Abstract
The efficient monitoring of volatile organic compounds (VOCs) has become an essential priority in fields such as environmental protection, occupational health, and industrial safety due to their significant impact on air quality and human well-being. This article provides an in-depth review of recent advancements in portable monitoring systems that incorporate smart sensor technologies for VOC detection. Progress in sensor miniaturization, advanced signal-processing algorithms, and low-power electronic design has enabled the development of compact devices capable of real-time measurement with high levels of sensitivity and chemical selectivity. Furthermore, the integration of these systems into Internet of Things architectures has expanded their functionality, allowing for continuous data transmission, remote device management, and the application of predictive analytics through Big Data platforms. These capabilities not only enhance early detection of hazardous exposure but also support large-scale environmental surveillance and industrial process optimization. Despite these technological advances, several challenges persist. Issues related to long-term sensor calibration, environmental interferences, data reliability, and energy efficiency continue to limit widespread adoption. Additionally, ensuring interoperability among different communication protocols and maintaining cybersecurity standards remain critical considerations for future deployment. This review also outlines the growing range of applications for portable VOC monitors, including workplace exposure assessment, industrial emission control, environmental monitoring stations, and biomedical diagnostics. These systems play a crucial role in risk prevention and contribute to sustainable management practices aimed at reducing pollution and protecting public health. Overall, portable smart-sensor-based VOC monitoring technologies represent a promising direction for future research and innovation.
References
Banerjee, S. (2023). Challenges and Solutions for Data Management in Cloud-Based Environments. International Journal of Advanced Research in Science, Communication and Technology, 370-378. https://doi.org/10.48175/ijarsct-13555c
Benammar, M., Abdaoui, A., Ahmad, S. H. M., Touati, F., & Kadri, A. (2018). A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring. Sensors, 18(2), 581. https://doi.org/10.3390/s18020581
Broday, D. M., & The Citi-Sense Project Collaborators. (2017). Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement—The Promise and the Current Reality. Sensors, 17(10), 2263. https://doi.org/10.3390/s17102263
Buelvas, J., Múnera, D., Tobón V., D. P., Aguirre, J., & Gaviria, N. (2023). Data Quality in IoT-Based Air Quality Monitoring Systems: A Systematic Mapping Study. Water, Air, & Soil Pollution, 234(4), 248. https://doi.org/10.1007/s11270-023-06127-9
Cheah, C. G., Chia, W. Y., Lai, S. F., Chew, K. W., Chia, S. R., & Show, P. L. (2022). Innovation designs of industry 4.0 based solid waste management: Machinery and digital circular economy. Environmental Research, 213, 113619. https://doi.org/10.1016/j.envres.2022.113619
García, L., Garcia-Sanchez, A.-J., Asorey-Cacheda, R., Garcia-Haro, J., & Zúñiga-Cañón, C.-L. (2022). Smart Air Quality Monitoring IoT-Based Infrastructure for Industrial Environments. Sensors, 22(23), 9221. https://doi.org/10.3390/s22239221
Hamza, M. A., Shaiba, H., Marzouk, R., Alhindi, A., Asiri, M. M., Yaseen, I., Motwakel, A., & Rizwanullah, M. (2022). Big Data Analytics with Artificial Intelligence Enabled Environmental Air Pollution Monitoring Framework. Computers, Materials & Continua, 73(2), 3235. https://doi.org/10.32604/cmc.2022.029604
Hernández-Gordillo, A., Ruiz-Correa, S., Robledo-Valero, V., Hernández-Rosales, C., & Arriaga, S. (2021). Recent advancements in low-cost portable sensors for urban and indoor air quality monitoring. Air Quality, Atmosphere & Health, 14(12), 1931-1951. https://doi.org/10.1007/s11869-021-01067-x
Hong, G.-H., Le, T.-C., Lin, G.-Y., Cheng, H.-W., Yu, J.-Y., Dejchanchaiwong, R., Tekasakul, P., & Tsai, C.-J. (2023). Long-term field calibration of low-cost metal oxide VOC sensor: Meteorological and interference gas effects. Atmospheric Environment, 310, 119955. https://doi.org/10.1016/j.atmosenv.2023.119955
Horvat, T., Pehnec, G., & Jakovljević, I. (2025). Volatile Organic Compounds in Indoor Air: Sampling, Determination, Sources, Health Risk, and Regulatory Insights. Toxics, 13(5), 344. https://doi.org/10.3390/toxics13050344
Hussain, M. N., Halim, M. A., Khan, M. Y. A., Ibrahim, S., & Haque, A. (2024). A Comprehensive Review on Techniques and Challenges of Energy Harvesting from Distributed Renewable Energy Sources for Wireless Sensor Networks. Control Systems and Optimization Letters, 2(1), 15-22. https://doi.org/10.59247/csol.v2i1.60
Kortoçi, P., Motlagh, N. H., Zaidan, M. A., Fung, P. L., Varjonen, S., Rebeiro-Hargrave, A., Niemi, J. V., Nurmi, P., Hussein, T., Petäjä, T., Kulmala, M., & Tarkoma, S. (2022). Air pollution exposure monitoring using portable low-cost air quality sensors. Smart Health, 23, 100241. https://doi.org/10.1016/j.smhl.2021.100241
Lanzolla, A., & Spadavecchia, M. (2021). Wireless Sensor Networks for Environmental Monitoring. Sensors, 21(4), 1172. https://doi.org/10.3390/s21041172
Lorenzo-Sáez, E., Oliver-Villanueva, J.-V., Lemus-Zúñiga, L.-G., Coll-Aliaga, E., Castillo, C. P., & Lavalle, C. (2021). Assessment of an air quality surveillance network through passive pollution measurement with mobile sensors. Environmental Research Letters, 16(5), 054072. https://doi.org/10.1088/1748-9326/abe435
Schweizer-Berberich, M., Strathmann, S., Weimar, U., Sharma, R., Seube, A., Peyre-Lavigne, A., & Göpel, W. (1999). Strategies to avoid VOC cross-sensitivity of SnO2-based CO sensors. Sensors and Actuators B: Chemical, 58(1), 318-324. https://doi.org/10.1016/S0925-4005(99)00149-5
Ullah, U., Usama, M., Muhammad, Z., & Akbar, A. (2024). AI-enabled low-powered wireless area networks for quality air. En Low-Power Wide Area Network for Large Scale Internet of Things. CRC Press.

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Copyright (c) 2025 Cristina Velva-Borja (Author)
