On the public citation graph

A Survey on Sensor Calibration in Air Pollution Monitoring Deployments

https://doi.org/10.1109/jiot.2018.2853660
0 signed · 409 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-03071-5_3openalex-snapshot
On Rendezvous in Mobile Sensing Networks
inferredcites →https://doi.org/10.1007/978-3-319-22482-4_58openalex-snapshot
Blind Calibration of Mobile Sensors Using Informed Nonnegative Matrix Factorization
inferredcites →https://doi.org/10.1007/978-3-319-55077-0_38openalex-snapshot
Stochastic Comparison of Machine Learning Approaches to Calibration of Mobile Air Quality Monitors
inferredcites →https://doi.org/10.1007/978-3-319-62398-6_31openalex-snapshot
Computational Intelligence for Smart Air Quality Monitors Calibration
inferredcites →https://doi.org/10.1007/978-3-642-28169-3_15openalex-snapshot
On-the-Fly Calibration of Low-Cost Gas Sensors
inferredcites →https://doi.org/10.1007/978-981-10-4322-2_8openalex-snapshot
A Transfer Learning Approach for Correcting Instrumental Variation and Time-Varying Drift
inferredcites →https://doi.org/10.1016/j.aca.2014.05.054openalex-snapshot
Calibration transfer between electronic nose systems for rapid In situ measurement of pulp and paper industry emissions
inferredcites →https://doi.org/10.1016/j.atmosenv.2005.04.015openalex-snapshot
Flow field measurements in the proximity of an urban intersection in London, UK
inferredcites →https://doi.org/10.1016/j.atmosenv.2012.11.060openalex-snapshot
The use of electrochemical sensors for monitoring urban air quality in low-cost, high-density networks
inferredcites →https://doi.org/10.1016/j.atmosenv.2016.10.024openalex-snapshot
Development of a baseline-temperature correction methodology for electrochemical sensors and its implications for long-term stability
inferredcites →https://doi.org/10.1016/j.buildenv.2010.05.005openalex-snapshot
Detection of human effluents by a MOS gas sensor in correlation to VOC quantification by GC/MS
inferredcites →https://doi.org/10.1016/j.comcom.2010.02.006openalex-snapshot
Trust management systems for wireless sensor networks: Best practices
inferredcites →https://doi.org/10.1016/j.envint.2016.12.007openalex-snapshot
Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?
inferredcites →https://doi.org/10.1016/j.envpol.2015.01.013openalex-snapshot
A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi'an, China
inferredcites →https://doi.org/10.1016/j.envpol.2015.08.035openalex-snapshot
On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter
inferredcites →https://doi.org/10.1016/j.envpol.2017.09.042openalex-snapshot
Node-to-node field calibration of wireless distributed air pollution sensor network
inferredcites →https://doi.org/10.1016/j.scitotenv.2014.09.059openalex-snapshot
On the feasibility of measuring urban air pollution by wireless distributed sensor networks
inferredcites →https://doi.org/10.1016/j.scitotenv.2017.06.266openalex-snapshot
End-user perspective of low-cost sensors for outdoor air pollution monitoring
inferredcites →https://doi.org/10.1016/j.snb.2005.02.008openalex-snapshot
Gas sensor network for air-pollution monitoring
inferredcites →https://doi.org/10.1016/j.snb.2006.04.058openalex-snapshot
Calibration of a multivariate gas sensing device for atmospheric pollution measurement
inferredcites →https://doi.org/10.1016/j.snb.2007.09.060openalex-snapshot
On field calibration of an electronic nose for benzene estimation in an urban pollution monitoring scenario
inferredcites →https://doi.org/10.1016/j.snb.2007.11.009openalex-snapshot
Characterisation of humidity dependence of a metal oxide semiconductor sensor array using partial least squares
inferredcites →https://doi.org/10.1016/j.snb.2009.08.041openalex-snapshot
CO, NO2 and NOx urban pollution monitoring with on-field calibrated electronic nose by automatic bayesian regularization
inferredcites →https://doi.org/10.1016/j.snb.2011.08.079openalex-snapshot
On-line sensor calibration transfer among electronic nose instruments for monitoring volatile organic chemicals in indoor air quality
inferredcites →https://doi.org/10.1016/j.snb.2013.08.006openalex-snapshot
Enabling a transferable calibration model for metal-oxide type electronic noses
inferredcites →https://doi.org/10.1016/j.snb.2014.11.032openalex-snapshot
Approach for quantification of metal oxide type semiconductor gas sensors used for ambient air quality monitoring
inferredcites →https://doi.org/10.1016/j.snb.2015.03.031openalex-snapshot
Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part A: Ozone and nitrogen dioxide
inferredcites →https://doi.org/10.1016/j.snb.2015.05.060openalex-snapshot
Improving the transfer ability of prediction models for electronic noses
inferredcites →https://doi.org/10.1016/j.snb.2015.11.058openalex-snapshot
Calibration transfer and drift compensation of e-noses via coupled task learning
inferredcites →https://doi.org/10.1016/j.snb.2016.03.038openalex-snapshot
Dynamic neural network architectures for on field stochastic calibration of indicative low cost air quality sensing systems
inferredcites →https://doi.org/10.1016/j.snb.2016.05.089openalex-snapshot
Calibration transfer and drift counteraction in chemical sensor arrays using Direct Standardization
inferredcites →https://doi.org/10.1016/j.snb.2016.07.036openalex-snapshot
Field calibration of a cluster of low-cost commercially available sensors for air quality monitoring. Part B: NO, CO and CO2
inferredcites →https://doi.org/10.1016/j.snb.2016.09.020openalex-snapshot
Electrochemical ozone sensors: A miniaturised alternative for ozone measurements in laboratory experiments and air-quality monitoring
inferredcites →https://doi.org/10.1016/j.snb.2016.10.006openalex-snapshot
Development of a normalized multi-sensors system for low cost on-line atmospheric pollution detection
inferredcites →https://doi.org/10.1016/j.snb.2017.07.155openalex-snapshot
Calibrating chemical multisensory devices for real world applications: An in-depth comparison of quantitative machine learning approaches
inferredcites →https://doi.org/10.1016/j.teac.2016.06.001openalex-snapshot
