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1Twitter - Top 10 global health challenges
https://twitter.com/FyezahJehan/status/1317151170532696068
4 years ago by @becker
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mother
weight
challenge
air
child
challenges
global
bmi
malnutrition
health
pollution
motherweightchallengeairchildchallengesglobalbmimalnutritionhealthpollution
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2jamesdlow/open-airplay: A collection of libraries for Apple's AirPlay protocol
https://github.com/jamesdlow/open-airplay
6 years ago by @becker
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linux
apple
play
client
air
airplay
ios
mac
linuxappleplayclientairairplayiosmac
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1senseBox | Die Kiste mit Sinn
https://sensebox.de/
6 years ago by @becker
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sensorbox
everyaware
project
air
sensor
p2map
box
eva
quality
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sensorboxeveryawareprojectairsensorp2mapboxevaqualitypollution
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2Feinstaubalarm in Stuttgart? | Live-Messwerte Stuttgart & Region - Stuttgarter Zeitung
https://scicar409635912018.sched.com/event/FmNX
6 years ago by @becker
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set
dataset
germany
data
everyaware
air
p2map
eva
quality
setdatasetgermanydataeveryawareairp2mapevaquality
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1Air Quality Measures on the National Environmental Health Tracking Network - Data.gov
https://catalog.data.gov/dataset/air-quality-measures-on-the-national-environmental-health-tracking-network
6 years ago by @becker
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dataset
usa
data
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air
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gov
eva
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setdatasetusadataeveryawareairp2mapgovevaquality
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1London Air Quality Network » Annual Pollution Maps
https://www.londonair.org.uk/london/asp/annualmaps.asp
6 years ago by @becker
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dataset
data
air
map
p2map
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london
quality
datasetdataairmapp2mapmodellondonquality
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1Luftverschmutzung in Stadtring Süd, Würzburg: Echtzeit-Karte des Luftqualitätsindex
http://aqicn.org/map/germany/bayern/wurzburg/stadtring-sud/de/
6 years ago by @becker
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everyaware
air
aqi
index
p2map
eva
quality
everyawareairaqiindexp2mapevaquality
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1Airnet: a Machine Learning Dataset for Air Quality Forecasting - Semantic Scholar
https://www.semanticscholar.org/paper/Airnet%3A-a-Machine-Learning-Dataset-for-Air-Quality-XTRACTION/57e9c34b0c0ca1f5510f2be161888730ac67e02e
6 years ago by @becker
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air
lur
p2map
network
eva
quality
nn
pollution
datasetneuralairlurp2mapnetworkevaqualitynnpollution
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3luftdaten.info – Feinstaub selber messen – Open Data und Citizen Science aus Stuttgart
http://luftdaten.info/
7 years ago by @becker
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code
everyaware
air
codefor
arduino
p2map
scicar
eva
quality
platform
codeeveryawareaircodeforarduinop2mapscicarevaqualityplatform
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1Daten | Umweltbundesamt
Contact: Neuberger * Are the raw data available? * Are the models available (as shown on maps)?
7 years ago by @becker
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environment
earth
data
air
scicar
quality
environmentearthdataairscicarquality
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1Hawa Dawa | Know your air. Empower yourself.
A novel solution for fighting urban air pollution.
7 years ago by @hotho
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aware
related
air
every
pollution
awarerelatedaireverypollution
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1Air Quality Sensor Makes a Fashion Statement : TreeHugger
http://www.treehugger.com/clean-technology/air-quality-sensor-makes-a-fashion-statement.html
7 years ago by @becker
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sensorbox
air
sensor
quality
pollution
sensorboxairsensorqualitypollution
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1Carnegie Mellon Develops a Trio of Portable Air and Water Pollution Sensors : TreeHugger
http://www.treehugger.com/gadgets/airbot-and-waterbot-are-portable-air-and-water-pollution-detectors.html
7 years ago by @becker
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sensorbox
air
sensor
mobile
box
water
pollution
sensorboxairsensormobileboxwaterpollution
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2Worldwide Air Pollution Map and live air quality levels
Follow air quality in your city in real-time, and protect yourself from pollution thanks to our personalized advice and hourly forecasts.
