{"id":"https://openalex.org/W3217761989","doi":"https://doi.org/10.1109/ssrr53300.2021.9597688","title":"Selective and Hierarchical Allocation of Sensing Resources for Anomalous Target Identification in Exploratory Missions","display_name":"Selective and Hierarchical Allocation of Sensing Resources for Anomalous Target Identification in Exploratory Missions","publication_year":2021,"publication_date":"2021-10-25","ids":{"openalex":"https://openalex.org/W3217761989","doi":"https://doi.org/10.1109/ssrr53300.2021.9597688","mag":"3217761989"},"language":"en","primary_location":{"id":"doi:10.1109/ssrr53300.2021.9597688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssrr53300.2021.9597688","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)","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/A5046804617","display_name":"Brigid A. Blakeslee","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]},{"id":"https://openalex.org/I1306686416","display_name":"RTX (United States)","ror":"https://ror.org/0354t7b78","country_code":"US","type":"company","lineage":["https://openalex.org/I1306686416"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Brigid A. Blakeslee","raw_affiliation_strings":["New York University, Brooklyn, New York, USA","Raytheon Technologies Research Center, East Hartford, Connecticut, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, New York, USA","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Raytheon Technologies Research Center, East Hartford, Connecticut, USA","institution_ids":["https://openalex.org/I1306686416"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077485450","display_name":"Giuseppe Loianno","orcid":"https://orcid.org/0000-0002-3263-5401"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Giuseppe Loianno","raw_affiliation_strings":["New York University, Brooklyn, New York, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, New York, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046804617"],"corresponding_institution_ids":["https://openalex.org/I1306686416","https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18457863,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"196","last_page":"203"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9970999956130981,"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":0.8057677745819092},{"id":"https://openalex.org/keywords/situation-awareness","display_name":"Situation awareness","score":0.764727771282196},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5739948749542236},{"id":"https://openalex.org/keywords/exploratory-search","display_name":"Exploratory search","score":0.4973302185535431},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.46515804529190063},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4312676787376404},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37454068660736084},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3724372386932373},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23534393310546875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8057677745819092},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.764727771282196},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5739948749542236},{"id":"https://openalex.org/C2777866876","wikidata":"https://www.wikidata.org/wiki/Q5421358","display_name":"Exploratory search","level":2,"score":0.4973302185535431},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.46515804529190063},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4312676787376404},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37454068660736084},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3724372386932373},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23534393310546875},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssrr53300.2021.9597688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssrr53300.2021.9597688","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320307798","display_name":"Nokia","ror":"https://ror.org/04pkc8m17"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2083272983","https://openalex.org/W2095788786","https://openalex.org/W2108825342","https://openalex.org/W2121734178","https://openalex.org/W2139047169","https://openalex.org/W2164716063","https://openalex.org/W2738842532","https://openalex.org/W2912372166","https://openalex.org/W2990375254","https://openalex.org/W3035218572","https://openalex.org/W3041521567","https://openalex.org/W3086406985","https://openalex.org/W3089444735","https://openalex.org/W3096656822","https://openalex.org/W3104218527","https://openalex.org/W3122272697","https://openalex.org/W3122578501","https://openalex.org/W3122721318","https://openalex.org/W3124451778","https://openalex.org/W3124863095","https://openalex.org/W3133663968","https://openalex.org/W3206820044","https://openalex.org/W6678073246","https://openalex.org/W6680614221","https://openalex.org/W6788557108","https://openalex.org/W6788967303","https://openalex.org/W6789177232","https://openalex.org/W6790085167"],"related_works":["https://openalex.org/W2946273706","https://openalex.org/W3024912289","https://openalex.org/W2415747217","https://openalex.org/W2143767096","https://openalex.org/W2561023719","https://openalex.org/W2094708502","https://openalex.org/W1542973883","https://openalex.org/W1590515626","https://openalex.org/W2792418094","https://openalex.org/W2891877740"],"abstract_inverted_index":{"We":[0,111],"present":[1],"an":[2,29],"approach":[3,155],"for":[4,37,101,117],"selective,":[5],"hierarchical":[6],"allocation":[7],"of":[8,52,57,66,77,104,120,146],"sensing":[9,115,137],"resources":[10,116],"that":[11,68,128],"aims":[12],"to":[13,62,162],"maximize":[14],"information":[15,169],"gain":[16,170],"in":[17,28,80,148,164],"exploratory":[18,136],"missions":[19],"such":[20],"as":[21,70,99],"search":[22],"and":[23,92,133,156,171,176],"rescue":[24],"(SAR)":[25],"or":[26,40,108,142],"surveillance":[27,42],"efficient":[30],"manner.":[31],"Specifically,":[32],"we":[33],"propose":[34],"a":[35,53,64,74,105,124],"methodology":[36],"perception-enabled":[38],"SAR":[39,106],"crowd":[41],"driven":[43],"by":[44],"anomaly":[45],"detection":[46],"based":[47],"on":[48],"low-level":[49],"statistical":[50],"assessment":[51],"region.":[54],"The":[55],"characterizations":[56],"previously-observed":[58],"regions":[59,79,84,122],"are":[60,85],"used":[61],"populate":[63],"window":[65],"observations":[67],"serves":[69],"\u201cshort-term":[71],"memory,\u201d":[72],"providing":[73],"contextually-appropriate":[75],"characterization":[76],"proximate":[78],"the":[81,102,153],"scene.":[82],"Currently-observed":[83],"compared":[86],"with":[87,160],"this":[88],"short-term":[89],"memory":[90],"window,":[91],"if":[93],"sufficiently":[94],"dissimilar,":[95],"can":[96],"be":[97],"considered":[98],"candidates":[100],"presence":[103],"target":[107],"unexpected":[109],"event.":[110],"adaptively":[112],"allocate":[113],"additional":[114],"subsequent":[118],"exploration":[119,165],"anomalous":[121],"through":[123],"novel":[125],"utility":[126],"function":[127],"balances":[129],"varied":[130],"mission":[131,174],"objectives":[132],"constraints":[134],"including":[135],"actions,":[138],"maintaining":[139],"situational":[140],"awareness,":[141],"ensuring":[143],"some":[144],"degree":[145],"confidence":[147],"self-localization.":[149],"Simulation":[150],"results":[151],"validate":[152],"proposed":[154],"demonstrate":[157],"its":[158],"benefits":[159],"regards":[161],"efficiency":[163],"while":[166],"maximizing":[167],"potential":[168],"balancing":[172],"other":[173],"requirements":[175],"objectives.":[177]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