Crowd-sourced air quality studies: A review of the literature & portable sensors
inferredcites →https://doi.org/10.1016/s0925-4005(01)00620-7openalex-snapshot
Nanostructured thick-film gas sensors for atmospheric pollutant monitoring: quantitative analysis on field tests
inferredcites →https://doi.org/10.1016/s1352-2310(00)00330-7openalex-snapshot
Exposure assessment of air pollutants: a review on spatial heterogeneity and indoor/outdoor/personal exposure to suspended particulate matter, nitrogen dioxide and ozone
inferredcites →https://doi.org/10.1016/s1352-2310(99)00272-1openalex-snapshot
Indoor air quality and health
inferredcites →https://doi.org/10.1021/ac00036a012openalex-snapshot
Chemical sensors
inferredcites →https://doi.org/10.1021/acssensors.7b00620openalex-snapshot
Amperometric Gas Sensors as a Low Cost Emerging Technology Platform for Air Quality Monitoring Applications: A Review
inferredcites →https://doi.org/10.1038/srep24382openalex-snapshot
Self Calibrated Wireless Distributed Environmental Sensory Networks
inferredcites →https://doi.org/10.1039/c0an00387eopenalex-snapshot
Support vector machine regression (SVR/LS-SVM)—an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data
inferredcites →https://doi.org/10.1039/c5em00365bopenalex-snapshot
Determining PM 2.5 calibration curves for a low-cost particle monitor: common indoor residential aerosols
inferredcites →https://doi.org/10.1039/c5fd00201jopenalex-snapshot
Evaluating the performance of low cost chemical sensors for air pollution research
inferredcites →https://doi.org/10.1080/02786826.2015.1100710openalex-snapshot
Laboratory Evaluation and Calibration of Three Low-Cost Particle Sensors for Particulate Matter Measurement
inferredcites →https://doi.org/10.1088/0957-0233/2/5/008openalex-snapshot
Artificial neural networks and gas sensor arrays: quantification of individual components in a gas mixture
inferredcites →https://doi.org/10.1109/aim.2016.7576904openalex-snapshot
Enhancing measurement quality through active sampling in mobile air quality monitoring sensor networks
inferredcites →https://doi.org/10.1109/dcoss.2013.12openalex-snapshot
Model-Driven Accuracy Bounds for Noisy Sensor Readings
inferredcites →https://doi.org/10.1109/icassp.2016.7472216openalex-snapshot
Blind mobile sensor calibration using an informed nonnegative matrix factorization with a relaxed rendezvous model
inferredcites →https://doi.org/10.1109/icsens.2015.7370258openalex-snapshot
Model-based rendezvous calibration of mobile sensor networks for monitoring air quality
inferredcites →https://doi.org/10.1109/infocom.2017.8056962openalex-snapshot
Multihop calibration for mobile sensing: K-hop Calibratability and reference sensor deployment
inferredcites →https://doi.org/10.1109/jsen.2016.2582539openalex-snapshot
Blind Drift Calibration of Sensor Networks using Sparse Bayesian Learning
inferredcites →https://doi.org/10.1109/mass.2017.56openalex-snapshot
Opportunistic Multiparty Calibration for Robust Participatory Sensing
inferredcites →https://doi.org/10.1109/melcon.2016.7495468openalex-snapshot
Air pollution monitoring in lemesos using a wireless sensor network
inferredcites →https://doi.org/10.1109/sam.2016.7569735openalex-snapshot
Nonlinear mobile sensor calibration using informed semi-nonnegative matrix factorization with a Vandermonde factor
inferredcites →https://doi.org/10.1109/tmc.2008.58openalex-snapshot
Rendezvous Planning in Wireless Sensor Networks with Mobile Elements
inferredcites →https://doi.org/10.1109/wcnc.2018.8377051openalex-snapshot
Calibrating low-cost air quality sensors using multiple arrays of sensors
inferredcites →https://doi.org/10.1145/1236360.1236372openalex-snapshot
Blind calibration of sensor networks
inferredcites →https://doi.org/10.1145/1362542.1362546openalex-snapshot
Reputation-based framework for high integrity sensor networks
inferredcites →https://doi.org/10.1145/2185677.2185687openalex-snapshot
Collaborative calibration and sensor placement for mobile sensor networks
inferredcites →https://doi.org/10.1145/2541831.2541859openalex-snapshot
Enabling low-cost particulate matter measurement for participatory sensing scenarios
inferredcites →https://doi.org/10.1145/2668332.2668346openalex-snapshot
AirCloud
inferredcites →https://doi.org/10.1145/2737095.2737113openalex-snapshot
Reducing multi-hop calibration errors in large-scale mobile sensor networks
inferredcites →https://doi.org/10.1145/2858036.2858571openalex-snapshot
MyPart
inferredcites →https://doi.org/10.1145/3090084openalex-snapshot
SCAN
inferredcites →https://doi.org/10.1145/3143337.3143339openalex-snapshot
Issues of using wireless sensor network to monitor urban air quality
inferredcites →https://doi.org/10.1145/3191756openalex-snapshot
W-Air
inferredcites →https://doi.org/10.1371/journal.pone.0137789openalex-snapshot
Laboratory Evaluation of the Shinyei PPD42NS Low-Cost Particulate Matter Sensor
inferredcites →https://doi.org/10.3390/s100302088openalex-snapshot
Metal Oxide Gas Sensors: Sensitivity and Influencing Factors
inferredcites →https://doi.org/10.3390/s100605469openalex-snapshot
Metal Oxide Semi-Conductor Gas Sensors in Environmental Monitoring
inferredcites →https://doi.org/10.3390/s120709635openalex-snapshot
A Survey on Gas Sensing Technology
inferredcites →https://doi.org/10.3390/s151229859openalex-snapshot
A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems
inferredcites →https://doi.org/10.3390/s17071520openalex-snapshot
Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds
inferredcites →https://doi.org/10.3390/s17081916openalex-snapshot
Development and Evaluation of A Novel and Cost-Effective Approach for Low-Cost NO2 Sensor Drift Correction
inferredcites →https://doi.org/10.3390/s17102263openalex-snapshot
Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement—The Promise and the Current Reality
inferredcites →https://doi.org/10.3390/s18020059openalex-snapshot
Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring
inferredcites →https://doi.org/10.4103/2229-5186.79345openalex-snapshot
Methods for the determination of limit of detection and limit of quantitation of the analytical methods
