{"id":"https://openalex.org/W4321454985","doi":"https://doi.org/10.1145/3584949","title":"Solar-powered Parking Analytics System Using Deep Reinforcement Learning","display_name":"Solar-powered Parking Analytics System Using Deep Reinforcement Learning","publication_year":2023,"publication_date":"2023-02-21","ids":{"openalex":"https://openalex.org/W4321454985","doi":"https://doi.org/10.1145/3584949"},"language":"en","primary_location":{"id":"doi:10.1145/3584949","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3584949","pdf_url":null,"source":{"id":"https://openalex.org/S170502224","display_name":"ACM Transactions on Sensor Networks","issn_l":"1550-4859","issn":["1550-4859","1550-4867"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Sensor Networks","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056482171","display_name":"Yoones Rezaei","orcid":"https://orcid.org/0000-0001-6706-4517"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yoones Rezaei","raw_affiliation_strings":["University of Pittsburgh, Pittsburgh, Pennsylvania, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh, Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100638828","display_name":"Talha Khan","orcid":"https://orcid.org/0000-0003-1552-2728"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Talha Khan","raw_affiliation_strings":["University of Pittsburgh, Pittsburgh, Pennsylvania, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh, Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100650753","display_name":"Stephen Lee","orcid":"https://orcid.org/0000-0001-9022-4259"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephen Lee","raw_affiliation_strings":["University of Pittsburgh, Pittsburgh, Pennsylvania, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh, Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088337929","display_name":"Daniel Moss\u00e9","orcid":"https://orcid.org/0000-0002-9508-9815"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Moss\u00e9","raw_affiliation_strings":["University of Pittsburgh, Pittsburgh, Pennsylvania, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh, Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056482171"],"corresponding_institution_ids":["https://openalex.org/I170201317"],"apc_list":null,"apc_paid":null,"fwci":0.788,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.68210956,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"19","issue":"4","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12546","display_name":"Smart Parking Systems Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12546","display_name":"Smart Parking Systems Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10914","display_name":"Tactile and Sensory Interactions","score":0.9696999788284302,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9419000148773193,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8380812406539917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8201503753662109},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.7326822280883789},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7009086012840271},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.6387978792190552},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.450805127620697},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4369000494480133},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4212053716182709},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4181833267211914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39151522517204285},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3256082832813263},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.13929316401481628},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08581748604774475}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8380812406539917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8201503753662109},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.7326822280883789},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7009086012840271},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.6387978792190552},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.450805127620697},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4369000494480133},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4212053716182709},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4181833267211914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39151522517204285},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3256082832813263},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.13929316401481628},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08581748604774475},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3584949","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3584949","pdf_url":null,"source":{"id":"https://openalex.org/S170502224","display_name":"ACM Transactions on Sensor Networks","issn_l":"1550-4859","issn":["1550-4859","1550-4867"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Sensor Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320333934","display_name":"Center for Research Computing, University of Pittsburgh","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1984148697","https://openalex.org/W1984502030","https://openalex.org/W2111200615","https://openalex.org/W2122046168","https://openalex.org/W2140199336","https://openalex.org/W2142218074","https://openalex.org/W2145339207","https://openalex.org/W2161160262","https://openalex.org/W2163605009","https://openalex.org/W2277615321","https://openalex.org/W2291888299","https://openalex.org/W2405859254","https://openalex.org/W2545300838","https://openalex.org/W2678047256","https://openalex.org/W2752236330","https://openalex.org/W2756881949","https://openalex.org/W2883920103","https://openalex.org/W2901017430","https://openalex.org/W2971847049","https://openalex.org/W2988035443","https://openalex.org/W2994240296","https://openalex.org/W3028307607","https://openalex.org/W3104494818","https://openalex.org/W3109129044","https://openalex.org/W3167267130","https://openalex.org/W4214717370","https://openalex.org/W4230033334","https://openalex.org/W4255491249","https://openalex.org/W4301715823","https://openalex.org/W4402530599","https://openalex.org/W6766152879","https://openalex.org/W6771522568"],"related_works":["https://openalex.org/W4362501864","https://openalex.org/W4306904969","https://openalex.org/W4380318855","https://openalex.org/W2138720691","https://openalex.org/W2031695474","https://openalex.org/W2586732548","https://openalex.org/W3049728571","https://openalex.org/W20361778","https://openalex.org/W2024136090","https://openalex.org/W179829755"],"abstract_inverted_index":{"Advances":[0],"in":[1,129,199],"deep":[2,29,49],"vision":[3],"techniques":[4,31,192],"and":[5,45,82,109,177],"the":[6,13,55,59,64,101,115,118,122,126,130,133,139,171,185,194],"ubiquity":[7],"of":[8,16,26,98,182],"smart":[9],"cameras":[10,56],"will":[11],"drive":[12],"next":[14],"generation":[15],"video":[17,20,42,89],"analytics.":[18],"However,":[19],"analytics":[21,43,90],"applications":[22,74],"consume":[23],"vast":[24],"amounts":[25],"energy":[27,60,140,173],"as":[28],"learning":[30,103],"are":[32],"power-hungry.":[33],"In":[34,114],"this":[35],"article,":[36],"we":[37,83],"focus":[38],"on":[39,121,148],"a":[40,48,149,158],"parking":[41,151],"platform":[44],"propose":[46],"RL-CamSleep,":[47],"reinforcement":[50,102],"learning-based":[51],"technique,":[52],"to":[53,57,78,87,124],"actuate":[54],"reduce":[58],"footprint":[61],"while":[62],"retaining":[63],"system\u2019s":[65],"utility.":[66],"Our":[67,160],"key":[68],"insight":[69],"is":[70,136],"that":[71,169],"many":[72],"video-analytics":[73],"do":[75],"not":[76],"need":[77,195],"be":[79],"always":[80],"operational,":[81],"can":[84,164],"design":[85,95],"policies":[86],"activate":[88],"only":[91],"when":[92],"necessary.":[93],"We":[94,144],"two":[96],"modes":[97],"operation":[99],"for":[100,196],"(RL)":[104],"controller:":[105],"(i)":[106],"cloud-based":[107,116],"mode":[108],"(ii)":[110],"grid-isolated":[111,186],"solar-powered":[112,131],"mode.":[113],"mode,":[117,132,187],"controller":[119,135],"runs":[120],"cloud":[123],"control":[125],"cameras,":[127],"whereas,":[128],"RL":[134],"constrained":[137],"by":[138,142,175],"produced":[141],"solar.":[143],"evaluate":[145],"our":[146],"approach":[147],"city-scale":[150],"dataset":[152],"having":[153],"76":[154],"streets":[155],"spread":[156],"across":[157],"city.":[159],"analysis":[161],"shows":[162],"RL-CamSleep":[163,188],"learn":[165],"an":[166,179],"adaptive":[167,197],"policy":[168,198],"reduces":[170],"average":[172,180],"consumption":[174],"76%":[176],"achieves":[178],"accuracy":[181],"98%.":[183],"For":[184],"outperforms":[189],"other":[190],"baseline":[191],"demonstrating":[193],"energy-constrained":[200],"environments.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}