{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T16:22:57Z","timestamp":1783009377195,"version":"3.54.5"},"reference-count":49,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,9,10]],"date-time":"2018-09-10T00:00:00Z","timestamp":1536537600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shanghai Institute of Intelligent Electronics and Systems","award":["NA"],"award-info":[{"award-number":["NA"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With the swift growth in commerce and transportation in the modern civilization, much attention has been paid to air quality monitoring, however existing monitoring systems are unable to provide sufficient spatial and temporal resolutions of the data with cost efficient and real time solutions. In this paper we have investigated the issues, infrastructure, computational complexity, and procedures of designing and implementing real-time air quality monitoring systems. To daze the defects of the existing monitoring systems and to decrease the overall cost, this paper devised a novel approach to implement the air quality monitoring system, employing the edge-computing based Internet-of-Things (IoT). In the proposed method, sensors gather the air quality data in real time and transmit it to the edge computing device that performs necessary processing and analysis. The complete infrastructure &amp; prototype for evaluation is developed over the Arduino board and IBM Watson IoT platform. Our model is structured in such a way that it reduces the computational burden over sensing nodes (reduced to 70%) that is battery powered and balanced it with edge computing device that has its local data base and can be powered up directly as it is deployed indoor. Algorithms were employed to avoid temporary errors in low cost sensor, and to manage cross sensitivity problems. Automatic calibration is set up to ensure the accuracy of the sensors reporting, hence achieving data accuracy around 75\u201380% under different circumstances. In addition, a data transmission strategy is applied to minimize the redundant network traffic and power consumption. Our model acquires a power consumption reduction up to 23% with a significant low cost. Experimental evaluations were performed under different scenarios to validate the system\u2019s effectiveness.<\/jats:p>","DOI":"10.3390\/s18093021","type":"journal-article","created":{"date-parts":[[2018,9,10]],"date-time":"2018-09-10T10:28:57Z","timestamp":1536575337000},"page":"3021","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":133,"title":["Edge Computing Based IoT Architecture for Low Cost Air Pollution Monitoring Systems: A Comprehensive System Analysis, Design Considerations &amp; Development"],"prefix":"10.3390","volume":"18","author":[{"given":"Zeba","family":"Idrees","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8546-1329","authenticated-orcid":false,"given":"Zhuo","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lirong","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,9,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Khot, R., and Chitre, V. (2017, January 17\u201318). Survey on air pollution monitoring systems. Proceedings of the 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), Coimbatore, India.","DOI":"10.1109\/ICIIECS.2017.8275846"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ahmed, M.M., Banu, S., and Paul, B. (2017, January 7\u20139). Real-time air quality monitoring system for Bangladesh\u2019s perspective based on Internet of Things. Proceedings of the 2017 3rd International Conference on Electrical Information and Communication Technology (EICT), Khulna, Bangladesh.","DOI":"10.1109\/EICT.2017.8275161"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"31392","DOI":"10.3390\/s151229859","article-title":"A survey of wireless sensor network based air pollution monitoring systems","volume":"15","author":"Yi","year":"2015","journal-title":"Sensors"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Vel\u00e1squez, P., V\u00e1squez, L., Correa, C., and Rivera, D. (2017, January 18\u201320). A low-cost IoT based environmental monitoring system. A citizen approach to pollution awareness. Proceedings of the 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), Pucon, Chile.","DOI":"10.1109\/CHILECON.2017.8229599"},{"key":"ref_5","unstructured":"Chen, X.J., Liu, X.P., and Xu, P. (2015, January 27\u201329). IOT-based air pollution monitoring and forecasting system. Proceedings of the 2015 International Conference on Computer and Computational Sciences (ICCCS), Noida, India."