inferredcites →https://doi.org/10.4108/eai.15-1-2018.153564openalex-snapshot
Privacy-Preserving Collaborative Blind Macro-Calibration of Environmental Sensors in Participatory Sensing
inferredcites →https://doi.org/10.4108/icst.mobiquitous.2014.257822openalex-snapshot
SBC: Scalable Smartphone Barometer Calibration through Crowdsourcing
inferredcites →https://doi.org/10.4236/wsn.2012.49032openalex-snapshot
Neighbor-Based Malicious Node Detection in Wireless Sensor Networks
inferredcites →https://doi.org/10.5194/amt-10-2383-2017openalex-snapshot
Evaluation and environmental correction of ambient CO 2 measurements from a low-cost NDIR sensor
inferredcites →https://doi.org/10.5194/amt-10-3575-2017openalex-snapshot
Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements
inferredcites →https://doi.org/10.5194/amt-10-3783-2017openalex-snapshot
Design of an ozone and nitrogen dioxide sensor unit and its long-term operation within a sensor network in the city of Zurich
inferredcites →https://doi.org/10.5194/amt-11-1937-2018openalex-snapshot
The BErkeley Atmospheric CO 2 Observation Network: field calibration and evaluation of low-cost air quality sensors
inferredcites →https://doi.org/10.5194/amt-11-291-2018openalex-snapshot
A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring
inferredcites →https://doi.org/10.5194/amt-11-315-2018openalex-snapshot
Calibration and assessment of electrochemical air quality sensors by co-location with regulatory-grade instruments
inferredcites →https://doi.org/10.5194/amt-5-1925-2012openalex-snapshot
Performance of a low-cost methane sensor for ambient concentration measurements in preliminary studies
inferredcites →https://doi.org/10.5194/amt-7-1121-2014openalex-snapshot
Field calibrations of a low-cost aerosol sensor at a regulatory monitoring site in California
inferredcites →https://doi.org/10.5194/amt-7-3325-2014openalex-snapshot
The next generation of low-cost personal air quality sensors for quantitative exposure monitoring
inferredcites →https://doi.org/10.5194/amt-9-5281-2016openalex-snapshot
Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States
inferredcites →https://doi.org/10.5555/2893711.2893734openalex-snapshot
Mitigating Slow Dynamics of Low-Cost Chemical Sensors for Mobile Air Quality Monitoring Sensor Networks
inferredcites →https://doi.org/10.5555/2893711.2893735openalex-snapshot
Pre-Deployment Testing, Augmentation and Calibration of Cross-Sensitive Sensors
inferredcites →https://doi.org/10.5555/3108009.3108011openalex-snapshot
Using Multi-parameters for Calibration of Low-cost Sensors in Urban Environment
inferredcites →https://doi.org/10.5860/choice.47-4447openalex-snapshot
Air pollution: measurement, modelling and mitigation

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4646331openalex-extracted
Electric Buses as an Air Pollution and Meteorological Observation Network
inferred← citeshttps://doi.org/10.1002/adem.202300007openalex-snapshot
Silicon Nanowires Driving Miniaturization of Microelectromechanical Systems Physical Sensors: A Review
inferred← citeshttps://doi.org/10.1002/ail2.76openalex-snapshot
Applying machine learning for large scale field calibration of low‐cost PM 2.5 and PM 10 air pollution sensors
inferred← citeshttps://doi.org/10.1002/met.2161openalex-snapshot
Low‐cost air quality monitoring networks for long‐term field campaigns: A review
inferred← citeshttps://doi.org/10.1002/qre.70004openalex-snapshot
Statistical Calibration of NO2${\rm NO}_2$ Low‐Cost Sensors
inferred← citeshttps://doi.org/10.1002/rob.22109openalex-snapshot
Gas source localization and mapping with mobile robots: A review
inferred← citeshttps://doi.org/10.1002/wer.70249openalex-snapshot
Smart Water Management: Role of IoT, AI, and Machine Learning in Water Quality Monitoring
inferred← citeshttps://doi.org/10.1007/978-3-030-28374-2_59openalex-snapshot
A Distributed Pollution Monitoring System: The Application of Blockchain to Air Quality Monitoring
inferred← citeshttps://doi.org/10.1007/978-3-030-40305-8_27openalex-snapshot
IoT Enabled Air Pollution Monitoring in Smart Cities
inferred← citeshttps://doi.org/10.1007/978-3-030-76063-2_40openalex-snapshot
Calibration of Low-Cost Particulate Matter Sensors with Elastic Weight Consolidation (EWC) as an Incremental Deep Learning Method
inferred← citeshttps://doi.org/10.1007/978-3-030-98423-6_4openalex-snapshot
Low-Cost Sensor Node for Air Quality Monitoring: Verification of NO2 Measurements Against a Commercial System
inferred← citeshttps://doi.org/10.1007/978-3-031-66635-3_11openalex-snapshot
Smart City Air Quality Monitoring: A Mobile Application for Intelligent Cities
inferred← citeshttps://doi.org/10.1007/978-981-15-5511-4_7openalex-snapshot
Air Quality Measuring Sensors
inferred← citeshttps://doi.org/10.1007/978-981-15-7527-3_60openalex-snapshot
An IoT-Based Air Quality Monitoring with Deep Learning Model System
inferred← citeshttps://doi.org/10.1007/978-981-15-9509-7_31openalex-snapshot
Design of a Water and Oxygen Generator from Atmospheric Pollutant Air Using Internet of Things
inferred← citeshttps://doi.org/10.1007/s10462-025-11277-9openalex-snapshot
Advancements in air quality monitoring: a systematic review of IoT-based air quality monitoring and AI technologies
inferred← citeshttps://doi.org/10.1007/s10618-021-00739-7openalex-snapshot
Detecting virtual concept drift of regressors without ground truth values
inferred← citeshttps://doi.org/10.1007/s10661-020-08781-6openalex-snapshot
Sensors for indoor air quality monitoring and assessment through Internet of Things: a systematic review
inferred← citeshttps://doi.org/10.1007/s10661-023-11756-yopenalex-snapshot
Air pollution forecasting based on wireless communications: review
inferred← citeshttps://doi.org/10.1007/s11270-021-05363-1openalex-snapshot
Missing Data Estimation in a Low-Cost Sensor Network for Measuring Air Quality: a Case Study in Aburrá Valley
inferred← citeshttps://doi.org/10.1007/s11356-020-11709-9openalex-snapshot
Low-cost sensor system for monitoring the oil mist concentration in a workshop
inferred← citeshttps://doi.org/10.1007/s11356-021-17384-8openalex-snapshot
Has the public habituated to the haze in China?
