Improving Data Quality of Low-cost IoT Sensors in Environmental Monitoring Networks Using Data Fusion and Machine Learning Approach

Talavera, 2017, Review of IoT applications in agro-industrial and environmental fields, Comput. Electron. Agric., 142, 283, 10.1016/j.compag.2017.09.015 Bublitz, 2019, Disruptive technologies for environment and health research: An overview of artificial intelligence, blockchain, and Internet of Things, Int. J. Environ. Res. Public Health, 16, 3847, 10.3390/ijerph16203847 Gao, 2015, A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi’an, China, Environ. Pollut., 199, 56, 10.1016/j.envpol.2015.01.013 Okafor, 2019, Considerations for system design in IoT-based autonomous ecological sensing, Procedia Comput. Sci., 155, 258, 10.1016/j.procs.2019.08.037 Mao, 2019, Low-cost environmental sensor networks: Recent advances and future directions, Front. Earth Sci., 7, 10.3389/feart.2019.00221 Rai, 2017, End-user perspective of low-cost sensors for outdoor air pollution monitoring, Sci. Total Environ., 607–608, 691, 10.1016/j.scitotenv.2017.06.266 Williams, 2019 Borrego, 2016, Assessment of air quality microsensors versus reference methods:The EuroNetAir joint exercise, Atmos. Environ., 147, 246, 10.1016/j.atmosenv.2016.09.050 Hagan, 2018, Calibration and assessment of electrochemical air quality sensors by co-location with regulatory-grade instruments, Atmos. Meas. Tech., 11, 315, 10.5194/amt-11-315-2018 Sun, 2017, Development and evaluation of a novel and cost-effective approach for low-cost NO2 sensor drift correction, Sensors, 17, 1916, 10.3390/s17081916 Delaine, 2019, In situ Calibration algorithms for environmental sensor networks: A review, IEEE Sens. J., 19, 5968, 10.1109/JSEN.2019.2910317 Syafrudin, 2018, Performance analysis of IoT-based sensor, big data processing, and machine learning model for real-time monitoring system in automotive manufacturing, Sensors, 18, 2946, 10.3390/s18092946 Manes, 2016, Realtime gas emission monitoring at hazardous sites using a distributed point-source sensing infrastructure, Sensors, 16, 121, 10.3390/s16010121 Pandey, 2007, The relative performance of NDIR-based sensors in the near real-time analysis of CO2 in air, Sensors, 7, 1683, 10.3390/s7091683 Jiao, 2016, Community Air Sensor Network (CAIRSENSE) project: evaluation of low-costsensor performance in a suburban environment in the southeastern unitedstates, Atmos. Meas. Tech., 9, 5281, 10.5194/amt-9-5281-2016 Badura, 2019, Regression methods in the calibration of low-cost sensors for ambient particulate matter measurements, SN Appl. Sci., 1, 10.1007/s42452-019-0630-1 Munir, 2019, Analysing the performance of low-cost air quality sensors, their drivers, relative benefits and calibration in cities—a case study in Sheffield, Environ. Monit. Assess., 191, 10.1007/s10661-019-7231-8 Yamamoto, 2017, Machine learning-based Calibration of low-cost air temperature sensors using environmental data, Sensors, 17, 1290, 10.3390/s17061290 Zimmerman, 2018, A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring, Atmos. Meas. Tech., 11, 291, 10.5194/amt-11-291-2018 Spinelle, 2014, Calibration of a cluster of low-cost sensors for the measurement of air pollution in ambient air, Sensors, 21 Maag, 2016, 169 Schneider, 2017, Mapping urban air quality in near real-time using observations from low-cost sensors and model information, Environ. Int., 106, 234, 10.1016/j.envint.2017.05.005 X. Fang, I. Bate, Using multi-parameters for calibration of low-cost sensors in urban environment, in: Proceedings of the International Conference on Embedded Wireless Systems and Networks, 2017, pp. 1–11. Spinelle, 2015, Field calibration of a cluster of low-cost available: sensors for air quality monitoring Part A: Ozone and nitrogen dioxide, Sensors Actuators B, 215, 249, 10.1016/j.snb.2015.03.031 2020 Duvall, 2016, Performance evaluation and community application of low-cost sensors for ozone and nitrogen dioxide, Sensors, 16, 1698, 10.3390/s16101698 2020 Williams, 2014 2020 Hope, 2017 Spinelle, 2013