{"id":"https://openalex.org/W4414539626","doi":"https://doi.org/10.1109/icc52391.2025.11161868","title":"Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure","display_name":"Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414539626","doi":"https://doi.org/10.1109/icc52391.2025.11161868"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11161868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5095941275","display_name":"Fatemeh Dehrouyeh","orcid":"https://orcid.org/0009-0003-0350-3009"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Fatemeh Dehrouyeh","raw_affiliation_strings":["University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada"],"affiliations":[{"raw_affiliation_string":"University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036132710","display_name":"Ibrahim Shaer","orcid":"https://orcid.org/0000-0002-2723-4662"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ibrahim Shaer","raw_affiliation_strings":["University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada"],"affiliations":[{"raw_affiliation_string":"University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078998486","display_name":"Soodeh Nikan","orcid":"https://orcid.org/0000-0001-8223-1571"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Soodeh Nikan","raw_affiliation_strings":["University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada"],"affiliations":[{"raw_affiliation_string":"University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051907334","display_name":"Firouz Badrkhani Ajaei","orcid":"https://orcid.org/0000-0002-2635-4128"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Firouz Badrkhani Ajaei","raw_affiliation_strings":["University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada"],"affiliations":[{"raw_affiliation_string":"University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041270670","display_name":"Abdallah Shami","orcid":"https://orcid.org/0000-0003-2887-0350"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Abdallah Shami","raw_affiliation_strings":["University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada"],"affiliations":[{"raw_affiliation_string":"University of Western Ontario,Department of Electrical and Computer Engineering,London,Ontario,Canada","institution_ids":["https://openalex.org/I125749732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5095941275"],"corresponding_institution_ids":["https://openalex.org/I125749732"],"apc_list":null,"apc_paid":null,"fwci":4.1047,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.94451089,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1195","last_page":"1200"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":0.9300000071525574,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10917","display_name":"Smart Grid Security and Resilience","score":0.9300000071525574,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9271000027656555,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.923799991607666,"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/pruning","display_name":"Pruning","score":0.6740999817848206},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.635699987411499},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.617900013923645},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6017000079154968},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5302000045776367},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5156000256538391},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45159998536109924},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4399999976158142}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6740999817848206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6668999791145325},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6647999882698059},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.635699987411499},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.617900013923645},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6017000079154968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.579200029373169},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5302000045776367},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5156000256538391},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45159998536109924},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4399999976158142},{"id":"https://openalex.org/C2776422217","wikidata":"https://www.wikidata.org/wiki/Q13629441","display_name":"Electric vehicle","level":3,"score":0.43389999866485596},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4032999873161316},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.39899998903274536},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.271699994802475},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11161868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,42,104],"growing":[2],"need":[3],"for":[4,28],"real-time":[5],"processing":[6],"on":[7,95],"IoT":[8],"devices,":[9],"optimizing":[10],"machine":[11],"learning":[12],"(ML)":[13],"models'":[14],"size,":[15],"latency,":[16],"and":[17,47,57,74,87,109],"computational":[18,113],"efficiency":[19,114],"is":[20],"essential.":[21],"This":[22],"paper":[23],"investigates":[24],"a":[25,92],"pruning":[26,76,108],"method":[27],"anomaly":[29,118],"detection":[30,119],"in":[31,84,103],"resourceconstrained":[32],"environments,":[33],"specifically":[34],"targeting":[35],"Electric":[36],"Vehicle":[37],"Charging":[38],"Infrastructure":[39],"(EVCI).":[40],"Using":[41],"CICEVSE2024":[43],"dataset,":[44],"we":[45],"trained":[46],"optimized":[48,79],"three":[49],"models\u2014Multi-Layer":[50],"Perceptron":[51],"(MLP),":[52],"Long":[53],"Short-Term":[54],"Memory":[55],"(LSTM),":[56],"XGBoost\u2014through":[58],"hyperparameter":[59],"tuning":[60],"with":[61,90],"Optuna,":[62],"further":[63],"refining":[64],"them":[65],"using":[66],"SHapley":[67],"Additive":[68],"exPlanations":[69],"(SHAP)-based":[70],"feature":[71],"selection":[72],"(FS)":[73],"unstructured":[75],"techniques.":[77],"The":[78],"models":[80],"achieved":[81],"significant":[82],"reductions":[83],"model":[85],"size":[86],"inference":[88],"times,":[89],"only":[91],"marginal":[93],"impact":[94],"their":[96],"performance.":[97],"Notably,":[98],"our":[99],"findings":[100],"indicate":[101],"that,":[102],"context":[105],"of":[106],"EVCI,":[107],"FS":[110],"can":[111],"enhance":[112],"while":[115],"retaining":[116],"critical":[117],"capabilities.":[120]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}