inferred← citeshttps://doi.org/10.1007/s11869-021-01067-xopenalex-snapshot
Recent advancements in low-cost portable sensors for urban and indoor air quality monitoring
inferred← citeshttps://doi.org/10.1007/s11869-025-01771-yopenalex-snapshot
Air pollution observation—bridging spaceborne to unmanned airborne remote sensing: a systematic review and meta-analysis
inferred← citeshttps://doi.org/10.1007/s12145-025-01927-5openalex-snapshot
Mapping trends and analyzing key themes in low-cost sensors for air quality monitoring
inferred← citeshttps://doi.org/10.1007/s12613-021-2378-zopenalex-snapshot
Application of low-cost particulate matter sensors for air quality monitoring and exposure assessment in underground mines: A review
inferred← citeshttps://doi.org/10.1007/s12647-022-00569-yopenalex-snapshot
SODAR Based Meteorological Sensor Network for Air Pollution Monitoring in Northern India
inferred← citeshttps://doi.org/10.1016/b978-0-323-95879-0.50259-9openalex-snapshot
Bayesian Neural Network-Based Calibration for Urban Air Quality Sensors
inferred← citeshttps://doi.org/10.1016/b978-0-323-99762-1.00046-2openalex-snapshot
Low-cost sensors for air quality monitoring
inferred← citeshttps://doi.org/10.1016/b978-0-443-26643-0.00030-3openalex-snapshot
Impact of external pollutants on indoor air quality
inferred← citeshttps://doi.org/10.1016/b978-0-443-36396-2.00001-9openalex-snapshot
Performance evaluation of low-cost SDS particulate sensor and standard devices for air quality and climate change monitoring with respect to LULC in Kolkata, West Bengal
inferred← citeshttps://doi.org/10.1016/j.apr.2023.101946openalex-snapshot
Spatial and temporal variability of urban cyclists’ exposure to PM2.5 in Medellín, Colombia
inferred← citeshttps://doi.org/10.1016/j.apr.2025.102556openalex-snapshot
Evaluation of urban PM2.5 concentrations over 73 major cities and their association with satellite Aerosol Optical Depth: A global analysis of ambient air pollution
inferred← citeshttps://doi.org/10.1016/j.apr.2025.102676openalex-snapshot
Field-based calibration and operation of low-cost sensors for particulate matter by linear and nonlinear methods
inferred← citeshttps://doi.org/10.1016/j.atmosenv.2019.116905openalex-snapshot
Field testing a low-cost passive aerosol sampler for long-term measurement of ambient PM2.5 concentrations and particle composition
inferred← citeshttps://doi.org/10.1016/j.atmosenv.2023.119756openalex-snapshot
A machine learning-based approach for fusing measurements from standard sites, low-cost sensors, and satellite retrievals: Application to NO2 pollution hotspot identification
inferred← citeshttps://doi.org/10.1016/j.atmosenv.2024.120841openalex-snapshot
Calibration of NO, SO2, and PM using Airify: A low-cost sensor cluster for air quality monitoring
inferred← citeshttps://doi.org/10.1016/j.buildenv.2022.108833openalex-snapshot
Predicting airborne pollutant concentrations and events in a commercial building using low-cost pollutant sensors and machine learning: A case study
inferred← citeshttps://doi.org/10.1016/j.buildenv.2022.109432openalex-snapshot
Design, fabrication, and calibration of the Building EnVironment and Occupancy (BEVO) Beacon: A rapidly-deployable and affordable indoor environmental quality monitor
inferred← citeshttps://doi.org/10.1016/j.buildenv.2023.109997openalex-snapshot
Information fusion of stationary, mobile, and wearable consumer-grade sensors to confidently estimate bedroom ventilation rates
inferred← citeshttps://doi.org/10.1016/j.buildenv.2024.112068openalex-snapshot
A UAV-based method for efficiently measuring the spatial pattern of multiple air pollutants in street canyons
inferred← citeshttps://doi.org/10.1016/j.carbon.2024.119207openalex-snapshot
Amplified sensing of nitrogen dioxide with a phosphate-doped reduced graphene oxide powder
inferred← citeshttps://doi.org/10.1016/j.compenvurbsys.2024.102073openalex-snapshot
Intelligent coverage and cost-effective monitoring: Bus-based mobile sensing for city air quality
inferred← citeshttps://doi.org/10.1016/j.dib.2025.111439openalex-snapshot
A dataset of particulate matters measurements from a network of mobile and fixed sensors and monitoring stations in Rouen (Northwestern France)
inferred← citeshttps://doi.org/10.1016/j.dib.2026.113025openalex-snapshot
Multi-source dataset of NO2 and PM from mobile and fixed sensors in Rouen (France)
inferred← citeshttps://doi.org/10.1016/j.ecoinf.2024.102568openalex-snapshot
HypeAIR: A novel framework for real-time low-cost sensor calibration for air quality monitoring in smart cities
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.107591openalex-snapshot
GAMMA: A universal model for calibrating sensory data of multiple low-cost air monitoring devices
inferred← citeshttps://doi.org/10.1016/j.enpol.2021.112571openalex-snapshot
Energy poverty influences urban outdoor air pollution levels during COVID-19 lockdown in south-central Chile
inferred← citeshttps://doi.org/10.1016/j.envint.2020.105965openalex-snapshot
Data fusion for air quality mapping using low-cost sensor observations: Feasibility and added-value
inferred← citeshttps://doi.org/10.1016/j.envint.2022.107329openalex-snapshot
Assessment of the impact of sensor error on the representativeness of population exposure to urban air pollutants
inferred← citeshttps://doi.org/10.1016/j.envpol.2025.126418openalex-snapshot
Low-cost sensors for atmospheric NO2 measurement: A review
inferred← citeshttps://doi.org/10.1016/j.envres.2025.122941openalex-snapshot
Using low-cost sensors and GPS to assess spatiotemporal variations in personal exposure to PM2.5 in the Washington State Twin Registry
inferred← citeshttps://doi.org/10.1016/j.ifacol.2020.12.223openalex-snapshot
From Sensor to Processing Networks: Optimal Estimation with Computation and Communication Latency
inferred← citeshttps://doi.org/10.1016/j.indic.2024.100424openalex-snapshot
Assessing risk of acute respiratory infectious diseases in crowded indoor settings with digital twin and precision trajectory approach
