{"id":"https://openalex.org/W3183883603","doi":"https://doi.org/10.1109/metroind4.0iot51437.2021.9488476","title":"Damage Detection in Structural Health Monitoring with Spiking Neural Networks","display_name":"Damage Detection in Structural Health Monitoring with Spiking Neural Networks","publication_year":2021,"publication_date":"2021-06-07","ids":{"openalex":"https://openalex.org/W3183883603","doi":"https://doi.org/10.1109/metroind4.0iot51437.2021.9488476","mag":"3183883603"},"language":"en","primary_location":{"id":"doi:10.1109/metroind4.0iot51437.2021.9488476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/metroind4.0iot51437.2021.9488476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5081317256","display_name":"Luca Zanatta","orcid":"https://orcid.org/0000-0002-4654-4690"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Zanatta","raw_affiliation_strings":["DEI Universit\u00e0 di Bologna, Bologna, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DEI Universit\u00e0 di Bologna, Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022195134","display_name":"Francesco Barchi","orcid":"https://orcid.org/0000-0001-5155-6883"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Barchi","raw_affiliation_strings":["DEI Universit\u00e0 di Bologna, Bologna, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DEI Universit\u00e0 di Bologna, Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032095821","display_name":"Alessio Burrello","orcid":"https://orcid.org/0000-0002-6215-8220"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessio Burrello","raw_affiliation_strings":["DEI Universit\u00e0 di Bologna, Bologna, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DEI Universit\u00e0 di Bologna, Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047906923","display_name":"Andrea Bartolini","orcid":"https://orcid.org/0000-0002-1148-2450"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Bartolini","raw_affiliation_strings":["DEI Universit\u00e0 di Bologna, Bologna, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DEI Universit\u00e0 di Bologna, Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030075617","display_name":"Davide Brunelli","orcid":"https://orcid.org/0000-0001-5110-6823"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Davide Brunelli","raw_affiliation_strings":["DII Universit\u00e0 di Trento, Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DII Universit\u00e0 di Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031653904","display_name":"Andrea Acquaviva","orcid":"https://orcid.org/0000-0002-7323-759X"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Acquaviva","raw_affiliation_strings":["DEI Universit\u00e0 di Bologna, Bologna, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DEI Universit\u00e0 di Bologna, Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2508,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.93014419,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"105","last_page":"110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9994000196456909,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/computer-science","display_name":"Computer science","score":0.7811428308486938},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.7740173935890198},{"id":"https://openalex.org/keywords/structural-health-monitoring","display_name":"Structural health monitoring","score":0.7425895929336548},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6721779108047485},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.6144769191741943},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5633859634399414},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5470252633094788},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.537617027759552},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5338616967201233},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.493868887424469},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.45287594199180603},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4330231249332428},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14484775066375732}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7811428308486938},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.7740173935890198},{"id":"https://openalex.org/C2776247918","wikidata":"https://www.wikidata.org/wiki/Q1423713","display_name":"Structural health monitoring","level":2,"score":0.7425895929336548},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6721779108047485},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.6144769191741943},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5633859634399414},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5470252633094788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.537617027759552},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5338616967201233},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.493868887424469},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45287594199180603},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4330231249332428},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14484775066375732},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/metroind4.0iot51437.2021.9488476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/metroind4.0iot51437.2021.9488476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)","raw_type":"proceedings-article"},{"id":"pmh:oai:cris.unibo.it:11585/862684","is_oa":false,"landing_page_url":"http://hdl.handle.net/11585/862684","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"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":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:iris.unitn.it:11572/314764","is_oa":false,"landing_page_url":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9488476","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"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":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W59997565","https://openalex.org/W101771737","https://openalex.org/W1582368210","https://openalex.org/W2006370340","https://openalex.org/W2037660732","https://openalex.org/W2051230740","https://openalex.org/W2107994122","https://openalex.org/W2130360162","https://openalex.org/W2480038822","https://openalex.org/W2524099095","https://openalex.org/W2552999262","https://openalex.org/W2569813014","https://openalex.org/W2749476078","https://openalex.org/W2758564008","https://openalex.org/W2783525259","https://openalex.org/W2798878556","https://openalex.org/W2902164950","https://openalex.org/W2924059947","https://openalex.org/W2943780481","https://openalex.org/W2944996566","https://openalex.org/W3039105774","https://openalex.org/W3043133474","https://openalex.org/W3084020652"],"related_works":["https://openalex.org/W2765080098","https://openalex.org/W2385749422","https://openalex.org/W2009888974","https://openalex.org/W2355290145","https://openalex.org/W2353465659","https://openalex.org/W3023105672","https://openalex.org/W2355539379","https://openalex.org/W4231410700","https://openalex.org/W4237770763","https://openalex.org/W4386041242"],"abstract_inverted_index":{"Structural":[0],"Health":[1],"Monitoring":[2],"(SHM)":[3],"is":[4,134],"an":[5,142],"evolving":[6],"research":[7,15],"field":[8,18],"involving":[9],"internet-of-things":[10],"and":[11,32,77,112],"machine-learning":[12],"technologies.":[13],"Recent":[14],"in":[16,61,92,135],"this":[17,40,149],"demonstrated":[19],"the":[20,28,106,160],"effectiveness":[21],"of":[22,30,95,108],"low-cost":[23],"MEMS":[24,55],"accelerometers":[25],"to":[26,54,57,146],"monitor":[27],"vibrations":[29],"buildings,":[31],"neural":[33,120],"networks":[34],"analyse":[35],"generated":[36],"data":[37,56],"streams.":[38],"In":[39,83],"work,":[41],"we":[42,113,151],"propose":[43],"a":[44,62,100,132,136,153],"novel":[45],"SHM":[46,176],"approach":[47],"using":[48],"Spiking":[49],"Neural":[50],"Networks":[51],"(SNNs)":[52],"applied":[53],"detect":[58],"infrastructural":[59],"damages":[60],"motorway":[63],"bridge.":[64],"SNNs":[65],"are":[66,71,89,172],"brain-inspired":[67],"network":[68,121],"models":[69],"that":[70,126,158,169],"promising":[72],"as":[73],"being":[74],"more":[75],"compact":[76],"potentially":[78],"energy-efficient":[79],"than":[80],"traditional":[81],"networks.":[82],"particular,":[84],"Long":[85],"Short-Term":[86],"SNN":[87,127],"(LSNN)":[88],"very":[90],"effective":[91],"analysing":[93],"streams":[94],"data,":[96],"but":[97],"they":[98],"require":[99],"nontrivial":[101],"learning":[102],"process.":[103],"We":[104,124,166],"study":[105],"feasibility":[107],"LSNNs":[109],"for":[110],"SHM,":[111],"compare":[114],"their":[115],"accuracy":[116,143],"with":[117,141,174],"alternative":[118],"artificial":[119],"(ANN)":[122],"models.":[123],"demonstrate":[125],"can":[128],"effectively":[129],"discriminate":[130],"whether":[131],"structure":[133],"healthy":[137],"or":[138],"damaged":[139],"condition":[140],"level":[144],"similar":[145],"ANN.":[147],"To":[148],"purpose,":[150],"exploited":[152],"state-of-the-art":[154],"fast":[155],"training":[156],"algorithm":[157],"approximates":[159],"Back":[161],"Propagation":[162],"Through":[163],"Time":[164],"(BPTT).":[165],"also":[167],"show":[168],"inference":[170],"times":[171],"compliant":[173],"real-time":[175],"requirements.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-09-03T10:48:47.769340","created_date":"2025-10-10T00:00:00"}