{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T14:54:40Z","timestamp":1777733680556,"version":"3.51.4"},"reference-count":46,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T00:00:00Z","timestamp":1648512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2022,3,29]]},"abstract":"<jats:p>Despite regulations and policies to improve city-level air quality in the long run, there lack precise control measures to protect critical urban spots from heavy air pollution. In this work, we propose iSpray, the first-of-its-kind data analytics engine for fine-grained PM2.5 and PM10 control at key urban areas via cost-effective water spraying. iSpray combines domain knowledge with machine learning to profile and model how water spraying affects PM25 and PM10 concentrations in time and space. It also utilizes predictions of pollution propagation paths to schedule a minimal number of sprayers to keep the pollution concentrations at key spots under control. In-field evaluations show that compared with scheduling based on real-time pollution concentrations, iSpray reduces the total sprayer switch-on time by 32%, equivalent to 1, 782 m3 water and 18, 262 kWh electricity in our deployment, while decreasing the days of poor air quality at key spots by up to 16%.<\/jats:p>","DOI":"10.1145\/3517227","type":"journal-article","created":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T13:42:46Z","timestamp":1648561366000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["iSpray"],"prefix":"10.1145","volume":"6","author":[{"given":"Yun","family":"Cheng","sequence":"first","affiliation":[{"name":"ETH Zurich, Computer Engineering and Networks Laboratory, Zurich, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zimu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Singapore Management University, School of Computing and Information Systems, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lothar","family":"Thiele","sequence":"additional","affiliation":[{"name":"ETH Zurich, Computer Engineering and Networks Laboratory, Zurich, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,3,29]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.ede.0000199439.57655.6b"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.matcom.2004.06.023"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1183\/09031936.05.00001805"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2016.11.188"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3314389"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3314393"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/IoTDI49375.2020.00010"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-12640-1_16"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2668332.2668346"},{"key":"e_1_2_1_10_1","volume-title":"Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers","author":"Cheng Yun","unstructured":"Yun Cheng, Olga Saukh, and Lothar Thiele. 2021. TIP-Air: Tracking Pollution Transfer for Accurate Air Quality Prediction. In Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers. ACM, New York, NY, USA, 589--599."},{"key":"e_1_2_1_11_1","volume-title":"Douglas W Dockery, Yun Wang, Majid Ezzati, and Francesca Dominici.","author":"Correia Andrew W","year":"2013","unstructured":"Andrew W Correia, C Arden Pope III, Douglas W Dockery, Yun Wang, Majid Ezzati, and Francesca Dominici. 2013. The effect of air pollution control on life expectancy in the United States: an analysis of 545 US counties for the period 2000 to 2007. Epidemiology (Cambridge, Mass.) 24, 1 (2013), 23."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nucengdes.2016.06.043"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488713"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2016.7524478"},{"key":"e_1_2_1_15_1","unstructured":"Michael Greenstone and Patrick Schwarz. 2018. Is China winning its war on pollution?"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pmcj.2014.11.008"},{"key":"e_1_2_1_17_1","unstructured":"Baidu Inc. 2021. Baidu POI. http:\/\/lbsyun.baidu.com\/index.php?title=androidsdk\/guide\/search\/poi."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.8768"},{"key":"e_1_2_1_19_1","volume-title":"Analysis of exposure-response relationships of air particulate matter and adverse health outcomes in China. Journal of Environment and Health 6","author":"Kan Haidong","year":"1989","unstructured":"Haidong Kan and Bingheng Chen. 1989. Analysis of exposure-response relationships of air particulate matter and adverse health outcomes in China. Journal of Environment and Health 6 (1989)."},{"key":"e_1_2_1_20_1","volume-title":"Handbook for Dust Control in Mining","author":"Kissell Fred N","unstructured":"Fred N Kissell. 2003. Handbook for Dust Control in Mining. NIOSH, Cincinnati, OH, USA."},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmst.2013.12.007"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigComp48618.2020.00-99"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098090"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3191752"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/618109"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.envres.2014.06.029"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397322"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3191756"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-15562-9"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.7424\/jsm130204"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-28650-9_4"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460418.3479277"},{"key":"e_1_2_1_33_1","unstructured":"Xingjian SHI Zhourong Chen Hao Wang Dit-Yan Yeung Wai-kin Wong and Wang-chun WOO. 2015. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. In Advances in Neural Information Processing Systems C. Cortes N. Lawrence D. Lee M. Sugiyama and R. Garnett (Eds.). Curran Associates Inc. Red Hook NY USA 802--810."},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/MDM52706.2021.00015"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2858036.2858571"},{"key":"e_1_2_1_36_1","first-page":"211","article-title":"Dust Control Measures in the Construction Industry","volume":"47","author":"Nij Evelyn Tjoe","year":"2003","unstructured":"Evelyn Tjoe Nij, Simone Hilhorst, Ton Spee, Judith Spierings, Friso Steffens, Mieke Lumens, and Dick Heederik. 2003. Dust Control Measures in the Construction Industry. Annals of Occupational Hygiene 47, 3 (2003), 211--218.","journal-title":"Annals of Occupational Hygiene"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.14778\/3236187.3236211"},{"key":"e_1_2_1_38_1","volume-title":"Yue Chen, Susan M Gapstur, and Michael J Thun.","author":"Turner Michelle C","year":"2011","unstructured":"Michelle C Turner, Daniel Krewski, C Arden Pope III, Yue Chen, Susan M Gapstur, and Michael J Thun. 2011. Long-term ambient fine particulate matter air pollution and lung cancer in a large cohort of never-smokers. American journal of respiratory and critical care medicine 184, 12 (2011), 1374--1381."},{"key":"e_1_2_1_39_1","unstructured":"World Health Organization. 2018. Ambient Air Pollution - a Major Threat to Health and Climate. http:\/\/www.who.int\/airpollution\/ambient\/en\/."},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397328"},{"key":"e_1_2_1_41_1","first-page":"E69","article-title":"The impact of PM2. 5 on the human respiratory system","volume":"8","author":"Xing Yu-Fei","year":"2016","unstructured":"Yu-Fei Xing, Yue-Hua Xu, Min-Hua Shi, and Yi-Xin Lian. 2016. The impact of PM2. 5 on the human respiratory system. Journal of thoracic disease 8, 1 (2016), E69.","journal-title":"Journal of thoracic disease"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10311-013-0444-0"},{"key":"e_1_2_1_43_1","volume-title":"Air Pollution Modeling","author":"Zannetti Paolo","unstructured":"Paolo Zannetti. 1990. Gaussian models. In Air Pollution Modeling. Springer, Berlin, Germany, 141--183."},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.14778\/3368289.3368297"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2488188"},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788573"}],"container-title":["Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3517227","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3517227","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T04:26:01Z","timestamp":1752467161000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3517227"}},"subtitle":["Reducing Urban Air Pollution with Intelligent Water Spraying"],"short-title":[],"issued":{"date-parts":[[2022,3,29]]},"references-count":46,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,3,29]]}},"alternative-id":["10.1145\/3517227"],"URL":"https:\/\/doi.org\/10.1145\/3517227","relation":{},"ISSN":["2474-9567"],"issn-type":[{"value":"2474-9567","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,29]]},"assertion":[{"value":"2022-03-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}