inferred← citeshttps://doi.org/10.1016/j.inffus.2026.104124openalex-snapshot
Data fusion for low-cost sensors: A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.ins.2023.119307openalex-snapshot
STCM: A spatio-temporal calibration model for low-cost air monitoring sensors
inferred← citeshttps://doi.org/10.1016/j.iot.2022.100628openalex-snapshot
Modeling indoor PM2.5 using Adaptive Dynamic Fuzzy Inference System Tree (ADFIST) on Internet of Things-based sensor network data
inferred← citeshttps://doi.org/10.1016/j.jaerosci.2021.105829openalex-snapshot
Long-term evaluation and calibration of three types of low-cost PM2.5 sensors at different air quality monitoring stations
inferred← citeshttps://doi.org/10.1016/j.jaerosci.2021.105872openalex-snapshot
Tutorial: Guidelines for implementing low-cost sensor networks for aerosol monitoring
inferred← citeshttps://doi.org/10.1016/j.jaerosci.2024.106335openalex-snapshot
Exploration of intra-city and inter-city PM2.5 regional calibration models to improve low-cost sensor performance
inferred← citeshttps://doi.org/10.1016/j.jenvman.2025.125100openalex-snapshot
A scalable framework for harmonizing, standardization, and correcting crowd-sourced low-cost sensor PM2.5 data across Europe
inferred← citeshttps://doi.org/10.1016/j.jes.2023.05.044openalex-snapshot
Evaluating the performance and influencing factors of three portable black carbon monitors for field measurement
inferred← citeshttps://doi.org/10.1016/j.jii.2019.100123openalex-snapshot
Low cost air pollution monitoring systems: A review of protocols and enabling technologies
inferred← citeshttps://doi.org/10.1016/j.jnca.2022.103434openalex-snapshot
Data reconstruction applications for IoT air pollution sensor networks using graph signal processing
inferred← citeshttps://doi.org/10.1016/j.meadig.2026.100025openalex-snapshot
A Laplace-domain method for in situ temperature calibration in sensor networks
inferred← citeshttps://doi.org/10.1016/j.measurement.2026.121033openalex-snapshot
A hybrid machine learning and Extended Kalman filtering framework for sensor fusion of low-cost and high-precision dissolved oxygen sensors under environmental variability
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2022.158872openalex-snapshot
High-density volatile organic compound monitoring network for identifying pollution sources
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2023.162336openalex-snapshot
A Nested Machine Learning Approach to Short-Term Pm2.5 Prediction in Metropolitan Areas Using Pm2.5 Data from Different Sensor Networks
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2024.170593openalex-snapshot
Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2024.171522openalex-snapshot
RPCA-based techniques for pattern extraction, hotspot identification and signal correction using data from a dense network of low-cost NO2 sensors in London
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2024.175327openalex-snapshot
Electric buses as an air pollution and meteorological observation network: Methodology and preliminary results
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2025.179364openalex-snapshot
Calibration and validation-based assessment of low-cost air quality sensors
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2025.179717openalex-snapshot
Nowcasting street-level NO2 concentrations using Gaussian processes
inferred← citeshttps://doi.org/10.1016/j.scs.2020.102076openalex-snapshot
Evaluation of low-cost sensors for quantitative personal exposure monitoring
inferred← citeshttps://doi.org/10.1016/j.snb.2019.127428openalex-snapshot
An Improved Sensor Calibration with Anomaly Detection and Removal
inferred← citeshttps://doi.org/10.1016/j.snb.2021.130958openalex-snapshot
From air quality sensors to sensor networks: Things we need to learn
inferred← citeshttps://doi.org/10.1016/j.snb.2022.132417openalex-snapshot
RF sputtered CuO anchored SnO2 for H2S gas sensor
inferred← citeshttps://doi.org/10.1016/j.snb.2025.138424openalex-snapshot
Bionic enriched olfactory system with preconcentration-enhanced sensing and hierarchical regression analysis strategy for ultra-sensitive detection of soil petroleum hydrocarbon contamination
inferred← citeshttps://doi.org/10.1016/j.suscom.2020.100409openalex-snapshot
Scheduling recurring and dependent tasks in EH-WSNs
inferred← citeshttps://doi.org/10.1016/j.uclim.2023.101684openalex-snapshot
Hyperlocal air pollution in an urban environment - measured with low-cost sensors
inferred← citeshttps://doi.org/10.1021/acs.est.3c03661openalex-snapshot
Low-Cost Particulate Matter Sensors for Monitoring Residential Wood Burning
inferred← citeshttps://doi.org/10.1029/2023gh000935openalex-snapshot
Identification of Neighborhood Hotspots via the Cumulative Hazard Index: Results From a Community‐Partnered Low‐Cost Sensor Deployment
inferred← citeshttps://doi.org/10.1038/s41597-024-03767-2openalex-snapshot
QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
inferred← citeshttps://doi.org/10.1038/s41598-022-18700-zopenalex-snapshot
Design and development of an open-source framework for citizen-centric environmental monitoring and data analysis
inferred← citeshttps://doi.org/10.1038/s41612-025-01145-2openalex-snapshot
Dynamic calibration of low-cost PM2.5 sensors using trust-based consensus mechanisms
inferred← citeshttps://doi.org/10.1049/ell2.12816openalex-snapshot
An open‐source tool for evaluating calibration techniques used in low‐cost air pollutant monitors
inferred← citeshttps://doi.org/10.1049/wss2.12043openalex-snapshot
Evaluation and calibration of low‐cost off‐the‐shelf particulate matter sensors using machine learning techniques
inferred← citeshttps://doi.org/10.1080/00207233.2019.1696595openalex-snapshot
Experimental analysis of a corona-charged baghouse filter
inferred← citeshttps://doi.org/10.1080/12269328.2022.2120094openalex-snapshot
A strategy for ammonia odor monitoring, prediction, and reduction from livestock manure wastes in Korea: a short review