},{"key":"ref_6","first-page":"100","article-title":"IoT Based Air Pollution Monitoring System","volume":"3","author":"Devahema","year":"2018","journal-title":"J. Netw. Commun. Emerg. Technol."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Alvear, O., Zamora, W., Calafate, C.T., Cano, J.C., and Manzoni, P. (2016, January 21\u201324). EcoSensor: Monitoring environmental pollution using mobile sensors. Proceedings of the 2016 IEEE 17th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Coimbra, Portugal.","DOI":"10.1109\/WoWMoM.2016.7523519"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Caya, M.V.C., Babila, A.P., Bais, A.M.M., Im, S.J.V., and Maramba, R. (2017, January 1\u20133). Air pollution and particulate matter detector using raspberry Pi with IoT based notification. Proceedings of the 2017 IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), Manila, Philippines.","DOI":"10.1109\/HNICEM.2017.8269490"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Gao, Y., Dong, W., Guo, K., Liu, X., Chen, Y., Liu, X., Bu, J., and Chen, C. (2016, January 10\u201314). Mosaic: A low-cost mobile sensing system for urban air quality monitoring. Proceedings of the IEEE INFOCOM 2016\u2014The 35th Annual IEEE International Conference on Computer Communications, San Francisco, CA, USA.","DOI":"10.1109\/INFOCOM.2016.7524478"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kang, J., and Hwang, K.-I. (2016). A Comprehensive Real-Time Indoor Air-Quality Level Indicator. Sustainability, 8.","DOI":"10.3390\/su8090881"},{"key":"ref_11","unstructured":"(2018, April 21). Enviornmental Protection Agency US, Available online: https:\/\/www.airnow.gov\/index.cfm?action=pubs.index."},{"key":"ref_12","unstructured":"(2018, April 21). Air Quality Index Report, Available online: https:\/\/www.epa.gov\/outdoor-air-quality-data\/air-quality-index-report."},{"key":"ref_13","unstructured":"(2018, April 21). Shanghai Air Pollution: Real-time Air Quality Index (AQI). Available online: http:\/\/aqicn.org\/city\/shanghai\/."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Andr\u00e9s, G.R.C. (2016, January 14\u201316). CleanWiFi: The wireless network for air quality monitoring, community Internet access and environmental education in smart cities. Proceedings of the 2016 ITU Kaleidoscope: ICTs for a Sustainable World (ITU WT), Bangkok, Thailand.","DOI":"10.1109\/ITU-WT.2016.7805708"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Braem, B., Latre, S., Leroux, P., Demeester, P., Coenen, T., and Ballon, P. (2016, January 12\u201315). Designing a smart city playground: Real-time air quality measurements and visualization in the City of Things testbed. Proceedings of the 2016 IEEE International Smart Cities Conference (ISC2), Trento, Italy.","DOI":"10.1109\/ISC2.2016.7580871"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Hojaiji, H., Goldstein, O., King, C.E., Sarrafzadeh, M., and Jerrett, M. (2017, January 19\u201322). Design and calibration of a wearable and wireless research grade air quality monitoring system for real-time data collection. Proceedings of the 2017 IEEE Global Humanitarian Technology Conference (GHTC), San Jose, CA, USA.","DOI":"10.1109\/GHTC.2017.8239308"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Alshamsi, A., Anwar, Y., Almulla, M., Aldohoori, M., Hamad, N., and Awad, M. (2017, January 21\u201323). Monitoring pollution: Applying IoT to create a smart environment. Proceedings of the 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA), Ras Al Khaimah, UAE.","DOI":"10.1109\/ICECTA.2017.8251998"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Bellavista, P., Giannelli, C., and Zamagna, R. (2017). The PeRvasive Environment Sensing and Sharing Solution. Sustainability, 9.","DOI":"10.3390\/su9040585"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Lee, S., Jo, J., Kim, Y., and Stephen, H. (July, January 27). A framework for environmental monitoring with Arduino-based sensors using Restful web service. Proceedings of the 2014 IEEE International Conference on Services, Anchorage, AK, USA.","DOI":"10.1109\/SCC.2014.44"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Yang, Y., Zheng, Z., Bian, K., Jiang, Y., Song, L., and