgaard
 
Sed 3 Equipment Procedures And Sampling
Sed 3 Equipment Procedures And SamplingSed 3 Equipment Procedures And Sampling
Sed 3 Equipment Procedures And SamplingUW Discovery Farms
 
HydroSense for Water Management Scientists
HydroSense for Water Management ScientistsHydroSense for Water Management Scientists
HydroSense for Water Management Scientists
Eric Larson
 
Repa_Resume 2015
Repa_Resume 2015Repa_Resume 2015
Repa_Resume 2015Jennifer Repa
 
Job Talk
Job TalkJob Talk
Job TalkEric Larson
 
Larson.defense
Larson.defenseLarson.defense
Larson.defenseEric Larson
 
Final written info_product
Final written info_productFinal written info_product
Final written info_productannielb
 
Where DSP meets UbiComp
Where DSP meets UbiCompWhere DSP meets UbiComp
Where DSP meets UbiComp
Eric Larson
 
Residential water users' modeling SOTA
Residential water users' modeling SOTAResidential water users' modeling SOTA
Residential water users' modeling SOTA
ACominola
 
Residential water users' modeling SOTA
Residential water users' modeling SOTAResidential water users' modeling SOTA
Residential water users' modeling SOTA
SmartH2O
 
Effectiveness of the telemetric flood monitoring device
Effectiveness of the telemetric flood monitoring deviceEffectiveness of the telemetric flood monitoring device
Effectiveness of the telemetric flood monitoring device
Harhar Caparida
 
Ubi Comp2009 Hydro Sense Final
Ubi Comp2009 Hydro Sense FinalUbi Comp2009 Hydro Sense Final
Ubi Comp2009 Hydro Sense Final
Eric Larson
 
Panel 2: Understanding Risk in Natural and Manmade Systems
Panel 2: Understanding Risk in Natural and Manmade SystemsPanel 2: Understanding Risk in Natural and Manmade Systems
Panel 2: Understanding Risk in Natural and Manmade Systems
ResilienceByDesign
 
The National Water Census
The National Water CensusThe National Water Census
The National Water Census
Kim Beidler
 
K levy chile_geo_health_2013
K levy chile_geo_health_2013K levy chile_geo_health_2013
K levy chile_geo_health_2013Soledad Burgos
 
Ragab R 1 - UEI Day 1 - Kochi Jan18
Ragab R 1 - UEI Day 1 - Kochi Jan18Ragab R 1 - UEI Day 1 - Kochi Jan18
Ragab R 1 - UEI Day 1 - Kochi Jan18
India UK Water Centre (IUKWC)
 
WIPAC Monthly - February 2022
WIPAC Monthly - February 2022WIPAC Monthly - February 2022
WIPAC Monthly - February 2022
Water Industry Process Automation & Control
 
Temporal and spatial assessment of evaporation transpiration an
Temporal and spatial assessment of evaporation transpiration anTemporal and spatial assessment of evaporation transpiration an
Temporal and spatial assessment of evaporation transpiration an
Ahmed Alzubaidi
 
Mission: Magazine, Issue #3 - The Magazine that Addresses Critical Water Issues
Mission: Magazine, Issue #3 - The Magazine that Addresses Critical Water IssuesMission: Magazine, Issue #3 - The Magazine that Addresses Critical Water Issues
Mission: Magazine, Issue #3 - The Magazine that Addresses Critical Water Issues
Xylem Inc.
 
WATER QUALITY PREDICTION
WATER QUALITY PREDICTIONWATER QUALITY PREDICTION
WATER QUALITY PREDICTION
Fasil47
 
Science fair project
Science fair projectScience fair project
Science fair projectStuart3333
 
Science fair project
Science fair projectScience fair project
Science fair project
Stuart3333
 
Testing The Waters Water Quality Testing Session
Testing The Waters Water Quality Testing SessionTesting The Waters Water Quality Testing Session
Testing The Waters Water Quality Testing SessionDane George
 
Project powerpoint
Project powerpoint Project powerpoint
Project powerpoint eldracherda
 
PupilWare Petra 2015
PupilWare Petra 2015PupilWare Petra 2015
PupilWare Petra 2015
Eric Larson
 
Mobile healthforthemasses.2015
Mobile healthforthemasses.2015Mobile healthforthemasses.2015
Mobile healthforthemasses.2015
Eric Larson
 

More Related Content

Similar to Consumer Centered Calibration End Use Water Monitoring

Final written info_product
Final written info_productFinal written info_product
Final written info_productannielb
 
Where DSP meets UbiComp
Where DSP meets UbiCompWhere DSP meets UbiComp
Where DSP meets UbiComp
Eric Larson
 
Residential water users' modeling SOTA
Residential water users' modeling SOTAResidential water users' modeling SOTA
Residential water users' modeling SOTA
ACominola
 
Residential water users' modeling SOTA
Residential water users' modeling SOTAResidential water users' modeling SOTA
Residential water users' modeling SOTA
SmartH2O
 
Effectiveness of the telemetric flood monitoring device
Effectiveness of the telemetric flood monitoring deviceEffectiveness of the telemetric flood monitoring device
Effectiveness of the telemetric flood monitoring device
Harhar Caparida
 
