{"id":"https://openalex.org/W7129243841","doi":"https://doi.org/10.1109/access.2026.3665786","title":"MobileNet-Lite-Health: A Sustainable Edge AI Framework for Medical Image Classification and Carbon-Aware Computing","display_name":"MobileNet-Lite-Health: A Sustainable Edge AI Framework for Medical Image Classification and Carbon-Aware Computing","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7129243841","doi":"https://doi.org/10.1109/access.2026.3665786"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3665786","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3665786","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3665786","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045152639","display_name":"Faheem Shaukat","orcid":null},"institutions":[{"id":"https://openalex.org/I188771183","display_name":"Iqra University","ror":"https://ror.org/00thhhw55","country_code":"PK","type":"education","lineage":["https://openalex.org/I188771183"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Faheem Shaukat","raw_affiliation_strings":["Department of Computing and Technology, IQRA University, Islamabad Campus, Islamabad, Pakistan"],"raw_orcid":"https://orcid.org/0009-0001-9842-3380","affiliations":[{"raw_affiliation_string":"Department of Computing and Technology, IQRA University, Islamabad Campus, Islamabad, Pakistan","institution_ids":["https://openalex.org/I188771183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121900969","display_name":"Khadija Parwez","orcid":null},"institutions":[{"id":"https://openalex.org/I188771183","display_name":"Iqra University","ror":"https://ror.org/00thhhw55","country_code":"PK","type":"education","lineage":["https://openalex.org/I188771183"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Khadija Parwez","raw_affiliation_strings":["Department of Computing and Technology, IQRA University, Islamabad Campus, Islamabad, Pakistan"],"raw_orcid":"https://orcid.org/0009-0007-6971-8140","affiliations":[{"raw_affiliation_string":"Department of Computing and Technology, IQRA University, Islamabad Campus, Islamabad, Pakistan","institution_ids":["https://openalex.org/I188771183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126214876","display_name":"Zeeshan Ashraf","orcid":null},"institutions":[{"id":"https://openalex.org/I165232561","display_name":"Asian University","ror":"https://ror.org/04hah6r58","country_code":"TH","type":"education","lineage":["https://openalex.org/I165232561"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Zeeshan Ashraf","raw_affiliation_strings":["Department of Computer Science, Grand Asian University, Sialkot, Pakistan"],"raw_orcid":"https://orcid.org/0000-0002-2700-5982","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Grand Asian University, Sialkot, Pakistan","institution_ids":["https://openalex.org/I165232561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110470154","display_name":"Abdullah Alhabeeb","orcid":null},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Abdullah Alhabeeb","raw_affiliation_strings":["Department of Information Science, King Saud University, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0003-0188-3549","affiliations":[{"raw_affiliation_string":"Department of Information Science, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015428357","display_name":"Faiz Abdullah Alotaibi","orcid":"https://orcid.org/0009-0007-1908-4928"},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Faiz Abdullah Alotaibi","raw_affiliation_strings":["Department of Information Science, College of Humanities and Social Sciences, King Saud University, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0009-0007-1908-4928","affiliations":[{"raw_affiliation_string":"Department of Information Science, College of Humanities and Social Sciences, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]},{"author_position":"last","author":{"id":null,"display_name":"Mrim M. Alnfiai","orcid":"https://orcid.org/0000-0003-3837-6313"},"institutions":[{"id":"https://openalex.org/I179331831","display_name":"Taif University","ror":"https://ror.org/014g1a453","country_code":"SA","type":"education","lineage":["https://openalex.org/I179331831"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mrim M. Alnfiai","raw_affiliation_strings":["Department of Information Technology, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0003-3837-6313","affiliations":[{"raw_affiliation_string":"Department of Information Technology, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia","institution_ids":["https://openalex.org/I179331831"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18978646,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"29306","last_page":"29319"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.3935000002384186,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.3935000002384186,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.19539999961853027,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T13702","display_name":"Machine Learning in Healthcare","score":0.02590000070631504,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6291999816894531},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5878999829292297},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.5680999755859375},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5472999811172485},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5080999732017517},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48899999260902405},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4691999852657318},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.4528000056743622},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.44530001282691956},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4221999943256378}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.830299973487854},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6291999816894531},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5878999829292297},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.5680999755859375},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5472999811172485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5412999987602234},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5080999732017517},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48899999260902405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47110000252723694},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4691999852657318},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.4528000056743622},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.44530001282691956},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4221999943256378},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.39959999918937683},{"id":"https://openalex.org/C75027835","wikidata":"https://www.wikidata.org/wiki/Q1064746","display_name":"Green