Han, Z. (2017, January 4\u20138). Arms: A Fine-Grained 3D AQI Realtime Monitoring System by UAV. Proceedings of the GLOBECOM 2017\u20142017 IEEE Global Communications, Singapore.","DOI":"10.1109\/GLOCOM.2017.8253968"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Min, K.T., Forys, A., and Schmid, T. (2014, January 15\u201317). Demonstration abstract: Airfeed: Indoor real time interactive air quality monitoring system. Proceedings of the 13th International Symposium on Information Processing in Sensor Networks, Berlin, Germany.","DOI":"10.1109\/IPSN.2014.6846785"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Simi\u0107, M., Stojanovi\u0107, G.M., Manjakkal, L., and Zaraska, K. (2016, January 22\u201323). Multi-sensor system for remote environmental (air and water) quality monitoring. Proceedings of the 2016 24th Telecommunications Forum (TELFOR), Belgrade, Serbia.","DOI":"10.1109\/TELFOR.2016.7818711"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Boubrima, A., Bechkit, W., and Rivano, H. (2016, January 26\u201328). Optimal deployment of dense wsn for error bounded air pollution mapping. Proceedings of the 2016 International Conference on Distributed Computing in Sensor Systems (DCOSS), Washington, DC, USA.","DOI":"10.1109\/DCOSS.2016.26"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2723","DOI":"10.1109\/TWC.2017.2658601","article-title":"Optimal WSN deployment models for air pollution monitoring","volume":"16","author":"Boubrima","year":"2017","journal-title":"IEEE Trans. Wireless Commun."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4230","DOI":"10.1109\/JSEN.2014.2359832","article-title":"ISSAQ: An integrated sensing systems for real-time indoor air quality monitoring","volume":"14","author":"Kim","year":"2014","journal-title":"IEEE Sens. J."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Taylor, M.D. (November, January 30). Low-cost air quality monitors: Modeling and characterization of sensor drift in optical particle counters. Proceedings of the 2016 IEEE SENSORS, Orlando, FL, USA.","DOI":"10.1109\/ICSENS.2016.7808832"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Yang, X., Yang, L., and Zhang, J. (2017, January 3\u20136). A WiFi-enabled indoor air quality monitoring and control system: The design and control experiments. Proceedings of the 2017 13th IEEE International Conference on Control & Automation (ICCA), Ohrid, Macedonia.","DOI":"10.1109\/ICCA.2017.8003185"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Rachana, M., Abhilash, B., Meghana, P., Mishra, V., and Rudraswamy, S.B. (2017, January 15\u201316). Design and deployment of sensor system\u2014envirobat 2.1, an urban air quality monitoring system. Proceedings of the 2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), Mysuru, India.","DOI":"10.1109\/ICEECCOT.2017.8284539"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Li, Y., and He, J. (2017, January 3\u20135). Design of an intelligent indoor air quality monitoring and purification device. Proceedings of the 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference (ITOEC), Chongqing, China.","DOI":"10.1109\/ITOEC.2017.8122535"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Kim, S.H., Jeong, J.M., Hwang, M.T., and Kang, C.S. (2017, January 18\u201320). Development of an IoT-based atmospheric environment monitoring system. Proceedings of the 2017 International Conference on Information and Communication Technology Convergence (ICTC), Jeju, Korea.","DOI":"10.1109\/ICTC.2017.8190799"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Firdhous, M., Sudantha, B., and Karunaratne, P. (2017, January 23\u201324). IoT enabled proactive indoor air quality monitoring system for sustainable health management. Proceedings of the 2017 2nd International Conference on Computing and Communications Technologies (ICCCT), Chennai, India.","DOI":"10.1109\/ICCCT2.2017.7972281"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Swain, K.B., Santamanyu, G., and Senapati, A.R. (2017, January 4\u20135). Smart industry pollution monitoring and controlling using LabVIEW based IoT. Proceedings of the 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS), Chennai, India.","DOI":"10.1109\/SSPS.2017.8071568"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Arfire, A., Marjovi, A., and