Ubi Comp2009 Hydro Sense Final
Ubi Comp2009 Hydro Sense FinalUbi Comp2009 Hydro Sense Final
Ubi Comp2009 Hydro Sense Final
Eric Larson
 
Panel 2: Understanding Risk in Natural and Manmade Systems
Panel 2: Understanding Risk in Natural and Manmade SystemsPanel 2: Understanding Risk in Natural and Manmade Systems
Panel 2: Understanding Risk in Natural and Manmade Systems
ResilienceByDesign
 
The National Water Census
The National Water CensusThe National Water Census
The National Water Census
Kim Beidler
 
K levy chile_geo_health_2013
K levy chile_geo_health_2013K levy chile_geo_health_2013
K levy chile_geo_health_2013Soledad Burgos
 
Ragab R 1 - UEI Day 1 - Kochi Jan18
Ragab R 1 - UEI Day 1 - Kochi Jan18Ragab R 1 - UEI Day 1 - Kochi Jan18
Ragab R 1 - UEI Day 1 - Kochi Jan18
India UK Water Centre (IUKWC)
 
WIPAC Monthly - February 2022
WIPAC Monthly - February 2022WIPAC Monthly - February 2022
WIPAC Monthly - February 2022
Water Industry Process Automation & Control
 
Temporal and spatial assessment of evaporation transpiration an
Temporal and spatial assessment of evaporation transpiration anTemporal and spatial assessment of evaporation transpiration an
Temporal and spatial assessment of evaporation transpiration an
Ahmed Alzubaidi
 
Mission: Magazine, Issue #3 - The Magazine that Addresses Critical Water Issues
Mission: Magazine, Issue #3 - The Magazine that Addresses Critical Water IssuesMission: Magazine, Issue #3 - The Magazine that Addresses Critical Water Issues
Mission: Magazine, Issue #3 - The Magazine that Addresses Critical Water Issues
Xylem Inc.
 
WATER QUALITY PREDICTION
WATER QUALITY PREDICTIONWATER QUALITY PREDICTION
WATER QUALITY PREDICTION
Fasil47
 
Science fair project
Science fair projectScience fair project
Science fair projectStuart3333
 
Science fair project
Science fair projectScience fair project
Science fair project
Stuart3333
 
Testing The Waters Water Quality Testing Session
Testing The Waters Water Quality Testing SessionTesting The Waters Water Quality Testing Session
Testing The Waters Water Quality Testing SessionDane George
 
Project powerpoint
Project powerpoint Project powerpoint
Project powerpoint eldracherda
 

Similar to Consumer Centered Calibration End Use Water Monitoring (20)

Job Talk
Job TalkJob Talk
Job Talk
 
Larson.defense
Larson.defenseLarson.defense
Larson.defense
 
Final written info_product
Final written info_productFinal written info_product
Final written info_product
 
Where DSP meets UbiComp
Where DSP meets UbiCompWhere DSP meets UbiComp
Where DSP meets UbiComp
 
Residential water users' modeling SOTA
Residential water users' modeling SOTAResidential water users' modeling SOTA
Residential water users' modeling SOTA
 
Residential water users' modeling SOTA
Residential water users' modeling SOTAResidential water users' modeling SOTA
Residential water users' modeling SOTA
 
Effectiveness of the telemetric flood monitoring device
Effectiveness of the telemetric flood monitoring deviceEffectiveness of the telemetric flood monitoring device
Effectiveness of the telemetric flood monitoring device
 
Ubi Comp2009 Hydro Sense Final
Ubi Comp2009 Hydro Sense FinalUbi Comp2009 Hydro Sense Final
Ubi Comp2009 Hydro Sense Final
 
Panel 2: Understanding Risk in Natural and Manmade Systems
Panel 2: Understanding Risk in Natural and Manmade SystemsPanel 2: Understanding Risk in Natural and Manmade Systems
Panel 2: Understanding Risk in Natural and Manmade Systems
 
The National Water Census
The National Water CensusThe National Water Census
The National Water Census
 
K levy chile_geo_health_2013
K levy chile_geo_health_2013K levy chile_geo_health_2013
K levy chile_geo_health_2013
 
Ragab R 1 - UEI Day 1 - Kochi Jan18
Ragab R 1 - UEI Day 1 - Kochi Jan18Ragab R 1 - UEI Day 1 - Kochi Jan18
Ragab R 1 - UEI Day 1 - Kochi Jan18
 
WIPAC Monthly - February 2022
WIPAC Monthly - February 2022WIPAC Monthly - February 2022
WIPAC Monthly - February 2022
 
Temporal and spatial assessment of evaporation transpiration an
Temporal and spatial assessment of evaporation transpiration anTemporal and spatial assessment of evaporation transpiration an
Temporal and spatial assessment of evaporation transpiration an
 
Mission: Magazine, Issue #3 - The Magazine that Addresses Critical Water Issues
Mission: Magazine, Issue #3 - The Magazine that Addresses Critical Water IssuesMission: Magazine, Issue #3 - The Magazine that Addresses Critical Water Issues
Mission: Magazine, Issue #3 - The Magazine that Addresses Critical Water Issues
 