inferred← citeshttps://doi.org/10.1088/1748-9326/ada397openalex-snapshot
Spatiotemporal air quality prediction using stochastic advection–diffusion model for multimodal data fusion
inferred← citeshttps://doi.org/10.1088/1748-9326/ae2b89openalex-snapshot
Optimal sensor placement in low-cost PM 2.5 sensor networks using value of information and multimodal data fusion
inferred← citeshttps://doi.org/10.1088/1755-1315/1544/1/012011openalex-snapshot
Monitoring and Improving Air Quality in the Zhytomyr Community through Strategic Environmental Tools
inferred← citeshttps://doi.org/10.1088/1755-1315/266/1/012017openalex-snapshot
Air pollution monitoring network using low-cost sensors, a case study in Hanoi, Vietnam
inferred← citeshttps://doi.org/10.1109/access.2020.2980736openalex-snapshot
Design and Evaluation of a Reliable Low-Cost Atmospheric Pollution Station in Urban Environment
inferred← citeshttps://doi.org/10.1109/access.2020.3038954openalex-snapshot
Minimizing Age of Information in Energy Harvesting Wireless Sensor Networks
inferred← citeshttps://doi.org/10.1109/access.2022.3145945openalex-snapshot
Stochastic Online Calibration of Low-Cost Gas Sensor Networks With Mobile References
inferred← citeshttps://doi.org/10.1109/access.2022.3164506openalex-snapshot
Enhanced Air Quality Inference via Multi-View Learning With Mobile Sensing Memory
inferred← citeshttps://doi.org/10.1109/access.2022.3174853openalex-snapshot
Deep-AIR: A Hybrid CNN-LSTM Framework for Fine-Grained Air Pollution Estimation and Forecast in Metropolitan Cities
inferred← citeshttps://doi.org/10.1109/access.2024.3410171openalex-snapshot
UNI-CAL: A Universal AI-Driven Model for Air Pollutant Sensor Calibration With Domain-Specific Knowledge Inputs
inferred← citeshttps://doi.org/10.1109/aim65483.2026.11658010openalex-snapshot
Kernel-Adaptive TinyRBF Networks for On-Device Calibration of Soil Moisture Sensors
inferred← citeshttps://doi.org/10.1109/ccai50917.2021.9447517openalex-snapshot
Frequency Analysis of Particulate Matter in Urban Environments under Low-cost Sensors
inferred← citeshttps://doi.org/10.1109/cce60043.2023.10332832openalex-snapshot
Automated Stress Level Detection for Hospital Nurses: A Single Triaxial Wearable Accelerometer Sensor System Approach
inferred← citeshttps://doi.org/10.1109/coins51742.2021.9524276openalex-snapshot
Blind Calibration of Air Quality Wireless Sensor Networks Using Deep Neural Networks
inferred← citeshttps://doi.org/10.1109/compe49325.2020.9200053openalex-snapshot
Air Quality Monitoring Systems using IoT: A Review
inferred← citeshttps://doi.org/10.1109/dasa54658.2022.9765098openalex-snapshot
IoT Driven Solution for Indoor Air Quality Monitoring System to Develop a Smart Healthcare Environment: A Review Based Study
inferred← citeshttps://doi.org/10.1109/dts52014.2021.9498110openalex-snapshot
Combining of TD-GC-MS and home developed electronic nose for road traffic air monitoring
inferred← citeshttps://doi.org/10.1109/ehb64556.2024.10805630openalex-snapshot
Healing IoT Data for Indoor Air Quality Using Artificial Intelligence
inferred← citeshttps://doi.org/10.1109/electronica.2019.8825595openalex-snapshot
Smart Multisensor Node for Environmental Parameters Monitoring in Urban Areas
inferred← citeshttps://doi.org/10.1109/ic3s57698.2023.10169664openalex-snapshot
Towards smart helmet for motorcyclists: automatic stress level detection using wearable accelerometer sensor system
inferred← citeshttps://doi.org/10.1109/icaccess61735.2024.10499527openalex-snapshot
Classifying Daily Life Smoking Events: An Innovative Wearable Hand-Band Solution
inferred← citeshttps://doi.org/10.1109/icassp39728.2021.9414742openalex-snapshot
In Situ Calibration of Cross-Sensitive Sensors in Mobile Sensor Arrays Using Fast Informed Non-Negative Matrix Factorization
inferred← citeshttps://doi.org/10.1109/icassp49660.2025.10888054openalex-snapshot
Enhancing Network Calibration for Low-Cost Gas Sensor Networks Through Adaptive Similarity Search
inferred← citeshttps://doi.org/10.1109/icat54566.2022.9811215openalex-snapshot
Development of Correction Models for Three-Electrode NO2 Electrochemical Sensor
inferred← citeshttps://doi.org/10.1109/iccad52417.2021.9638737openalex-snapshot
Calibration Transfer to Address the Long Term Drift of Gas Sensors for in Field NO2 Monitoring
inferred← citeshttps://doi.org/10.1109/icccs55188.2022.10079635openalex-snapshot
Internet of Things: A Survey on Air Pollution Monitoring, Challenges and Applications
inferred← citeshttps://doi.org/10.1109/iccmc51019.2021.9418342openalex-snapshot
Data Analytics based Statistical Analysis of Air Pollution in the Major Cities of Karnataka
inferred← citeshttps://doi.org/10.1109/icii.2019.00069openalex-snapshot
Distributed Machine Learning for Internet-of-Things in Smart Cities
inferred← citeshttps://doi.org/10.1109/icimcis63449.2024.10957284openalex-snapshot
Preprocessing and Framework for Edge Intelligence in Air Quality Control: Work on Progress
inferred← citeshttps://doi.org/10.1109/icirca48905.2020.9183251openalex-snapshot
Real Time Analysis of Air Pollution Prediction using IoT
inferred← citeshttps://doi.org/10.1109/icpeev58650.2023.10391904openalex-snapshot
Smart Environment Monitoring System and its impact on health
inferred← citeshttps://doi.org/10.1109/icset53708.2021.9612560openalex-snapshot
Smart Air Filtration System Using IoT and Kalman Filter Algorithm for Indoor Air Quality and Plant Monitoring
inferred← citeshttps://doi.org/10.1109/icssas57918.2023.10331645openalex-snapshot
Comparative Analysis of Meteorological variables for Air Pollution Detection in Various Cities using ZigBee
inferred← citeshttps://doi.org/10.1109/icwt58823.2023.10335205openalex-snapshot
Performance Analysis Antares Long Range Technology with Mobile Application Visualization
inferred← citeshttps://doi.org/10.1109/ieeeconf58110.2023.10520457openalex-snapshot
Detection of Broiler Behaviors Through a Wearable Sensor System and Machine Learning Methods