9 years ago by @hotho
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everyaware
air
quality
pollution
everyawareairqualitypollution
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1Common Sense — Mobile sensing for community action
http://www.communitysensing.org/index.php
9 years ago by @becker
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sensing
eva21
everyaware
air
collective
eva
quality
participatory
sensingeva21everyawareaircollectiveevaqualityparticipatory
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1nQuire It
http://www.nquire-it.org/#/home
9 years ago by @becker
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sensing
widenoise
phone
air
noise
airprobe
nquire
eva
cell
smart
sensingwidenoisephoneairnoiseairprobenquireevacellsmart
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2Public/Publications – OpenSense
http://www.opensense.ethz.ch/trac/wiki/Public/Publications
9 years ago by @becker
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eva21
air
opensense
airprobe
quality
eva21airopensenseairprobequality
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1Air Quality Modeling
http://www.aqbook.org/read/?page=248
9 years ago by @becker
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modeling
book
air
model
eva
quality
modelingbookairmodelevaquality
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1Göttingen, Germany Air Pollution: Real-time PM2.5 Air Quality Index (AQI)
http://aqicn.org/city/germany/niedersachsen/gottingen/#map
9 years ago by @hotho
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visualization
data
everyaware
air
quality
visualizationdataeveryawareairquality
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1Indoor air quality monitoring & health...
https://forum.quantifiedself.com/thread-indoor-air-quality-monitoring-health
10 years ago by @becker
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co2
2014
indoor
project
air
eva
quality
co22014indoorprojectairevaquality
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publications (hide)56
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13OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning
F. Lautenschlager, M. Becker, K. Kobs, M. Steininger, P. Davidson, A. Krause, and A. Hotho. Atmospheric Environment, (2020)
3 years ago by @hotho
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myown
air
lur
2020
cv1
pollution
myownairlur2020cv1pollution
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12MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images
M. Steininger, K. Kobs, A. Zehe, F. Lautenschlager, M. Becker, and A. Hotho. ACM Trans. Spatial Algorithms Syst., (April 2020)
3 years ago by @hotho
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myown
deep
Land-use
regression
air
learning
2020
cv1
pollution
myowndeepLand-useregressionairlearning2020cv1pollution
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13OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning
F. Lautenschlager, M. Becker, K. Kobs, M. Steininger, P. Davidson, A. Krause, and A. Hotho. Atmospheric Environment, (2020)
4 years ago by @becker
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automl
project:bmbf
myown
use
everyaware
air
lur
quality
eva
optimization
bayes
regression
land
open
automlproject:bmbfmyownuseeveryawareairlurqualityevaoptimizationbayesregressionlandopen
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12MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images
M. Steininger, K. Kobs, A. Zehe, F. Lautenschlager, M. Becker, and A. Hotho. ACM Transactions on Spatial Algorithms and Systems (TSAS), 6 (3): 1--24 (2020)
4 years ago by @becker
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image
project:bmbf
mapping
myown
cnn
neural
air
network
networks
quality
p21
street
prediction
map
open
imageproject:bmbfmappingmyowncnnneuralairnetworknetworksqualityp21streetpredictionmapopen
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1Analysing the performance of low-cost air quality sensors, their drivers, relative benefits and calibration in cities---a case study in Sheffield