Martinoli, A. (2016, January 12\u201315). Enhancing measurement quality through active sampling in mobile air quality monitoring sensor networks. Proceedings of the 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Banff, AB, Canada.","DOI":"10.1109\/AIM.2016.7576904"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Arvind, D.K., Mann, J., Bates, A., and Kotsev, K. (September, January 31). The AirSpeck family of static and mobile wireless air quality monitors. Proceedings of the 2016 Euromicro Conference on Digital System Design (DSD), Limassol, Cyprus.","DOI":"10.1109\/DSD.2016.110"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Fioccola, G.B., Sommese, R., Tufano, I., Canonico, R., and Ventre, G. (2016, January 7\u20139). Polluino: An efficient cloud-based management of IoT devices for air quality monitoring. Proceedings of the 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI), Bologna, Italy.","DOI":"10.1109\/RTSI.2016.7740617"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3238","DOI":"10.1109\/ACCESS.2016.2582153","article-title":"Design and implementation of LPWA-based air quality monitoring system","volume":"4","author":"Zheng","year":"2016","journal-title":"IEEE Access"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Yokoyama, M., Hara, T., and Madria, S.K. (2017, January 11\u201314). Efficient diversified set monitoring for mobile sensor stream environments. in Big Data (Big Data). Proceedings of the 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, USA.","DOI":"10.1109\/BigData.2017.8257964"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1109\/MCG.2017.3621228","article-title":"Visual Analytics for Spatial Clusters of Air-Quality Data","volume":"37","author":"Zhou","year":"2017","journal-title":"IEEE Comput. Graph. Appl."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s11277-016-3845-0","article-title":"Software-Defined Fog Network Architecture for IoT","volume":"92","author":"Tomovic","year":"2017","journal-title":"Wirel. Pers. Commun."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"854","DOI":"10.1109\/JIOT.2016.2584538","article-title":"Fog and IoT: An overview of research opportunities","volume":"3","author":"Chiang","year":"2016","journal-title":"IEEE Internet Things J."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1872","DOI":"10.1109\/ACCESS.2017.2666200","article-title":"A Survey on Software-Defined Wireless Sensor Networks: Challenges and Design Requirements","volume":"5","author":"Kobo","year":"2017","journal-title":"IEEE Access"},{"key":"ref_42","unstructured":"(2018, August 24). MQ-135 GAS SENSOR. Available online: https:\/\/www.olimex.com\/Products\/Components\/Sensors\/SNS-MQ135\/resources\/SNS-MQ135.pdf."},{"key":"ref_43","unstructured":"(2018, August 24). MQ-7 GAS SENSOR. Available online: https:\/\/www.sparkfun.com\/datasheets\/Sensors\/Biometric\/MQ-7.pdf."},{"key":"ref_44","unstructured":"(2018, August 24). MQ-9 GAS SENSOR. Available online: https:\/\/www.scribd.com\/document\/314816873\/Datasheet-sensor-MQ9."},{"key":"ref_45","unstructured":"(2018, August 24). MQ-8 GAS SENSOR. Available online: https:\/\/dlnmh9ip6v2uc.cloudfront.net\/datasheets\/Sensors\/Biometric\/MQ-8.pdf."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1145\/1525856.1525863","article-title":"Sensor network data fault types","volume":"5","author":"Ni","year":"2009","journal-title":"ACM Trans. Sens. Netw."},{"key":"ref_47","unstructured":"(2018, August 24). Ministry of Ecology and Environment, Available online: http:\/\/english.mep.gov.cn\/."},{"key":"ref_48","unstructured":"(2018, August 24). National Service Center for Environmental Publications (NSCEP), Available online: https:\/\/nepis.epa.gov\/."},{"key":"ref_49","unstructured":"(2018, August 24). Shanghai Air Quality: PM2.5. Available online: http:\/\/www.young-0.com\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/9\/3021\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:19:38Z","timestamp":1760195978000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/9\/3021"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,10]]},"references-count":49,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2018,9]]}},"alternative-id":["s18093021"],"URL":"https:\/\/doi.org\/10.3390\/s18093021","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,10]]}}}