{"id":"https://openalex.org/W2163063485","doi":null,"title":"Autonomous Accident Monitoring Using Cellular Network Data","display_name":"Autonomous Accident Monitoring Using Cellular Network Data","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2163063485","mag":"2163063485"},"language":"en","primary_location":{"id":"pmh:oai:DiVA.org:ri-24157","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-24157","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I86987016","host_organization_name":"KTH Royal Institute of Technology","host_organization_lineage":["https://openalex.org/I86987016"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-24157","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041638453","display_name":"Olof G\u00f6rnerup","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Olof G\u00f6rnerup","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064297162","display_name":"Per Kreuger","orcid":"https://orcid.org/0000-0002-9331-0352","observed_orcids":["https://orcid.org/0000-0002-9331-0352"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Per Kreuger","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-9331-0352","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068280922","display_name":"Daniel Gillblad","orcid":"https://orcid.org/0000-0001-8952-3542","observed_orcids":["https://orcid.org/0000-0001-8952-3542"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniel Gillblad","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8952-3542","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4024,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59253042,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.538100004196167,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.538100004196167,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.26030001044273376,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12406","display_name":"IoT and GPS-based Vehicle Safety Systems","score":0.03929999843239784,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/accident-detection","display_name":"accident detection","score":0.9110000133514404},{"id":"https://openalex.org/keywords/traffic-accidents","display_name":"traffic accidents","score":0.6269999742507935},{"id":"https://openalex.org/keywords/cellular-network-data","display_name":"cellular network data","score":0.8289999961853027},{"id":"https://openalex.org/keywords/movement-patterns","display_name":"movement patterns","score":0.7919999957084656},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"anomaly detection","score":0.5730000138282776},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.8199999928474426},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"traffic congestion","score":0.6499999761581421},{"id":"https://openalex.org/keywords/road-traffic","display_name":"road traffic","score":0.8980000019073486},{"id":"https://openalex.org/keywords/autonomous-monitoring","display_name":"autonomous monitoring","score":0.5690000057220459}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7086209058761597},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.6106346249580383},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5838969945907593},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5698306560516357},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5383772253990173},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5091816782951355},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.44684451818466187},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.43282222747802734},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4256933629512787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30266332626342773},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.17042946815490723},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:DiVA.org:ri-24157","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-24157","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I86987016","host_organization_name":"KTH Royal Institute of Technology","host_organization_lineage":["https://openalex.org/I86987016"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:2163063485","doi":null,"is_oa":false,"landing_page_url":"https://dblp.uni-trier.de/db/conf/iscram/iscram2013.html#GornerupKG13","pdf_url":null,"source":{"id":"https://openalex.org/S4306419567","display_name":"International Conference on Information Systems for Crisis Response and Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Information Systems for Crisis Response and Management","raw_type":null}],"best_oa_location":{"id":"pmh:oai:DiVA.org:ri-24157","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-24157","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I86987016","host_organization_name":"KTH Royal Institute of Technology","host_organization_lineage":["https://openalex.org/I86987016"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7250000238418579,"id":"https://metadata.un.org/sdg/11"},{"display_name":"Industry, innovation and infrastructure","score":0.710099995136261,"id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W115644601","https://openalex.org/W129089342","https://openalex.org/W190212514","https://openalex.org/W1717968314","https://openalex.org/W1809001740","https://openalex.org/W1974331052","https://openalex.org/W2006820335","https://openalex.org/W2012998331","https://openalex.org/W2057301737","https://openalex.org/W2081739988","https://openalex.org/W2092867892","https://openalex.org/W2105907431","https://openalex.org/W2108432893","https://openalex.org/W2119792344","https://openalex.org/W2142960677","https://openalex.org/W2150370883","https://openalex.org/W2164466012","https://openalex.org/W2170535121","https://openalex.org/W2171128079"],"related_works":["https://openalex.org/W577486822","https://openalex.org/W2090650314","https://openalex.org/W7217261434","https://openalex.org/W2146499293","https://openalex.org/W7096832495","https://openalex.org/W1994808655","https://openalex.org/W2409573987","https://openalex.org/W2922807099","https://openalex.org/W1990857300","https://openalex.org/W2115972319"],"abstract_inverted_index":{"Mobile":[0],"communication":[1],"networks":[2,6],"constitute":[3],"large-scale":[4],"sensor":[5],"that":[7,13,49,119],"generate":[8],"huge":[9],"amounts":[10],"of":[11,65],"data":[12],"can":[14,122],"be":[15],"refined":[16],"into":[17],"collective":[18],"mobility":[19,76],"patterns.":[20],"In":[21],"this":[22,66,109],"paper":[23],"we":[24,107,117],"propose":[25],"a":[26,47,105,112],"method":[27,93,121],"for":[28],"using":[29,68],"these":[30,128],"patterns":[31,77],"to":[32,45,97,99],"autonomously":[33],"monitor":[34],"and":[35,38,62,71,85,126],"detect":[36,123],"accidents":[37,125],"other":[39],"critical":[40],"events.":[41],"The":[42],"approach":[43,110],"is":[44,50,94],"identify":[46,72],"measure":[48,67],"approximately":[51],"time-invariant":[52],"on":[53],"short":[54,61,84],"time-scales":[55],"under":[56],"regular":[57,130],"conditions,":[58],"estimate":[59],"the":[60,80,83,92,120],"long-term":[63,86,90,100],"dynamics":[64],"Bayesian":[69],"inference,":[70],"sudden":[73],"shifts":[74],"in":[75,102,111],"by":[78],"monitoring":[79],"divergence":[81],"between":[82],"estimates.":[87],"By":[88],"estimating":[89],"dynamics,":[91],"also":[95],"able":[96],"adapt":[98],"trends":[101],"data.":[103],"As":[104],"proof-of-concept,":[106],"apply":[108],"vehicular":[113],"traffic":[114,124,134],"scenario,":[115],"where":[116],"demonstrate":[118],"distinguish":[127],"from":[129],"events,":[131],"such":[132],"as":[133],"congestions.":[135]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2026-10-29T09:56:32.521200","created_date":"2016-06-24T00:00:00"}