{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T18:56:43Z","timestamp":1776365803675,"version":"3.51.2"},"reference-count":30,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Traffic prOcessing foR uRban EnvironmentS (TORRES), a Joint Research and Development Project"},{"name":"\u201cR\u00e9gion de Bruxelles-Capitale-Innoviris\u201d","award":["2022-RDIR-59b"],"award-info":[{"award-number":["2022-RDIR-59b"]}]},{"DOI":"10.13039\/100014013","name":"UK Research and Innovation (UKRI) Future Leaders Fellowship: \u2018Digitally Assisted Collective Governance of Smart City Commons\u2013ARTIO\u2019","doi-asserted-by":"publisher","award":["MR\/W009560\/1"],"award-info":[{"award-number":["MR\/W009560\/1"]}],"id":[{"id":"10.13039\/100014013","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Alan Turing Fellowship"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3343620","type":"journal-article","created":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T19:45:07Z","timestamp":1702669507000},"page":"142125-142145","source":"Crossref","is-referenced-by-count":9,"title":["Cooperative Multi-Agent Traffic Monitoring Can Reduce Camera Surveillance"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6865-1833","authenticated-orcid":false,"given":"Davide Andrea","family":"Guastella","sequence":"first","affiliation":[{"name":"Machine Learning Group, Universit&#x00E9; Libre de Bruxelles, Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3900-2057","authenticated-orcid":false,"given":"Evangelos","family":"Pournaras","sequence":"additional","affiliation":[{"name":"School of Computing, University of Leeds, Leeds, U.K"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/su132011162"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s10610-022-09527-5"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2022.110737"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2022.07.026"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-07940-9"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2019.107198"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2018.1700139"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/rs13040573"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00168"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2023.104387"},{"key":"ref11","article-title":"Short vs. long-term coordination of drones: When distributed optimization meets deep reinforcement learning","author":"Qin","year":"2023","journal-title":"arXiv:2311.09852"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11172748"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2023.109626"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2020.02.006"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1080\/15472450.2021.1966626"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/s20174824"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3025687"},{"key":"ref18","first-page":"347","article-title":"Exploiting LoRa, edge, and fog computing for traffic monitoring in smart cities","volume-title":"LPWAN Technologies for IoT and M2M Applications","author":"Gia","year":"2020"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-30930-3"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-22922-0_11"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103490"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3028967"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.52825\/scp.v2i.107"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-39698-6"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-15024-6_4"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.trd.2022.103477"},{"key":"ref27","volume-title":"Forecasting: Principles and Practice","author":"Hyndman","year":"2018"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2021.3058928"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/SEAMS.2019.00014"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ACSOS-C58168.2023.00021"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10360829.pdf?arnumber=10360829","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T22:37:25Z","timestamp":1705099045000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10360829\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3343620","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}