WATER QUALITY PREDICTION
WATER QUALITY PREDICTIONWATER QUALITY PREDICTION
WATER QUALITY PREDICTION
 
Science fair project
Science fair projectScience fair project
Science fair project
 
Science fair project
Science fair projectScience fair project
Science fair project
 
Testing The Waters Water Quality Testing Session
Testing The Waters Water Quality Testing SessionTesting The Waters Water Quality Testing Session
Testing The Waters Water Quality Testing Session
 
Project powerpoint
Project powerpoint Project powerpoint
Project powerpoint
 

More from Eric Larson

PupilWare Petra 2015
PupilWare Petra 2015PupilWare Petra 2015
PupilWare Petra 2015
Eric Larson
 
Mobile healthforthemasses.2015
Mobile healthforthemasses.2015Mobile healthforthemasses.2015
Mobile healthforthemasses.2015
Eric Larson
 
Flipping the clinic: in home health monitoring using mobile phones
Flipping the clinic: in home health monitoring using mobile phonesFlipping the clinic: in home health monitoring using mobile phones
Flipping the clinic: in home health monitoring using mobile phones
Eric Larson
 
First world problems: education, options, and impact
First world problems: education, options, and impactFirst world problems: education, options, and impact
First world problems: education, options, and impact
Eric Larson
 
Recognizing mHealth through phone-as-a-sensor technology
Recognizing mHealth through phone-as-a-sensor technologyRecognizing mHealth through phone-as-a-sensor technology
Recognizing mHealth through phone-as-a-sensor technology
Eric Larson
 
Big Data, Small Data
Big Data, Small DataBig Data, Small Data
Big Data, Small Data
Eric Larson
 
Phone As A Sensor Technology: mHealth and Chronic Disease
Phone As A Sensor Technology: mHealth and Chronic Disease Phone As A Sensor Technology: mHealth and Chronic Disease
Phone As A Sensor Technology: mHealth and Chronic Disease
Eric Larson
 
Commercialization and Broader Impact: mirroring research through commercial d...
Commercialization and Broader Impact: mirroring research through commercial d...Commercialization and Broader Impact: mirroring research through commercial d...
Commercialization and Broader Impact: mirroring research through commercial d...
Eric Larson
 
Creating the Dots: Computer Science and Engineering for Good
Creating the Dots: Computer Science and Engineering for GoodCreating the Dots: Computer Science and Engineering for Good
Creating the Dots: Computer Science and Engineering for Good
Eric Larson
 
Mobilizing mHealth: interdisciplinary computer science and engineering
Mobilizing mHealth: interdisciplinary computer science and engineeringMobilizing mHealth: interdisciplinary computer science and engineering
Mobilizing mHealth: interdisciplinary computer science and engineeringEric Larson
 
Applications and Derivation of Linear Predictive Coding
Applications and Derivation of Linear Predictive CodingApplications and Derivation of Linear Predictive Coding
Applications and Derivation of Linear Predictive CodingEric Larson
 
Sensing for Sustainability: Disaggregated Sensing of Electricity, Gas, and Water
Sensing for Sustainability: Disaggregated Sensing of Electricity, Gas, and WaterSensing for Sustainability: Disaggregated Sensing of Electricity, Gas, and Water
Sensing for Sustainability: Disaggregated Sensing of Electricity, Gas, and WaterEric Larson
 
Ubicomp2012 spiro smartpresentation
Ubicomp2012 spiro smartpresentationUbicomp2012 spiro smartpresentation
Ubicomp2012 spiro smartpresentationEric Larson
 
Machine Learning Lecture
Machine Learning LectureMachine Learning Lecture
Machine Learning Lecture
Eric Larson
 
ACEEE 2012
ACEEE 2012ACEEE 2012
ACEEE 2012
Eric Larson
 
Open cv tutorial
Open cv tutorialOpen cv tutorial
Open cv tutorial
Eric Larson
 
Accurate and Privacy Preserving Cough Sensing from a Low Cost Microphone
Accurate and Privacy Preserving Cough Sensing from a Low Cost MicrophoneAccurate and Privacy Preserving Cough Sensing from a Low Cost Microphone
Accurate and Privacy Preserving Cough Sensing from a Low Cost MicrophoneEric Larson
 
Hydro pervasive2011 eric_larson
Hydro pervasive2011 eric_larsonHydro pervasive2011 eric_larson
Hydro pervasive2011 eric_larson
Eric Larson
 
HeatWave CHI2011
HeatWave CHI2011HeatWave CHI2011
HeatWave CHI2011
Eric Larson
 

More from Eric Larson (20)

PupilWare Petra 2015
PupilWare Petra 2015PupilWare Petra 2015
PupilWare Petra 2015
 
Mobile healthforthemasses.2015
Mobile healthforthemasses.2015Mobile healthforthemasses.2015
Mobile healthforthemasses.2015
 
Flipping the clinic: in home health monitoring using mobile phones
Flipping the clinic: in home health monitoring using mobile phonesFlipping the clinic: in home health monitoring using mobile phones
Flipping the clinic: in home health monitoring using mobile phones
 
First world problems: education, options, and impact
First world problems: education, options, and impactFirst world problems: education, options, and impact
First world problems: education, options, and impact
 
Recognizing mHealth through phone-as-a-sensor technology
Recognizing mHealth through phone-as-a-sensor technologyRecognizing mHealth through phone-as-a-sensor technology
Recognizing mHealth through phone-as-a-sensor technology
 
Big Data, Small Data
Big Data, Small DataBig Data, Small Data
Big Data, Small Data
 
Phone As A Sensor Technology: mHealth and Chronic Disease
Phone As A Sensor Technology: mHealth and Chronic Disease Phone As A Sensor Technology: mHealth and Chronic Disease
Phone As A Sensor Technology: mHealth and Chronic Disease
 
Commercialization and Broader Impact: mirroring research through commercial d...
Commercialization and Broader Impact: mirroring research through commercial d...Commercialization and Broader Impact: mirroring research through commercial d...
Commercialization and Broader Impact: mirroring research through commercial d...
 
