Smart City Gnosys

Smart city article details

Title	Applications Of Machine Learning & Internet Of Things For Outdoor Air Pollution Monitoring And Prediction: A Systematic Literature Review
ID_Doc	10105
Authors	Gryech I.; Asaad C.; Ghogho M.; Kobbane A.
Year	2024
Published	Engineering Applications of Artificial Intelligence, 137
DOI	http://dx.doi.org/10.1016/j.engappai.2024.109182
Abstract	According to the World Health Organization (WHO), air pollution kills seven million people every year. Outdoor air pollution is a major environmental health problem affecting low, middle, and high-income countries. In the past few years, the research community has explored IoT-enabled machine learning applications for outdoor air pollution prediction. The general objective of this paper is to systematically review applications of machine learning and Internet of Things (IoT) for outdoor air pollution prediction and the combination of monitoring sensors and input features used. Two research questions were formulated for this review. 1086 publications were collected in the initial PRISMA stage. After the screening and eligibility phases, 37 papers were selected for inclusion. A cost-based analysis was conducted on the findings to highlight high-cost monitoring, low-cost IoT and hybrid enabled prediction. Three methods of prediction were identified: time series, feature-based and spatio-temporal. This review's findings identify major limitations in applications found in the literature, namely lack of coverage, lack of diversity of data and lack of inclusion of context-specific features. This review proposes directions for future research and underlines practical implications in healthcare, urban planning, global synergy and smart cities. © 2024 Elsevier Ltd
Author Keywords	Internet of Things; Machine learning; Outdoor air pollution; Pollution monitoring; Predictive models

Similar Articles

Id	Similarity	Authors	Title	Published
7141	0.934	Catovic A.; Kadusic E.; Ruland C.; Zivic N.; Hadzajlic N.	Air Pollution Prediction And Warning System Using Iot And Machine Learning	International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022 (2022)
27055	0.928	Varade H.P.; Bhangale S.C.; Thorat S.R.; Khatkale P.B.; Sharma S.K.; William P.	Framework Of Air Pollution Assessment In Smart Cities Using Iot With Machine Learning Approach	Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023 (2023)
31860	0.928	Samal A.; Samal L.; Swain A.K.; Mahapatra K.	Integrated Iot-Based Air Quality Monitoring And Prediction System: A Hybrid Approach	Proceedings - 2023 IEEE International Symposium on Smart Electronic Systems, iSES 2023 (2023)
7559	0.923	Samee I.U.; Jilani M.T.; Wahab H.G.A.	An Application Of Iot And Machine Learning To Air Pollution Monitoring In Smart Cities	2019 4th International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2019 (2019)
36027	0.923	Zareba M.; Cogiel S.; Danek T.; Weglinska E.	Machine Learning Techniques For Spatio-Temporal Air Pollution Prediction To Drive Sustainable Urban Development In The Era Of Energy And Data Transformation	Energies , 17, 11 (2024)
15000	0.921	Ameer, S; Shah, MA; Khan, A; Song, HB; Maple, C; Ul Islam, S; Asghar, MN	Comparative Analysis Of Machine Learning Techniques For Predicting Air Quality In Smart Cities	IEEE ACCESS, 7 (2019)
7169	0.92	Iskandaryan D.; Ramos F.; Trilles S.	Air Quality Prediction In Smart Cities Using Machine Learning Technologies Based On Sensor Data: A Review	Applied Sciences (Switzerland), 10, 7 (2020)
53645	0.913	Essamlali I.; Nhaila H.; El Khaili M.	Supervised Machine Learning Approaches For Predicting Key Pollutants And For The Sustainable Enhancement Of Urban Air Quality: A Systematic Review	Sustainability (Switzerland), 16, 3 (2024)
33609	0.913	Janardhan M.; Rakshitha N.; Sravani E.; Afroz D.M.; Supriya N.	Iot And Ml For Air Pollution Monitoring With Real Time Data And Prediction Of Health Advisory	Proceedings of 5th International Conference on Trends in Material Science and Inventive Materials, ICTMIM 2025 (2025)
33702	0.907	Alnowaiser K.; Alarfaj A.A.; Alabdulqader E.A.; Umer M.; Cascone L.; Alankar B.	Iot Based Smart Framework To Predict Air Quality In Congested Traffic Areas Using Sv-Cnn Ensemble And Knn Imputation Model	Computers and Electrical Engineering, 118 (2024)