{"id":"https://openalex.org/W3164152285","doi":"https://doi.org/10.1145/3412382.3458267","title":"CSafe","display_name":"CSafe","publication_year":2021,"publication_date":"2021-05-18","ids":{"openalex":"https://openalex.org/W3164152285","doi":"https://doi.org/10.1145/3412382.3458267","mag":"3164152285"},"language":"en","primary_location":{"id":"doi:10.1145/3412382.3458267","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3412382.3458267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021)","raw_type":"proceedings-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/A5051730108","display_name":"Stephen Xia","orcid":"https://orcid.org/0000-0001-5713-8885"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Stephen Xia","raw_affiliation_strings":["Columbia University, New York, New York, USA"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082699365","display_name":"Jingping Nie","orcid":"https://orcid.org/0000-0002-9181-8398"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingping Nie","raw_affiliation_strings":["Columbia University, New York, New York, USA"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063824268","display_name":"Xiaofan Jiang","orcid":"https://orcid.org/0000-0002-6480-0299"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaofan Jiang","raw_affiliation_strings":["Columbia University, New York, New York, USA"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051730108"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":2.8949,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.91555105,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"207","last_page":"221"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7511528730392456},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6349447965621948},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5726126432418823},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5376656651496887},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5364686846733093},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.5129608511924744},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.45302459597587585},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.4228513836860657},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.41424474120140076},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3690543472766876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32991504669189453},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1626267433166504},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.1305849850177765},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10091304779052734},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09746938943862915}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7511528730392456},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6349447965621948},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5726126432418823},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5376656651496887},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5364686846733093},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.5129608511924744},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.45302459597587585},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.4228513836860657},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.41424474120140076},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3690543472766876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32991504669189453},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1626267433166504},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.1305849850177765},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10091304779052734},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09746938943862915},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3412382.3458267","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3412382.3458267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G3115684587","display_name":null,"funder_award_id":"CNS-1704899,CNS-1815274,CNS-1943396,CNS-1837022","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W76597279","https://openalex.org/W141203745","https://openalex.org/W184698282","https://openalex.org/W1521758934","https://openalex.org/W1979202021","https://openalex.org/W1989876652","https://openalex.org/W1990408204","https://openalex.org/W2020074877","https://openalex.org/W2026034143","https://openalex.org/W2076145524","https://openalex.org/W2090340221","https://openalex.org/W2093010905","https://openalex.org/W2101609516","https://openalex.org/W2103279261","https://openalex.org/W2123649031","https://openalex.org/W2128131274","https://openalex.org/W2134807719","https://openalex.org/W2138467340","https://openalex.org/W2144244295","https://openalex.org/W2146544734","https://openalex.org/W2157738829","https://openalex.org/W2166389247","https://openalex.org/W2168088676","https://openalex.org/W2512029490","https://openalex.org/W2546814437","https://openalex.org/W2593116425","https://openalex.org/W2606707955","https://openalex.org/W2656075374","https://openalex.org/W2753969197","https://openalex.org/W2765748284","https://openalex.org/W2802577220","https://openalex.org/W2806568678","https://openalex.org/W2914314083","https://openalex.org/W2920981254","https://openalex.org/W2963751183","https://openalex.org/W3012345026","https://openalex.org/W3096282833","https://openalex.org/W6632323398","https://openalex.org/W6750651704"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2101960027","https://openalex.org/W2197846993","https://openalex.org/W1976827262","https://openalex.org/W49697837","https://openalex.org/W3122828758","https://openalex.org/W2170799233","https://openalex.org/W2768112316","https://openalex.org/W4205958986"],"abstract_inverted_index":{"Vehicle":[0],"accidents":[1],"are":[2],"one":[3],"of":[4,8,65,73,78,155],"the":[5,63,190],"greatest":[6],"cause":[7],"death":[9],"and":[10,18,35,83,143,150,169,185],"injury":[11],"in":[12,61,175],"urban":[13,57],"areas":[14],"for":[15],"pedestrians,":[16],"workers,":[17],"police":[19],"alike.":[20],"In":[21],"this":[22],"work,":[23],"we":[24,91],"present":[25],"CSafe,":[26],"a":[27,50,93,107,153,170],"low":[28],"power":[29],"audio-wearable":[30],"platform":[31],"that":[32,62,77,123,158],"detects,":[33],"localizes,":[34],"provides":[36],"alerts":[37],"about":[38],"oncoming":[39],"vehicles":[40],"to":[41,71,112,132,163],"improve":[42,127],"construction":[43,66,115,178],"worker":[44,47],"safety.":[45],"Construction":[46],"safety":[48,60,194],"is":[49,182],"much":[51],"more":[52],"challenging":[53],"problem":[54],"than":[55,76,189],"general":[56],"or":[58],"pedestrian":[59],"sound":[64,95],"tools":[67],"can":[68,126,160],"be":[69],"up":[70,131,162],"orders":[72],"magnitude":[74],"greater":[75],"vehicles,":[79],"making":[80],"vehicle":[81,128,166],"detection":[82,129,167],"localization":[84,173],"exceptionally":[85],"difficult.":[86],"To":[87],"overcome":[88],"these":[89],"challenges,":[90],"develop":[92],"novel":[94,108],"source":[96,137],"separation":[97,138],"algorithm,":[98],"called":[99],"Probabilistic":[100],"Template":[101],"Matching":[102],"(PTM),":[103],"as":[104,106],"well":[105],"noise":[109,145],"filtering":[110,146],"architecture":[111,125,147],"remove":[113],"loud":[114],"noises":[116],"from":[117],"our":[118,124,144],"observed":[119],"signals.":[120],"We":[121,140],"show":[122,151],"by":[130],"12%":[133],"over":[134],"other":[135],"state-of-art":[136,191],"algorithms.":[139],"integrate":[141],"PTM":[142],"into":[148],"CSafe":[149,159],"through":[152],"series":[154],"real-world":[156],"experiments":[157],"achieve":[161],"an":[164],"82%":[165],"rate":[168],"6.90\u00b0":[171],"mean":[172],"error":[174],"acoustically":[176],"noisy":[177],"site":[179],"scenarios,":[180],"which":[181],"16%":[183],"higher":[184],"almost":[186],"30\u00b0":[187],"lower":[188],"audio":[192],"wearable":[193],"works.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2021-06-07T00:00:00"}