Creating the Dots: Computer Science and Engineering for Good
Creating the Dots: Computer Science and Engineering for GoodCreating the Dots: Computer Science and Engineering for Good
Creating the Dots: Computer Science and Engineering for Good
 
Mobilizing mHealth: interdisciplinary computer science and engineering
Mobilizing mHealth: interdisciplinary computer science and engineeringMobilizing mHealth: interdisciplinary computer science and engineering
Mobilizing mHealth: interdisciplinary computer science and engineering
 
Applications and Derivation of Linear Predictive Coding
Applications and Derivation of Linear Predictive CodingApplications and Derivation of Linear Predictive Coding
Applications and Derivation of Linear Predictive Coding
 
BreatheSuite
BreatheSuiteBreatheSuite
BreatheSuite
 
Sensing for Sustainability: Disaggregated Sensing of Electricity, Gas, and Water
Sensing for Sustainability: Disaggregated Sensing of Electricity, Gas, and WaterSensing for Sustainability: Disaggregated Sensing of Electricity, Gas, and Water
Sensing for Sustainability: Disaggregated Sensing of Electricity, Gas, and Water
 
Ubicomp2012 spiro smartpresentation
Ubicomp2012 spiro smartpresentationUbicomp2012 spiro smartpresentation
Ubicomp2012 spiro smartpresentation
 
Machine Learning Lecture
Machine Learning LectureMachine Learning Lecture
Machine Learning Lecture
 
ACEEE 2012
ACEEE 2012ACEEE 2012
ACEEE 2012
 
Open cv tutorial
Open cv tutorialOpen cv tutorial
Open cv tutorial
 
Accurate and Privacy Preserving Cough Sensing from a Low Cost Microphone
Accurate and Privacy Preserving Cough Sensing from a Low Cost MicrophoneAccurate and Privacy Preserving Cough Sensing from a Low Cost Microphone
Accurate and Privacy Preserving Cough Sensing from a Low Cost Microphone
 
Hydro pervasive2011 eric_larson
Hydro pervasive2011 eric_larsonHydro pervasive2011 eric_larson
Hydro pervasive2011 eric_larson
 
HeatWave CHI2011
HeatWave CHI2011HeatWave CHI2011
HeatWave CHI2011
 

Recently uploaded

在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样
在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样
在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样
obonagu
 
Heap Sort (SS).ppt FOR ENGINEERING GRADUATES, BCA, MCA, MTECH, BSC STUDENTS
Heap Sort (SS).ppt FOR ENGINEERING GRADUATES, BCA, MCA, MTECH, BSC STUDENTSHeap Sort (SS).ppt FOR ENGINEERING GRADUATES, BCA, MCA, MTECH, BSC STUDENTS
Heap Sort (SS).ppt FOR ENGINEERING GRADUATES, BCA, MCA, MTECH, BSC STUDENTS
Soumen Santra
 
space technology lecture notes on satellite
space technology lecture notes on satellitespace technology lecture notes on satellite
space technology lecture notes on satellite
ongomchris
 
Pile Foundation by Venkatesh Taduvai (Sub Geotechnical Engineering II)-conver...
Pile Foundation by Venkatesh Taduvai (Sub Geotechnical Engineering II)-conver...Pile Foundation by Venkatesh Taduvai (Sub Geotechnical Engineering II)-conver...
Pile Foundation by Venkatesh Taduvai (Sub Geotechnical Engineering II)-conver...
AJAYKUMARPUND1
 
Building Electrical System Design & Installation
Building Electrical System Design & InstallationBuilding Electrical System Design & Installation
Building Electrical System Design & Installation
symbo111
 
Final project report on grocery store management system..pdf
Final project report on grocery store management system..pdfFinal project report on grocery store management system..pdf
Final project report on grocery store management system..pdf
Kamal Acharya
 
ML for identifying fraud using open blockchain data.pptx
ML for identifying fraud using open blockchain data.pptxML for identifying fraud using open blockchain data.pptx
ML for identifying fraud using open blockchain data.pptx
Vijay Dialani, PhD
 
HYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generationHYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generation
Robbie Edward Sayers
 
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdfAKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
SamSarthak3
 
Investor-Presentation-Q1FY2024 investor presentation document.pptx
Investor-Presentation-Q1FY2024 investor presentation document.pptxInvestor-Presentation-Q1FY2024 investor presentation document.pptx
Investor-Presentation-Q1FY2024 investor presentation document.pptx
AmarGB2
 
