{"id":"https://openalex.org/W3207072229","doi":"https://doi.org/10.1109/smartcomp52413.2021.00027","title":"ARIS: A Real Time Edge Computed Accident Risk Inference System","display_name":"ARIS: A Real Time Edge Computed Accident Risk Inference System","publication_year":2021,"publication_date":"2021-08-01","ids":{"openalex":"https://openalex.org/W3207072229","doi":"https://doi.org/10.1109/smartcomp52413.2021.00027","mag":"3207072229"},"language":"en","primary_location":{"id":"doi:10.1109/smartcomp52413.2021.00027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartcomp52413.2021.00027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Smart Computing (SMARTCOMP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.13016/m2yow8-nabr","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054156338","display_name":"Pretom Roy Ovi","orcid":"https://orcid.org/0009-0004-4955-1679"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pretom Roy Ovi","raw_affiliation_strings":["Center for Real-time Distributed Sensing and Autonomy (https://cards.umbc.edu), University of Maryland, Baltimore County, USA"],"affiliations":[{"raw_affiliation_string":"Center for Real-time Distributed Sensing and Autonomy (https://cards.umbc.edu), University of Maryland, Baltimore County, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102926029","display_name":"Emon Dey","orcid":"https://orcid.org/0000-0002-1290-0378"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emon Dey","raw_affiliation_strings":["Center for Real-time Distributed Sensing and Autonomy (https://cards.umbc.edu), University of Maryland, Baltimore County, USA"],"affiliations":[{"raw_affiliation_string":"Center for Real-time Distributed Sensing and Autonomy (https://cards.umbc.edu), University of Maryland, Baltimore County, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068320631","display_name":"Nirmalya Roy","orcid":"https://orcid.org/0000-0003-4827-3393"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nirmalya Roy","raw_affiliation_strings":["Center for Real-time Distributed Sensing and Autonomy (https://cards.umbc.edu), University of Maryland, Baltimore County, USA"],"affiliations":[{"raw_affiliation_string":"Center for Real-time Distributed Sensing and Autonomy (https://cards.umbc.edu), University of Maryland, Baltimore County, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051208435","display_name":"Aryya Gangopadhyay","orcid":"https://orcid.org/0000-0002-7553-7932"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aryya Gangopadhyay","raw_affiliation_strings":["Center for Real-time Distributed Sensing and Autonomy (https://cards.umbc.edu), University of Maryland, Baltimore County, USA"],"affiliations":[{"raw_affiliation_string":"Center for Real-time Distributed Sensing and Autonomy (https://cards.umbc.edu), University of Maryland, Baltimore County, USA","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054156338"],"corresponding_institution_ids":["https://openalex.org/I79272384"],"apc_list":null,"apc_paid":null,"fwci":1.2143,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.77167341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"47","last_page":"54"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9991000294685364,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9991000294685364,"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/T10370","display_name":"Traffic and Road Safety","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9513999819755554,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/computer-science","display_name":"Computer science","score":0.7220820784568787},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6089645028114319},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48988717794418335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30832812190055847}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7220820784568787},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6089645028114319},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48988717794418335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30832812190055847}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/smartcomp52413.2021.00027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartcomp52413.2021.00027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Smart Computing (SMARTCOMP)","raw_type":"proceedings-article"},{"id":"pmh:oai:mdsoar.org:11603/23237","is_oa":false,"landing_page_url":"http://hdl.handle.net/11603/23237","pdf_url":null,"source":{"id":"https://openalex.org/S4306402556","display_name":"Maryland Shared Open Access Repository (USMAI Consortium)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"doi:10.13016/m2yow8-nabr","is_oa":true,"landing_page_url":"https://doi.org/10.13016/m2yow8-nabr","pdf_url":null,"source":{"id":"https://openalex.org/S4306402644","display_name":"Digital Repository at the University of Maryland (University of Maryland College Park)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.13016/m2yow8-nabr","is_oa":true,"landing_page_url":"https://doi.org/10.13016/m2yow8-nabr","pdf_url":null,"source":{"id":"https://openalex.org/S4306402644","display_name":"Digital Repository at the University of Maryland (University of Maryland College