Monitoring Indoor Air Quality by using IoT Technology

Esquiagola, J.; Manini, M.; Aikawa, Arthur Sequeira; Yoshioka, Leopoldo Rideki; Zuffo, Marcelo Knörich

doi:10.1109/intercon.2018.8526380

Cited by 28 publications

(12 citation statements)

References 8 publications

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“…Once the session is completed, data can be retrieved via email from the AirCasting website for analysis. AirBeam2 is considered an IoT device that wirelessly transfers data to a network [ 29 ]. However, AirCasting provides an open-source code for the AirBeam2 so that users can change the calibration equation for the PMS 7003 if needed.…”

Section: Methodsmentioning

confidence: 99%

Laboratory Evaluation of Low-Cost Optical Particle Counters for Environmental and Occupational Exposures

Sousan

Regmi

Park

2021

Sensors

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Low-cost optical particle counters effectively measure particulate matter (PM) mass concentrations once calibrated. Sensor calibration can be established by deriving a linear regression model by performing side-by-side measurements with a reference instrument. However, calibration differences between environmental and occupational settings have not been demonstrated. This study evaluated four commercially available, low-cost PM sensors (OPC-N3, SPS30, AirBeam2, and PMS A003) in both settings. The mass concentrations of three aerosols (salt, Arizona road dust, and Poly-alpha-olefin-4 oil) were measured and compared with a reference instrument. OPC-N3 and SPS30 were highly correlated (r = 0.99) with the reference instrument for all aerosol types in environmental settings. In occupational settings, SPS30, AirBeam2, and PMS A003 exhibited high correlation (>0.96), but the OPC-N3 correlation varied (r = 0.88–1.00). Response significantly (p < 0.001) varied between environmental and occupational settings for most particle sizes and aerosol types. Biases varied by particle size and aerosol type. SPS30 and OPC-N3 exhibited low bias for environmental settings, but all of the sensors showed a high bias for occupational settings. For intra-instrumental precision, SPS30 exhibited high precision for salt for both settings compared to the other low-cost sensors and aerosol types. These findings suggest that SPS30 and OPC-N3 can provide a reasonable estimate of PM mass concentrations if calibrated differently for environmental and occupational settings using site-specific calibration factors.

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Section: Methodsmentioning

confidence: 99%

Laboratory Evaluation of Low-Cost Optical Particle Counters for Environmental and Occupational Exposures

Sousan

Regmi

Park

2021

Sensors

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“…Two [ 26 , 27 ] were excluded following EC4 as they were review papers or theoretical analysis (EC3, EC4). Furthermore, 20 studies [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 ] were removed due to missing information about the design methodology and the type of sensors used for measuring IAQ parameters (IC4, EC3). In addition, five more studies [ 48 , 49 , 50 , 51 , 52 ] were excluded as they were focused on thermal comfort parameters only or had no relevant details about IAQ sensors (IC2, IC3, EC3).…”

Section: Methodsmentioning

confidence: 99%

Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

Saini

Dutta

Marques

2020

IJERPH

129

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Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015–2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO2, and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency.

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“…Berikutnya ada [5], hasilnya adalah Peningkatan Tvoc dan Eco2 terjadi antara jam12 siang yang merupakan waktu orang kantor untuk pergi makan siang sehingga pergerakan manusia menjadi generator alami VOC ini mungkin yang meningkatkan partikulat debu baik dari pergerakan orang dalam kantor ataupun perpindahan barang dalam ruangan sehingga debu terevaporasi kemana-mana.…”

Section: Penelitian Terkaitunclassified

Rancang Bangun Sistem Pemantauan Dan Pengendali Kualitas Udara Diruang MI (Manual Insert) PT. Smart Meter

Zagita¹

2021

JTE

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Polusi udara adalah zat fisik, kimia, maupun biologi yang dapat membahayakan kesehatan dan dapat menimbulkan penyakit pada makhluk hidup, udara merupakan salah satu unsur pokok bagi makhluk hidup. Sistem monitoring pada penelitian ini mengacu pada data yang didapatkan dari tiga kombinasi sensor, sensor Air quality sensor untuk mengukur kadar kualitas udara, sensor MQ-7 sebagai pengukur gas karbon monoksida(CO), sensor MQ-135 sebagai pengukur gas karbon Dioksida (CO2). Membuat alat yang dapat mengukur kualitas udara dengan akurasi yang baik, Memperbaiki sirkulasi udara dalam ruangan dan menjaga kualitas-nya, masuk dalam ambang batas standar ISPU atau WHO serta Mengurangi kadar udara berbahaya yang secara langsung dapat merugikan kesehtan. Hasil dari penelitian ini menunjukan bahwa sistem yang dibuat mampu mendeteksi kualitas udara dan kadar gas dengan kecepatan respon 0,5 detik saat sistem dilakukan uji coba pada ruang MI (dalam ruangan, ber-AC) dengan suhu ruangan 27ºC, kelembaban 63% rata-rata Kadar kualitas udara didalam ruang MI saat dilakukan pengujian yaitu 29,7 ppm. Sedangkan untuk kadar gas CO2 adalah 10.90 ppm dan untuk kadar gas CO rata-rata 1.48 ppm.

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Monitoring Indoor Air Quality by using IoT Technology

Cited by 28 publications

References 8 publications

Laboratory Evaluation of Low-Cost Optical Particle Counters for Environmental and Occupational Exposures

Laboratory Evaluation of Low-Cost Optical Particle Counters for Environmental and Occupational Exposures

Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

Rancang Bangun Sistem Pemantauan Dan Pengendali Kualitas Udara Diruang MI (Manual Insert) PT. Smart Meter

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