computing","level":3,"score":0.3977000117301941},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.391400009393692},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.38659998774528503},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.35260000824928284},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.3424000144004822},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C2780936489","wikidata":"https://www.wikidata.org/wiki/Q310667","display_name":"Carbon footprint","level":3,"score":0.29019999504089355},{"id":"https://openalex.org/C46743427","wikidata":"https://www.wikidata.org/wiki/Q1341685","display_name":"Inference engine","level":3,"score":0.2892000079154968},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.273499995470047},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26669999957084656},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26159998774528503},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.257099986076355},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2567000091075897},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2524999976158142},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.25130000710487366},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3665786","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3665786","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3665786","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3665786","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.43079206347465515,"display_name":"Responsible consumption and production","id":"https://metadata.un.org/sdg/12"}],"awards":[{"id":"https://openalex.org/G5049684883","display_name":null,"funder_award_id":"TU-DSPP-2026-41","funder_id":"https://openalex.org/F4320323722","funder_display_name":"Taif University"},{"id":"https://openalex.org/G6295220511","display_name":null,"funder_award_id":"(TU-DSPP-2024-41)","funder_id":"https://openalex.org/F4320323722","funder_display_name":"Taif University"}],"funders":[{"id":"https://openalex.org/F4320323722","display_name":"Taif University","ror":"https://ror.org/014g1a453"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2],"transformed":[3],"medical":[4,83],"image":[5],"analysis,":[6],"achieving":[7],"high":[8],"accuracy":[9,144,186],"in":[10,46,53,213],"classification,":[11],"segmentation,":[12],"and":[13,19,32,78,92,97,114,129,135,146,173,189,198,220],"diagnosis.":[14],"However,":[15],"the":[16,121],"substantial":[17],"computational":[18],"energy":[20,133],"demands":[21],"of":[22],"advanced":[23],"models,":[24],"such":[25],"as":[26,164],"large":[27],"convolutional":[28],"neural":[29],"networks":[30],"(CNNs)":[31],"multimodal":[33],"vision-language":[34],"systems,":[35],"hinder":[36],"their":[37],"deployment":[38],"on":[39,88,118,187,191],"resource-constrained":[40],"edge":[41,177,207],"devices":[42,119],"like":[43,120,171],"smartphones,":[44],"especially":[45],"mobile":[47],"health.":[48],"This":[49,65,203],"challenge":[50],"is":[51],"critical":[52],"low-resource,":[54],"bandwidth-limited":[55],"settings":[56],"with":[57,127,141,184],"limited":[58],"high-performance":[59],"computing":[60],"access,":[61],"exacerbating":[62],"healthcare":[63,212],"disparities.":[64],"paper":[66],"introduces":[67],"MobileNet-Lite-Health":[68],"(MLH),":[69],"a":[70,105,142,165],"lightweight":[71],"CNN":[72],"framework":[73],"optimized":[74],"via":[75],"quantization,":[76],"pruning,":[77],"knowledge":[79],"distillation":[80],"for":[81,111,159,176],"sustainable":[82],"imaging":[84],"inference.We":[85],"assess":[86],"MLH":[87,162],"MedMNIST":[89],"(PathMNIST":[90],"subset)":[91],"HAM10000":[93],"datasets,":[94],"representing":[95],"benchmark":[96],"clinical":[98],"contexts,":[99],"respectively.":[100],"Key":[101],"contributions":[102],"include:":[103],"(1)":[104],"carbon-aware":[106,206],"evaluation":[107],"pipeline":[108],"integrating":[109],"CodeCarbon":[110],"CO2":[112,137,155],"tracking":[113],"real-time":[115],"battery":[116],"profiling":[117],"Google":[122],"Pixel":[123],"6;":[124],"(2)":[125],"comparisons":[126],"ResNet-18":[128],"MobileNetV2,":[130],"showing":[131],"74%":[132],"reduction":[134],"76%":[136],"decrease":[138],"per":[139,157],"inference":[140],"2%":[143],"drop;":[145],"(3)":[147],"scaling":[148],"simulations":[149],"projecting":[150],"approximately":[151],"1.1":[152],"g":[153],"annual":[154],"savings":[156],"clinic":[158],"50,000":[160],"screenings.":[161],"serves":[163],"green":[166],"alternative":[167],"to":[168],"energy-intensive":[169],"models":[170],"GPT-4V":[172],"MedPaLM,":[174],"unsuitable":[175],"use.":[178],"Experimental":[179],"results":[180],"confirm":[181],"MLH\u2019s":[182],"effectiveness,":[183],"84.7%":[185],"PathMNIST":[188],"80.1%":[190],"HAM10000,":[192],"plus":[193],"low":[194],"latency":[195],"(65":[196],"ms)":[197],"memory":[199],"use":[200],"(95":[201],"MB).":[202],"work":[204],"pioneers":[205],"AI,":[208],"promoting":[209],"sustainable,":[210],"accessible":[211],"resource-scarce":[214],"environments":[215],"by":[216],"balancing":[217],"efficiency,":[218],"utility,":[219],"environmental":[221],"impact.":[222]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-18T00:00:00"}