{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T17:23:45Z","timestamp":1778347425199,"version":"3.51.4"},"reference-count":25,"publisher":"SAGE Publications","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2022,9,22]]},"abstract":"<jats:p>With the rapid industrialization and urbanization worldwide, air quality levels are deteriorating at an unprecedented rate and posing a substantial threat to humans and the environment. This brings the concern to effectively monitor and forecast air quality levels in real-time. Conventional air quality monitoring stations are built based on centralized architectures involving high latency, communication technologies demanding high power, sensors involving high costs and decision making with moderate accuracy. To address the limitations of the existing systems, we propose a smart and distinct Air Quality Monitoring and Forecasting system embracing Fog Computing with IoT and Deep Learning (DL). The system is a three-layered architecture with the Sensing layer first, Fog Computing layer in between, and Cloud Computing layer at the end. Fog Computing is a powerful new generation paradigm that brings storage, computation, and networking at the edge of the IoT network and reduce network latency. A DL based BiLSTM (Bidirectional Long Short-Term Memory) model is deployed in the Fog Computing layer. The proposed system aims at real-time monitoring and accurate air quality forecasting to support decision making and aid timely prevention and control of pollutant emissions by alerting the stakeholders when a dangerous Air Quality Index (AQI) is expected. Experimental results show that the BiLSTM model has a better predictive performance considering the meteorological parameters than the baseline models in terms of MAE and RMSE. A proof of concept realizing the proposed system is elaborated in the paper.<\/jats:p>","DOI":"10.3233\/jifs-212713","type":"journal-article","created":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T12:34:54Z","timestamp":1654605294000},"page":"5621-5642","source":"Crossref","is-referenced-by-count":9,"title":["Fog computing enabled air quality monitoring and prediction leveraging deep learning in IoT"],"prefix":"10.1177","volume":"43","author":[{"given":"P. Divya","family":"Bharathi","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita VishwaVidyapeetham, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V. Anantha","family":"Narayanan","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita VishwaVidyapeetham, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P. Bagavathi","family":"Sivakumar","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita VishwaVidyapeetham, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-212713_ref1","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.is.2014.07.006","article-title":"The rise of \u201cbig data\u201d on cloud computing: Review and open research issues","volume":"47","author":"Hashem","year":"2015","journal-title":"Information Systems"},{"issue":"1","key":"10.3233\/JIFS-212713_ref2","first-page":"31","article-title":"Air pollution and chronic airway diseases: what should people know and do?","volume":"8","author":"Jiang","year":"2016","journal-title":"Journal of Thoracic Disease"},{"key":"10.3233\/JIFS-212713_ref4","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.jnca.2017.09.002","article-title":"Survey on fog computing:architecture, key technologies, applications and open issues,","volume":"98","author":"Hu","year":"2017","journal-title":"Journal of Network and Computer Applications"},{"key":"10.3233\/JIFS-212713_ref9","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.jss.2019.04.050","article-title":"Fogbus: A blockchain-based lightweight framework for edge and fog computing","volume":"154","author":"Tuli","year":"2019","journal-title":"Journal of Systems and Software"},{"key":"10.3233\/JIFS-212713_ref11","doi-asserted-by":"crossref","unstructured":"Gia T.N. , Queralta J.P. , Westerlund T. 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