Immunizing Image Classifiers Against Localized Adversary Attacks
Immunizing Image Classifiers Against Localized Adversary AttacksImmunizing Image Classifiers Against Localized Adversary Attacks
Immunizing Image Classifiers Against Localized Adversary Attacks
gerogepatton
 
Water Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation and Control Monthly - May 2024.pdfWater Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation & Control
 
block diagram and signal flow graph representation
block diagram and signal flow graph representationblock diagram and signal flow graph representation
block diagram and signal flow graph representation
Divya Somashekar
 
Unbalanced Three Phase Systems and circuits.pptx
Unbalanced Three Phase Systems and circuits.pptxUnbalanced Three Phase Systems and circuits.pptx
Unbalanced Three Phase Systems and circuits.pptx
ChristineTorrepenida1
 
Tutorial for 16S rRNA Gene Analysis with QIIME2.pdf
Tutorial for 16S rRNA Gene Analysis with QIIME2.pdfTutorial for 16S rRNA Gene Analysis with QIIME2.pdf
Tutorial for 16S rRNA Gene Analysis with QIIME2.pdf
aqil azizi
 
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdf
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdfHybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdf
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdf
fxintegritypublishin
 
Hierarchical Digital Twin of a Naval Power System
Hierarchical Digital Twin of a Naval Power SystemHierarchical Digital Twin of a Naval Power System
Hierarchical Digital Twin of a Naval Power System
Kerry Sado
 
AP LAB PPT.pdf ap lab ppt no title specific
AP LAB PPT.pdf ap lab ppt no title specificAP LAB PPT.pdf ap lab ppt no title specific
AP LAB PPT.pdf ap lab ppt no title specific
BrazilAccount1
 
road safety engineering r s e unit 3.pdf
road safety engineering r s e unit 3.pdfroad safety engineering r s e unit 3.pdf
road safety engineering r s e unit 3.pdf
VENKATESHvenky89705
 
Forklift Classes Overview by Intella Parts
Forklift Classes Overview by Intella PartsForklift Classes Overview by Intella Parts
Forklift Classes Overview by Intella Parts
Intella Parts
 

Recently uploaded (20)

在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样
在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样
在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样
 
Heap Sort (SS).ppt FOR ENGINEERING GRADUATES, BCA, MCA, MTECH, BSC STUDENTS
Heap Sort (SS).ppt FOR ENGINEERING GRADUATES, BCA, MCA, MTECH, BSC STUDENTSHeap Sort (SS).ppt FOR ENGINEERING GRADUATES, BCA, MCA, MTECH, BSC STUDENTS
Heap Sort (SS).ppt FOR ENGINEERING GRADUATES, BCA, MCA, MTECH, BSC STUDENTS
 
space technology lecture notes on satellite
space technology lecture notes on satellitespace technology lecture notes on satellite
space technology lecture notes on satellite
 
Pile Foundation by Venkatesh Taduvai (Sub Geotechnical Engineering II)-conver...
Pile Foundation by Venkatesh Taduvai (Sub Geotechnical Engineering II)-conver...Pile Foundation by Venkatesh Taduvai (Sub Geotechnical Engineering II)-conver...
Pile Foundation by Venkatesh Taduvai (Sub Geotechnical Engineering II)-conver...
 
Building Electrical System Design & Installation
Building Electrical System Design & InstallationBuilding Electrical System Design & Installation
Building Electrical System Design & Installation
 
Final project report on grocery store management system..pdf
Final project report on grocery store management system..pdfFinal project report on grocery store management system..pdf
Final project report on grocery store management system..pdf
 
ML for identifying fraud using open blockchain data.pptx
ML for identifying fraud using open blockchain data.pptxML for identifying fraud using open blockchain data.pptx
ML for identifying fraud using open blockchain data.pptx
 
HYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generationHYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generation
 
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdfAKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
 
Investor-Presentation-Q1FY2024 investor presentation document.pptx
Investor-Presentation-Q1FY2024 investor presentation document.pptxInvestor-Presentation-Q1FY2024 investor presentation document.pptx
Investor-Presentation-Q1FY2024 investor presentation document.pptx
 
Immunizing Image Classifiers Against Localized Adversary Attacks
Immunizing Image Classifiers Against Localized Adversary AttacksImmunizing Image Classifiers Against Localized Adversary Attacks
Immunizing Image Classifiers Against Localized Adversary Attacks
 
Water Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation and Control Monthly - May 2024.pdfWater Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation and Control Monthly - May 2024.pdf
 
block diagram and signal flow graph representation
block diagram and signal flow graph representationblock diagram and signal flow graph representation
block diagram and signal flow graph representation
 
Unbalanced Three Phase Systems and circuits.pptx
Unbalanced Three Phase Systems and circuits.pptxUnbalanced Three Phase Systems and circuits.pptx
Unbalanced Three Phase Systems and circuits.pptx
 
Tutorial for 16S rRNA Gene Analysis with QIIME2.pdf
Tutorial for 16S rRNA Gene Analysis with QIIME2.pdfTutorial for 16S rRNA Gene Analysis with QIIME2.pdf
Tutorial for 16S rRNA Gene Analysis with QIIME2.pdf
 
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdf
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdfHybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdf
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdf
 