inferred← citeshttps://doi.org/10.1109/iemcon51383.2020.9284914openalex-snapshot
Odour Detection System for Allergy Sufferers
inferred← citeshttps://doi.org/10.1109/ies55876.2022.9888466openalex-snapshot
Air Purification System for Air Quality Monitoring In-Vehicle
inferred← citeshttps://doi.org/10.1109/imcom51814.2021.9377350openalex-snapshot
On Modeling Air Pollution Detection With Internet of Vehicles
inferred← citeshttps://doi.org/10.1109/incit66780.2025.11276042openalex-snapshot
Design and Deployment of a Sensor Box for Altitude-Based Air Quality Monitoring
inferred← citeshttps://doi.org/10.1109/intercon63140.2024.10833487openalex-snapshot
Enhanced Calibration Techniques for Low-Cost Particulate Matter Monitors
inferred← citeshttps://doi.org/10.1109/iot69654.2025.11297590openalex-snapshot
Design a Mobile PM2.5 Sensor Device and Calibration Using Machine Learning Models
inferred← citeshttps://doi.org/10.1109/iotdi49375.2020.00010openalex-snapshot
MapTransfer : Urban Air Quality Map Generation for Downscaled Sensor Deployments
inferred← citeshttps://doi.org/10.1109/iotm.001.2300112openalex-snapshot
A Data-Driven Framework for Air Quality Sensor Networks
inferred← citeshttps://doi.org/10.1109/ipsn48710.2020.00-12openalex-snapshot
Poster Abstract: Robust Calibration for Low-Cost Air Quality Sensors using Historical Data
inferred← citeshttps://doi.org/10.1109/ipsn54338.2022.00010openalex-snapshot
Eclipse: An End-to-End Platform for Low-Cost, Hyperlocal Environmental Sensing in Cities
inferred← citeshttps://doi.org/10.1109/isc255366.2022.9921782openalex-snapshot
Towards a Digital Twin for Air Quality Monitoring Networks in Smart Cities
inferred← citeshttps://doi.org/10.1109/isc260477.2024.11004140openalex-snapshot
Low-Cost Smart Sensing Pipeline: Assembly, Calibration, and Interpretation of Air Quality Data
inferred← citeshttps://doi.org/10.1109/iscas51556.2021.9401413openalex-snapshot
ML-Based Humidity and Temperature Calibration System for Heterogeneous MOx Sensor Array in ppm-Level BTEX Monitoring
inferred← citeshttps://doi.org/10.1109/jiot.2019.2894196openalex-snapshot
2018 IndexIEEE Internet of Things JournalVol. 5
inferred← citeshttps://doi.org/10.1109/jiot.2019.2929594openalex-snapshot
A Comparative Study of Calibration Methods for Low-Cost Ozone Sensors in IoT Platforms
inferred← citeshttps://doi.org/10.1109/jiot.2020.2965283openalex-snapshot
Multisensor Data Fusion Calibration in IoT Air Pollution Platforms
inferred← citeshttps://doi.org/10.1109/jiot.2020.2971237openalex-snapshot
Nonlinear Polynomial Graph Filter for Anomalous IoT Sensor Detection and Localization
inferred← citeshttps://doi.org/10.1109/jiot.2021.3067717openalex-snapshot
Graph Learning Techniques Using Structured Data for IoT Air Pollution Monitoring Platforms
inferred← citeshttps://doi.org/10.1109/jiot.2022.3144934openalex-snapshot
On Data-Driven Self-Calibration for IoT-Based Gas Concentration Monitoring Systems
inferred← citeshttps://doi.org/10.1109/jiot.2022.3150849openalex-snapshot
MAIC: Metalearning-Based Adaptive In-Field Calibration for IoT Air Quality Monitoring System
inferred← citeshttps://doi.org/10.1109/jiot.2022.3177948openalex-snapshot
SensorFormer: Efficient Many-to-Many Sensor Calibration With Learnable Input Subsampling
inferred← citeshttps://doi.org/10.1109/jiot.2022.3196154openalex-snapshot
Graph Signal Reconstruction Techniques for IoT Air Pollution Monitoring Platforms
inferred← citeshttps://doi.org/10.1109/jiot.2023.3290508openalex-snapshot
Unmanned Aerial Vehicles for Air Pollution Monitoring: A Survey
inferred← citeshttps://doi.org/10.1109/jiot.2024.3405623openalex-snapshot
Improving Data Quality of Low-Cost Light-Scattering PM Sensors: Toward Automatic Air Quality Monitoring in Urban Environments
inferred← citeshttps://doi.org/10.1109/jsas.2026.3707543openalex-snapshot
Next-Generation Multipollutant Air Quality Monitoring System
inferred← citeshttps://doi.org/10.1109/jsen.2019.2910317openalex-snapshot
In Situ Calibration Algorithms for Environmental Sensor Networks: A Review
inferred← citeshttps://doi.org/10.1109/jsen.2021.3105442openalex-snapshot
Missing Data Imputation on IoT Sensor Networks: Implications for on-Site Sensor Calibration
inferred← citeshttps://doi.org/10.1109/jsen.2022.3212009openalex-snapshot
A Variational Bayesian Blind Calibration Approach for Air Quality Sensor Deployments
inferred← citeshttps://doi.org/10.1109/jsen.2023.3238900openalex-snapshot
Uncertainty-Based Calibration Method for Environmental Sensors—Application to Chlorine and pH Monitoring With Carbon Nanotube Sensor Array
inferred← citeshttps://doi.org/10.1109/jsen.2023.3277493openalex-snapshot
SNRepair: Systematically Addressing Sensor Faults and Self-Calibration in IoT Networks
inferred← citeshttps://doi.org/10.1109/jsen.2023.3305779openalex-snapshot
Drive-by Air Pollution Sensing Systems: Challenges and Future Directions
inferred← citeshttps://doi.org/10.1109/jsen.2023.3339202openalex-snapshot
Minimized Training of Machine Learning-Based Calibration Methods for Low-Cost O3 Sensors
inferred← citeshttps://doi.org/10.1109/jsen.2024.3362962openalex-snapshot
Sens-BERT: A BERT-Based Approach for Enabling Transferability and Re-Calibration of Calibration Models for Low-Cost Sensors Under Reference Measurements Scarcity
inferred← citeshttps://doi.org/10.1109/jsen.2024.3518093openalex-snapshot
Mobile Calibration for Bus-Based Urban Sensing
inferred← citeshttps://doi.org/10.1109/jsen.2025.3635300openalex-snapshot
HMTC: A Hybrid Mamba-Transformer Model for Calibration of Low-Cost Air Quality Sensors
inferred← citeshttps://doi.org/10.1109/jsyst.2023.3238357openalex-snapshot
Intelligent Wireless Sensor Network for Gas Classification Using Machine Learning
inferred← citeshttps://doi.org/10.1109/lats65346.2025.10963944openalex-snapshot
IoT and Edge Computing: Applications and Reliability Implications
inferred← citeshttps://doi.org/10.1109/mcom.2018.1701065openalex-snapshot
A City-Wide Real-Time Traffic Management System: Enabling Crowdsensing in Social Internet of Vehicles