Park)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G8230916623","display_name":null,"funder_award_id":"1923982","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1902934009","https://openalex.org/W1997430507","https://openalex.org/W2059425182","https://openalex.org/W2064675550","https://openalex.org/W2099471712","https://openalex.org/W2122679244","https://openalex.org/W2150882603","https://openalex.org/W2233116163","https://openalex.org/W2337546824","https://openalex.org/W2546536770","https://openalex.org/W2549401308","https://openalex.org/W2625157458","https://openalex.org/W2789876780","https://openalex.org/W2798249343","https://openalex.org/W2799197246","https://openalex.org/W2805029963","https://openalex.org/W2806282362","https://openalex.org/W2945388018","https://openalex.org/W2953066832","https://openalex.org/W2963048316","https://openalex.org/W2963114950","https://openalex.org/W2963225922","https://openalex.org/W2963674932","https://openalex.org/W2974690168","https://openalex.org/W2978776074","https://openalex.org/W2990605346","https://openalex.org/W2997076693","https://openalex.org/W3012971112","https://openalex.org/W3100199031","https://openalex.org/W3113595016","https://openalex.org/W4320013936","https://openalex.org/W6639703010","https://openalex.org/W6679667936","https://openalex.org/W6685891324","https://openalex.org/W6752353878","https://openalex.org/W6764779489"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"To":[0,117],"deploy":[1],"an":[2,9,36,42,75],"intelligent":[3],"transport":[4,32],"system":[5,125],"in":[6,33,61,208,310,325],"urban":[7],"environment,":[8],"effective":[10],"and":[11,31,52,110,177,199,231,271,286,296,302],"real-time":[12,115,127],"accident":[13,50,79,129,135,210,280],"risk":[14],"prediction":[15,53,77,130],"method":[16],"is":[17,41,155],"required":[18],"that":[19,163,255],"can":[20,80],"help":[21],"maintain":[22],"road":[23],"safety,":[24,48],"provide":[25],"adequate":[26],"level":[27],"of":[28,35,58,78,85,92,98,143,167,191,197,227,257,318,322],"medical":[29],"assistance":[30],"case":[34],"emergency.":[37],"Reducing":[38],"traffic":[39,67,128,134,279],"accidents":[40],"important":[43],"problem":[44],"for":[45,114,126],"increasing":[46],"public":[47],"so":[49],"analysis":[51],"have":[54,181,201,219,235,289,329],"been":[55],"a":[56,66,70,124,133,158,165,188,224,251,331],"subject":[57],"extensive":[59,107],"research":[60],"recent":[62],"time.":[63],"Even":[64],"if":[65],"hazard":[68],"occurs,":[69],"readily":[71],"deployable":[72],"structure":[73],"with":[74,101,242,264,307],"accurate":[76],"contribute":[81],"to":[82,150,213,276,291,313],"better":[83,314],"management":[84],"rescue":[86],"resources.":[87],"But":[88],"the":[89,96,238,248,293,316],"significant":[90,203],"shortcomings":[91],"current":[93],"studies":[94],"are":[95],"use":[97],"small-scale":[99],"datasets":[100],"minimal":[102],"scope,":[103],"being":[104,112],"based":[105,156],"on":[106,132,157,250],"data":[108,168],"sets,":[109],"not":[111],"applicable":[113],"purposes.":[116],"overcome":[118],"these":[119],"challenges,":[120],"we":[121,200,218,328],"propose":[122],"ARIS:":[123],"built":[131],"dataset":[136],"named":[137],"\u2018US-Accidents\u2019":[138],"which":[139],"covers":[140],"49":[141],"states":[142],"United":[144],"States,":[145],"collected":[146],"from":[147],"February":[148],"2016":[149],"June":[151],"2020.":[152],"Our":[153,269],"approach":[154],"deep":[159],"neural":[160],"network":[161],"model":[162,216,222,232,249,284,294],"utilizes":[164],"variety":[166],"characteristics,":[169],"such":[170],"as":[171],"time-sensitive":[172],"weather":[173],"data,":[174],"textual":[175],"information,":[176],"discerning":[178],"factors.":[179],"We":[180,234,288],"tested":[182],"ARIS":[183],"against":[184],"multiple":[185],"baselines":[186],"through":[187],"comprehensive":[189,332],"series":[190],"experiments":[192],"across":[193],"several":[194],"major":[195,274],"cities":[196],"USA,":[198],"noticed":[202],"improvement":[204],"during":[205],"inference":[206,239,297],"especially":[207],"detecting":[209],"classes.":[211],"Additionally,":[212],"make":[214],"our":[215,221,326],"edge-implementable":[217],"compressed":[220],"using":[223],"joint":[225],"technique":[226],"magnitude-based":[228],"weight":[229],"pruning":[230],"quantization.":[233],"also":[236],"demonstrated":[237],"results":[240],"along":[241],"power":[243],"consumption":[244],"profiling":[245],"after":[246,283],"deploying":[247],"resource":[252],"constrained":[253],"environment":[254],"consists":[256],"Intel":[258],"Neural":[259],"Compute":[260],"Stick":[261],"2":[262],"(NCS2)":[263],"Raspberry":[265],"Pi":[266],"4B":[267],"(RPi4).":[268],"investigation":[270],"observations":[272],"indicate":[273],"improvements":[275],"predict":[277],"unusual":[278],"event":[281],"even":[282],"compression":[285],"deployment.":[287],"managed":[290],"reduce":[292],"size":[295],"time":[298],"by":[299],"\u2248":[300,303],"6x,":[301],"70":[304],"%":[305],"respectively":[306],"insignificant":[308],"drop":[309],"performance.":[311],"Furthermore,":[312],"understand":[315],"importance":[317],"each":[319],"individual":[320],"type":[321],"variables":[323],"used":[324],"analysis,":[327],"showcased":[330],"ablation":[333],"study.":[334]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