Hierarchical Digital Twin of a Naval Power System
Hierarchical Digital Twin of a Naval Power SystemHierarchical Digital Twin of a Naval Power System
Hierarchical Digital Twin of a Naval Power System
 
AP LAB PPT.pdf ap lab ppt no title specific
AP LAB PPT.pdf ap lab ppt no title specificAP LAB PPT.pdf ap lab ppt no title specific
AP LAB PPT.pdf ap lab ppt no title specific
 
road safety engineering r s e unit 3.pdf
road safety engineering r s e unit 3.pdfroad safety engineering r s e unit 3.pdf
road safety engineering r s e unit 3.pdf
 
Forklift Classes Overview by Intella Parts
Forklift Classes Overview by Intella PartsForklift Classes Overview by Intella Parts
Forklift Classes Overview by Intella Parts
 

Consumer Centered Calibration End Use Water Monitoring

  • 1. consumer centered calibration in end-use water monitoring eric c. larson | eclarson.com Assistant Professor Computer Science and Engineering
  • 2.
  • 3.
  • 4. on average, a consumer can save 15-25%
  • 5.
  • 6.
  • 9.
  • 10. we are using water faster than it is being replenished Pacific Institute for Studies in Development, Environment, and Security, 2011
  • 11. we are using water faster than it is being replenished Pacific Institute for Studies in Development, Environment, and Security, 2011
  • 12.
  • 13.
  • 16.
  • 20. meters flow rate fixture flow inline water Fabricated"Unit 16
  • 21. meters flow rate fixture flow inline water water pressure pressure sensor Fabricated"Unit 16
  • 22. meters flow rate fixture flow inline water water pressure pressure sensor Fabricated"Unit 16
  • 23. meters flow rate fixture flow inline water water pressure pressure sensor machine learning estimated Fabricated"Unit 16
  • 25. • central sensing point • easy to install • low cost • can observe every fixture HydroSense
  • 26. • central sensing point • easy to install • low cost • can observe every fixture HydroSense BelkinEcho
  • 27. • central sensing point • easy to install • low cost • can observe every fixture HydroSense 40# 50# 60# 70# 80# Cold Line Pressure (Hose Spigot) 0 94.5 time (s) psi BelkinEcho
  • 28. • central sensing point • easy to install • low cost • can observe every fixture HydroSense 40# 50# 60# 70# 80# Cold Line Pressure (Hose Spigot) 0 94.5 time (s) psi BelkinEcho
  • 29. • central sensing point • easy to install • low cost • can observe every fixture HydroSense 40# 50# 60# 70# 80# Cold Line Pressure (Hose Spigot) 0 94.5 time (s) psi open close BelkinEcho
  • 30.
  • 31.
  • 32.
  • 34. kitchen sink upstairs toilet downstairs toilet days 33 33 30 27 33 events 2374 3075 4754 2499 2578 events/day 71.9 93.2 158.5 92.6 78.1 = days 33 33 30 events 2374 3075 4754 events/day 71.9 93.2 158.5
  • 35. kitchen sink upstairs toilet template matching unknown event downstairs toilet
  • 36. kitchen sink upstairs toilet template matching unknown event downstairs toilet
  • 37. feasibility study Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., and Patel, S.N. HydroSense: infrastructure-mediated single-point sensing of whole-home water activity. Proceedings of the 11th ACM international conference on Ubiquitous computing, (2009), 235–244. Larson, E., Froehlich, J., Campbell, T., et al. Disaggregated water sensing from a single, pressure- based sensor: An extended analysis of HydroSense using staged experiments. Pervasive and Mobile Computing, (2010).
  • 38. feasibility study • 10 homes Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., and Patel, S.N. HydroSense: infrastructure-mediated single-point sensing of whole-home water activity. Proceedings of the 11th ACM international conference on Ubiquitous computing, (2009), 235–244. Larson, E., Froehlich, J., Campbell, T., et al. Disaggregated water sensing from a single, pressure- based sensor: An extended analysis of HydroSense using staged experiments. Pervasive and Mobile Computing, (2010).
  • 39. feasibility study • 10 homes • staged calibration Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., and Patel, S.N. HydroSense: infrastructure-mediated single-point sensing of whole-home water activity. Proceedings of the 11th ACM international conference on Ubiquitous computing, (2009), 235–244. Larson, E., Froehlich, J., Campbell, T., et al. Disaggregated water sensing from a single, pressure- based sensor: An extended analysis of HydroSense using staged experiments. Pervasive and Mobile Computing, (2010).
  • 40. feasibility study • 10 homes • staged calibration • ~98% accuracy Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., and Patel, S.N. HydroSense: infrastructure-mediated single-point sensing of whole-home water activity. Proceedings of the 11th ACM international conference on Ubiquitous computing, (2009), 235–244. Larson, E., Froehlich, J., Campbell, T., et al. Disaggregated water sensing from a single, pressure- based sensor: An extended analysis of HydroSense using staged experiments. Pervasive and Mobile Computing, (2010).