S. Munir, M. Mayfield, D. Coca, S. Jubb, and O. Osammor. Environmental Monitoring and Assessment, 191 (2): 94 (Jan 22, 2019)
5 years ago by @becker
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sensors
emote
evaluation
test
air
review
sensor
plolution
eva
quality
sensorsemoteevaluationtestairreviewsensorplolutionevaquality
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5Air Trails--Urban Air Quality Campaign Exploration Patterns
M. Becker, F. Lautenschlager, and A. Hotho. Proceedings of VGI-ALIVE 2018 Workshop, colocated with AGILE 2018, (2018)
5 years ago by @becker
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hyptrails
myown
bayesian
comparison
bayes
mixedtrails
everyaware
air
p2map
model
eva
hyptrailsmyownbayesiancomparisonbayesmixedtrailseveryawareairp2mapmodeleva
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3W-Air: Enabling Personal Air Pollution Monitoring on Wearables
B. Maag, Z. Zhou, and L. Thiele. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2 (1): 24 (2018)
6 years ago by @becker
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airprobe2
neural
everyaware
air
p2map
network
airprobe
eva
calibration
quality
nn
airprobe2neuraleveryawareairp2mapnetworkairprobeevacalibrationqualitynn
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2Variability in and Agreement between Modeled and Personal Continuously Measured Black Carbon Levels Using Novel Smartphone and Sensor Technologies
M. Nieuwenhuijsen, D. Donaire-Gonzalez, I. Rivas, M. de Castro, M. Cirach, G. Hoek, E. Seto, M. Jerrett, and J. Sunyer. Environmental Science & Technology, 49 (5): 2977--2982 (February 2015)
6 years ago by @becker
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bc
mapping
pm2.5
air
black
pm25
quality
eva
school
carbon
2.5
map
p2map
model
pm
bcmappingpm2.5airblackpm25qualityevaschoolcarbon2.5mapp2mapmodelpm
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3A Neural Attention Model for Urban Air Quality Inference: Learning the Weights of Monitoring Stations
W. Cheng, Y. Shen, Y. Zhu, and L. Huang. AAAI, (2018)
6 years ago by @becker
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neural
everyaware
air
attention
p2map
model
network
eva
quality
nn
neuraleveryawareairattentionp2mapmodelnetworkevaqualitynn
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3Machine learning and air quality modeling
C. Keller, M. Evans, J. Kutz, and S. Pawson. Big Data (Big Data), 2017 IEEE International Conference on, page 4570--4576. IEEE, (2017)
6 years ago by @becker
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random
forest
machine
air
learning
p2map
quality
pollution
randomforestmachineairlearningp2mapqualitypollution
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2Self-Adaptive Revised Land Use Regression Models for Estimating PM2. 5 Concentrations in Beijing, China
L. Hu, J. Liu, and Z. He. Sustainability, 8 (8): 786 (2016)
6 years ago by @becker
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linear
use
air
osm
lur
quality
eva
pollution
citedby:scholar:count:4
regression
street
land
prediction
citedby:scholar:timestamp:2018-2-21
map
p2map
open
linearuseairosmlurqualityevapollutioncitedby:scholar:count:4regressionstreetlandpredictioncitedby:scholar:timestamp:2018-2-21mapp2mapopen
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2Land use regression models for ultrafine particles in six European areas
E. van Nunen, R. Vermeulen, M. Tsai, N. Probst-Hensch, A. Ineichen, M. Davey, M. Imboden, R. Ducret-Stich, A. Naccarati, D. Raffaele and 1 other author(s). Environmental science & technology, 51 (6): 3336--3345 (2017)
6 years ago by @becker
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use
air
lur
osm
citedby:scholar:count:7
quality
eva
pollution
features
regression
street
land
citedby:scholar:timestamp:2018-2-21
map
p2map
open
useairlurosmcitedby:scholar:count:7qualityevapollutionfeaturesregressionstreetlandcitedby:scholar:timestamp:2018-2-21mapp2mapopen
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6Exploring the modeling of spatiotemporal variations in ambient air pollution within the land use regression framework: Estimation of PM10 concentrations on a daily basis