inferred← citeshttps://doi.org/10.1109/piers-spring46901.2019.9017440openalex-snapshot
An Air Quality Monitoring System with Enhanced Coverage Capabilities by Using the Modulated Scattering Technique (MST)
inferred← citeshttps://doi.org/10.1109/sas48726.2020.9220079openalex-snapshot
IoT Enabled Low Cost Air Quality Sensor
inferred← citeshttps://doi.org/10.1109/sbesc60926.2023.10324138openalex-snapshot
Development of an air quality station using low-cost sensors
inferred← citeshttps://doi.org/10.1109/sbesc60926.2023.10324290openalex-snapshot
Calibration of a metal oxide sensor for ammonia detection targeting IoT solutions
inferred← citeshttps://doi.org/10.1109/secon52354.2021.9491586openalex-snapshot
Compensating Altered Sensitivity of Duty-Cycled MOX Gas Sensors with Machine Learning
inferred← citeshttps://doi.org/10.1109/sennano57767.2023.10352518openalex-snapshot
Validation of EEATC a Novel Calibration Approach for Low-cost Sensors in Different Tandem Configurations
inferred← citeshttps://doi.org/10.1109/sensors47087.2021.9639703openalex-snapshot
Design and Implementation of A Mobile Urban Low-Cost Environmental Sensor Network
inferred← citeshttps://doi.org/10.1109/sensors60989.2024.10784897openalex-snapshot
Environmental Variation or Instrumental Drift? A Probabilistic Approach to Gas Sensor Drift Modeling and Evaluation
inferred← citeshttps://doi.org/10.1109/smartworld-uic-atc-scalcom-iop-sci.2019.00143openalex-snapshot
Enhancing Multi-hop Sensor Calibration with Uncertainty Estimates
inferred← citeshttps://doi.org/10.1109/smc54092.2024.10831622openalex-snapshot
Calibrating Low-cost Environmental Sensors Using Optimised Artificial Neural Networks
inferred← citeshttps://doi.org/10.1109/tase.2022.3182289openalex-snapshot
Rendez-Vous Based Drift Diagnosis Algorithm for Sensor Networks Toward In Situ Calibration
inferred← citeshttps://doi.org/10.1109/tcomm.2021.3092038openalex-snapshot
Improving Multi-Hop Time Synchronization Performance in Wireless Sensor Networks Based on Packet-Relaying Gateways With Per-Hop Delay Compensation
inferred← citeshttps://doi.org/10.1109/telfor48224.2019.8971056openalex-snapshot
Variance Analysis of Signals from Four Electrode Electrochemical Sensors
inferred← citeshttps://doi.org/10.1109/tii.2022.3151782openalex-snapshot
Intelligent Air Pollution Sensors Calibration for Extreme Events and Drifts Monitoring
inferred← citeshttps://doi.org/10.1109/tii.2022.3215960openalex-snapshot
Time-Adaptive Expectation Maximization Learning Framework for HMM Based Data-Driven Gas Sensor Calibration
inferred← citeshttps://doi.org/10.1109/tim.2020.2978596openalex-snapshot
A Deep Calibration Method for Low-Cost Air Monitoring Sensors With Multilevel Sequence Modeling
inferred← citeshttps://doi.org/10.1109/tim.2020.3034109openalex-snapshot
Low Cost Sensor With IoT LoRaWAN Connectivity and Machine Learning-Based Calibration for Air Pollution Monitoring
inferred← citeshttps://doi.org/10.1109/tim.2020.3034987openalex-snapshot
Participatory Air Quality and Urban Heat Islands Monitoring System
inferred← citeshttps://doi.org/10.1109/tim.2022.3198747openalex-snapshot
Efficient and Automated Generation of Orthogonal Atmospheres for the Characterization of Low-Cost Gas Sensor Systems in Air Quality Monitoring
inferred← citeshttps://doi.org/10.1109/tim.2023.3239626openalex-snapshot
Temporal Pattern-Based Denoising and Calibration for Low-Cost Sensors in IoT Monitoring Platforms
inferred← citeshttps://doi.org/10.1109/tim.2024.3461788openalex-snapshot
Convex Relaxation Method for Sensor Placement in Multiclass Monitoring Networks
inferred← citeshttps://doi.org/10.1109/tmc.2025.3560120openalex-snapshot
CatUA: Catalyzing Urban Air Quality Intelligence Through Mobile Crowd-Sensing
inferred← citeshttps://doi.org/10.1109/tnse.2020.3008337openalex-snapshot
Computation-Communication Trade-Offs and Sensor Selection in Real-Time Estimation for Processing Networks
inferred← citeshttps://doi.org/10.1109/tqcebt67648.2026.11681151openalex-snapshot
An AI-Driven Framework for Energy-Efficient Environmental Monitoring in Smart Cities Using Edge Intelligence
inferred← citeshttps://doi.org/10.1109/tsp.2020.3014610openalex-snapshot
Asymptotically Optimal Blind Calibration of Uniform Linear Sensor Arrays for Narrowband Gaussian Signals
inferred← citeshttps://doi.org/10.1145/3314393openalex-snapshot
ICT
inferred← citeshttps://doi.org/10.1145/3368235.3368848openalex-snapshot
A Framework of Automation on Context-Aware Internet of Things (IoT) Systems
inferred← citeshttps://doi.org/10.1145/3410530.3414322openalex-snapshot
RCH
inferred← citeshttps://doi.org/10.1145/3446005openalex-snapshot
Low-Cost Outdoor Air Quality Monitoring and Sensor Calibration
inferred← citeshttps://doi.org/10.1145/3460418.3480402openalex-snapshot
Blind Calibration by Maximizing Correlation
inferred← citeshttps://doi.org/10.1145/3464943openalex-snapshot
Robust Environmental Sensing Using UAVs
inferred← citeshttps://doi.org/10.1145/3486611.3486658openalex-snapshot
PIRMedic
inferred← citeshttps://doi.org/10.1145/3494322.3494354openalex-snapshot
AQ-SCIENCE: Air Quality - Smart Cities with IoT-ENabled Citizen Engagement Approach
inferred← citeshttps://doi.org/10.1145/3512889openalex-snapshot
Evaluation of Low-cost Air Quality Sensor Calibration Models
inferred← citeshttps://doi.org/10.1145/3538393.3544934openalex-snapshot
On the prediction of air quality within vehicles using outdoor air pollution
inferred← citeshttps://doi.org/10.1145/3643832.3661872openalex-snapshot
MobiAir: Unleashing Sensor Mobility for City-scale and Fine-grained Air-Quality Monitoring with AirBERT
inferred← citeshttps://doi.org/10.1145/3715014.3722087openalex-snapshot
Eclipse Dataset: Advancing Urban Sensing Research with Hyperlocal Environmental Data from Chicago
inferred← citeshttps://doi.org/10.1145/3737877openalex-snapshot
Physics-Based Fault Analysis for Commodity PIR Sensors*
showing the first 200 of 314
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.