  • 44. how well does single point sensing work in a natural setting?
  • 47.
  • 48.
  • 49.
  • 50.
  • 51. totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% data collection Larson, E., Froehlich, J., Saba, E., et al. A Longitudinal Study of Pressure Sensing to Infer Real- World Water Usage Events in the Home. Pervasive Computing, Springer (2011), 50–69.
  • 52. totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% data collection Larson, E., Froehlich, J., Saba, E., et al. A Longitudinal Study of Pressure Sensing to Infer Real- World Water Usage Events in the Home. Pervasive Computing, Springer (2011), 50–69. most comprehensive labeled dataset of hot and cold water ever collected
  • 55. bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) 8AM 2 minutes
  • 56. toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) 8AM 2 minutes
  • 57. kitchen sink kitchen sink toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) 8AM 2 minutes
  • 58. kitchen sink kitchen sink toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) template matching: 98% 74% 8AM 2 minutes
  • 59. kitchen sink kitchen sink toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) template matching: 98% 74% 10 fold cross validation 8AM 2 minutes
  • 60. kitchen sink kitchen sink toilet bathroom sink natural water usage 70 50 30 pressure(psi) 70 50 30 pressure(psi) template matching: 98% 74% 10 fold cross validation 35% 8AM 2 minutes minimal
  • 61. two step process: segmentation 70 50 30 pressure(psi) 70 50 30 pressure(psi) standard deviation smoothing operation pressure deltas local maxima (for adjustments/compound)
  • 62. 70 50 30 pressure(psi) 70 50 30 pressure(psi) pressure drop min pressure duration min local maxima max derivative max amplitude LPC frequency characteristics sink flow meter two step process: features extraction xs 1
  • 63. 70 50 30 pressure(psi) 70 50 30 pressure(psi) pressure drop min pressure duration min local maxima max derivative max amplitude LPC frequency characteristics sink flow meter two step process: features extraction xs 1 xd 2 xd 3 xd 4 xd 5 xd 6 xd 7
  • 64. machine learning overview labeled RF classifier predicted fixture
  • 65. machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture
  • 66. machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture one or two examples per fixture
  • 67. machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture one or two examples per fixture accuracy 40-60%
  • 68. machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture one or two examples per fixture accuracy 40-60% need more labels!
  • 69. machine learning overview minimal set of labels for calibrationlabeled RF classifier predicted fixture one or two examples per fixture accuracy 40-60% need more labels! but which ones?
  • 70. active learning labeled classifier 1 classifier N… randomforest
  • 71. active learning labeled classifier 1 classifier N unlabeled … randomforest
  • 72. active learning labeled classifier 1 classifier N unlabeled disagree? … randomforest
  • 73. active learning labeled classifier 1 classifier N unlabeled disagree? max margin of committee … randomforest need a label margin < 20%
  • 75. active learning leveraging the homeowner • select low confidence margin examples
  • 76. active learning leveraging the homeowner • select low confidence margin examples • ask homeowner for label
  • 77. active learning leveraging the homeowner • select low confidence margin examples • ask homeowner for label AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo
  • 78. active learning leveraging the homeowner • select low confidence margin examples • ask homeowner for label AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
  • 79. simulating labels from homeowner AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
  • 80. simulating labels from homeowner AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo • ask for two labels every other day AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
  • 81. simulating labels from homeowner AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo • ask for two labels every other day • one morning and one evening AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
  • 82. simulating labels from homeowner AT&T LTEAT&T LTE 5:23 PM did you just use water? YesNo • ask for two labels every other day • one morning and one evening • only from 8AM-9PM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
  • 83. 10 15 20 25 30 35 40 45 0.65 0.7 0.75 0.8 0.85 Co−Labeling in H1 Number of Labels ValveLevelAccuracyofCoLabel−HMM Co−Labeling Random Labeling simulating labels from homeowner active learning for H1 totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% fixturepredictionaccuracy number of labeled examples
  • 84. 10 15 20 25 30 35 40 45 0.65 0.7 0.75 0.8 0.85 Co−Labeling in H1 Number of Labels ValveLevelAccuracyofCoLabel−HMM Co−Labeling Random Labeling simulating labels from homeowner active learning for H1minimaltrainingset totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% fixturepredictionaccuracy number of labeled examples