M. Alam, and A. McNabola. Journal of the Air & Waste Management Association, 65 (5): 628-640 (2015)PMID: 25947321.
6 years ago by @becker
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use
roads
air
lur
osm
quality
eva
pollution
features
regression
street
land
prediction
map
p2map
open
useroadsairlurosmqualityevapollutionfeaturesregressionstreetlandpredictionmapp2mapopen
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3ADVANCING THE USE OF MOBILE MONITORING DATA FOR AIR POLLUTION MODELLING
M. Adams. (2015)
6 years ago by @becker
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neural
use
air
lur
networks
quality
eva
pollution
regression
land
prediction
p2map
nn
neuraluseairlurnetworksqualityevapollutionregressionlandpredictionp2mapnn
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6Exploring the modeling of spatiotemporal variations in ambient air pollution within the land use regression framework: Estimation of PM10 concentrations on a daily basis
M. Alam, and A. McNabola. Journal of the Air & Waste Management Association, 65 (5): 628--640 (2015)
6 years ago by @becker
show all tags
neural
use
air
lur
citedby:scholar:count:7
network
non
quality
eva
pm10
pollution
regression
parametric
land
citedby:scholar:timestamp:2018-2-21
p2map
nn
neuraluseairlurcitedby:scholar:count:7networknonqualityevapm10pollutionregressionparametriclandcitedby:scholar:timestamp:2018-2-21p2mapnn
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2Mapping real-time air pollution health risk for environmental management: combining mobile and stationary air pollution monitoring with neural network models
M. Adams, and P. Kanaroglou. Journal of environmental management, (2016)
6 years ago by @becker
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citedby:scholar:count:31
neural
use
air
lur
mobile
network
quality
eva
pollution
stationary
regression
land
prediction
citedby:scholar:timestamp:2018-2-21
p2map
nn
citedby:scholar:count:31neuraluseairlurmobilenetworkqualityevapollutionstationaryregressionlandpredictioncitedby:scholar:timestamp:2018-2-21p2mapnn
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3A Spatiotemporal Prediction Framework for Air Pollution Based on Deep RNN
J. Fan, Q. Li, J. Hou, X. Feng, H. Karimian, and S. Lin. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, (2017)
6 years ago by @becker
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deep
neural
use
air
lur
network
quality
eva
pollution
regression
land
p2map
temporal
nn
deepneuraluseairlurnetworkqualityevapollutionregressionlandp2maptemporalnn
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1Land Use Random Forests for Estimation of Exposure to Elemental Components of Particulate Matter
R. Brokamp. University of Cincinnati, (2016)
6 years ago by @becker
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forest
use
air
lur
learning
lurf
quality
eva
pollution
random
variance
machine
regression
dissertation
land
p2map
pm
forestuseairlurlearninglurfqualityevapollutionrandomvariancemachineregressiondissertationlandp2mappm
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3Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches
C. Brokamp, R. Jandarov, M. Rao, G. LeMasters, and P. Ryan. Atmospheric Environment, (2017)
6 years ago by @becker
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comparison
linear
forest
citedby:scholar:count:11
use
air
lur
learning
quality
eva
pollution
random
machine
regression
land
citedby:scholar:timestamp:2018-2-21
p2map
ml
comparisonlinearforestcitedby:scholar:count:11useairlurlearningqualityevapollutionrandommachineregressionlandcitedby:scholar:timestamp:2018-2-21p2mapml
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2Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part A: Ozone and nitrogen dioxide
L. Spinelle, M. Gerboles, M. Villani, M. Aleixandre, and F. Bonavitacola. Sensors and Actuators B: Chemical, 215 (Supplement C): 249 - 257 (2015)
7 years ago by @becker
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no
ann
nose
o3
neural
air
network
quality
pollution
no2
sensors
multiple
sensor
p2map
calibration
nn
noannnoseo3neuralairnetworkqualitypollutionno2sensorsmultiplesensorp2mapcalibrationnn
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