  • 85. 10 15 20 25 30 35 40 45 0.65 0.7 0.75 0.8 0.85 Co−Labeling in H1 Number of Labels ValveLevelAccuracyofCoLabel−HMM Co−Labeling Random Labeling simulating labels from homeowner active learning for H1minimaltrainingset totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% fixturepredictionaccuracy number of labeled examples
  • 86. 10 15 20 25 30 35 40 45 0.65 0.7 0.75 0.8 0.85 Co−Labeling in H1 Number of Labels ValveLevelAccuracyofCoLabel−HMM Co−Labeling Random Labeling chosen labels random labeling iteration 1 iteration 3 iteration 5 iteration 10 simulating labels from homeowner active learning for H1minimaltrainingset totals days 33 33 30 27 33 156 events 2374 3075 4754 2499 2578 14,960 events/day 71.9 93.2 158.5 92.6 78.1 95.9 compound 22.2% 21.8% 16.6% 32% 21.3% 21.9% fixturepredictionaccuracy number of labeled examples
  • 87. totals totals 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 valve fixture category error bars=std err. active learning iteration accuracy
  • 88. totals totals 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 valve fixture category error bars=std err. active learning iteration accuracy
  • 89. totals totals 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 valve fixture category error bars=std err. active learning iteration accuracy
  • 90. totals totals 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 valve fixture category error bars=std err. active learning iteration accuracy
  • 91. usion is the secondary bathroom shower for the master bathroom shower. -374 8.5 1.5 -3 6.1 72 1.1 0.8 5.0 0.7 1.5 0.6 -7 18 92 0.6 5.4 2.6 4.9 3.4 2.3 3.5 0.9 5.1 -7 18 0.9 92 1.4 4.9 0.7 4.4 1.4 1.4 7.3 1.0 0.7 3.2 -753 2.1 -1 4.2 67 0.6 2.4 0.8 31 2.5 5.2 -5 1.2 5.0 0.6 18 4.2 88 1.8 7.5 1.5 1.6 5.7 1.0 -5 1.2 0.5 5.3 4.6 10 1.8 89 1.7 1.7 1.4 0.7 3.2 -2 2.9 0.6 81 12 -2 0.8 94 0.6 8.1 -1 6.7 68 -2 2.8 42 -1 1.9 2.9 0.5 25 0.8 95 0.7 -1 2.2 3.1 10 1.3 96 6.6 -290 -3 1.1 0.7 59 18 -3 0.9 0.9 15 60 er close,1 open,2 k close,3 open,4 er close,5 open,6 k close,7 open,8 et close,9 open,10 r close,11 open,12 k close,13 open,14 t open,15 e close,16 open,17
  • 92. usion is the secondary bathroom shower for the master bathroom shower. -374 8.5 1.5 -3 6.1 72 1.1 0.8 5.0 0.7 1.5 0.6 -7 18 92 0.6 5.4 2.6 4.9 3.4 2.3 3.5 0.9 5.1 -7 18 0.9 92 1.4 4.9 0.7 4.4 1.4 1.4 7.3 1.0 0.7 3.2 -753 2.1 -1 4.2 67 0.6 2.4 0.8 31 2.5 5.2 -5 1.2 5.0 0.6 18 4.2 88 1.8 7.5 1.5 1.6 5.7 1.0 -5 1.2 0.5 5.3 4.6 10 1.8 89 1.7 1.7 1.4 0.7 3.2 -2 2.9 0.6 81 12 -2 0.8 94 0.6 8.1 -1 6.7 68 -2 2.8 42 -1 1.9 2.9 0.5 25 0.8 95 0.7 -1 2.2 3.1 10 1.3 96 6.6 -290 -3 1.1 0.7 59 18 -3 0.9 0.9 15 60 er close,1 open,2 k close,3 open,4 er close,5 open,6 k close,7 open,8 et close,9 open,10 r close,11 open,12 k close,13 open,14 t open,15 e close,16 open,17 dishwasher laundry dishwasher laundry
  • 93. usion is the secondary bathroom shower for the master bathroom shower. -374 8.5 1.5 -3 6.1 72 1.1 0.8 5.0 0.7 1.5 0.6 -7 18 92 0.6 5.4 2.6 4.9 3.4 2.3 3.5 0.9 5.1 -7 18 0.9 92 1.4 4.9 0.7 4.4 1.4 1.4 7.3 1.0 0.7 3.2 -753 2.1 -1 4.2 67 0.6 2.4 0.8 31 2.5 5.2 -5 1.2 5.0 0.6 18 4.2 88 1.8 7.5 1.5 1.6 5.7 1.0 -5 1.2 0.5 5.3 4.6 10 1.8 89 1.7 1.7 1.4 0.7 3.2 -2 2.9 0.6 81 12 -2 0.8 94 0.6 8.1 -1 6.7 68 -2 2.8 42 -1 1.9 2.9 0.5 25 0.8 95 0.7 -1 2.2 3.1 10 1.3 96 6.6 -290 -3 1.1 0.7 59 18 -3 0.9 0.9 15 60 er close,1 open,2 k close,3 open,4 er close,5 open,6 k close,7 open,8 et close,9 open,10 r close,11 open,12 k close,13 open,14 t open,15 e close,16 open,17 dishwasher laundry dishwasher laundry
  • 95. implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
  • 96. implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp. did you plug in laptop?
  • 97. implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp. did you plug in laptop? did you recently start the oven?
  • 98. implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp. did you plug in laptop? did you recently start the oven? are you watching TV?
  • 99. implications for NILM AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp. did you plug in laptop? did you recently start the oven? are you watching TV? -can potentially start using more home specific features
  • 103. limitations responsive cloud architecture multiple people in a home trust in user as “oracle” AT&T LTEAT&T LTE 5:23 PM Fixture Selection Do Not Disturb Select Notification Times OFF Master Toilet Recently Used: Half Bath Toilet Dishwasher Master Sink Select Temp. Kitchen Sink Select Temp. Master Shower Select Temp. More Half Bath Sink Select Temp.
  • 104. consumer centered calibration in end-use water monitoring eric c. larson | eclarson.com Assistant Professor Computer Science and Engineering Thank You! eclarson.com eclarson@lyle.smu.edu @ec_larson acknowledgements Belkin, Inc. Shwetak Patel Jon Froehlich Sidhant Gupta Les Atlas