{"id":"https://openalex.org/W7225824335","doi":"https://doi.org/10.3390/s26227120","title":"An AI-Driven Federated Framework for Distributed Multimodal Sensing with Implications for Loan Risk Prediction","display_name":"An AI-Driven Federated Framework for Distributed Multimodal Sensing with Implications for Loan Risk Prediction","publication_year":2026,"publication_date":"2026-11-11","ids":{"openalex":"https://openalex.org/W7225824335","doi":"https://doi.org/10.3390/s26227120"},"language":"en","primary_location":{"id":"doi:10.3390/s26227120","doi":"https://doi.org/10.3390/s26227120","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26227120","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/s26227120","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5151627997","display_name":"Xutong Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xutong Wang","raw_affiliation_strings":["China Agricultural University, Beijing 100083, China","Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143874694","display_name":"Haoting Shi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoting Shi","raw_affiliation_strings":["Central University of Finance and Economics, Beijing 100081, China","Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central University of Finance and Economics, Beijing 100081, China","institution_ids":["https://openalex.org/I137867983"]},{"raw_affiliation_string":"Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133306307","display_name":"Wei Hong","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Hong","raw_affiliation_strings":["Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001454333","display_name":"Ruiqi Wu","orcid":"https://orcid.org/0009-0008-8175-9997","observed_orcids":["https://orcid.org/0009-0008-8175-9997"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiqi Wu","raw_affiliation_strings":["China Agricultural University, Beijing 100083, China","Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319947","display_name":"Xinyue Zhang","orcid":"https://orcid.org/0000-0001-7623-731X","observed_orcids":["https://orcid.org/0000-0001-7623-731X"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyue Zhang","raw_affiliation_strings":["China Agricultural University, Beijing 100083, China","Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144134584","display_name":"Wenjie Lu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Lu","raw_affiliation_strings":["China Agricultural University, Beijing 100083, China","Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049189767","display_name":"Yihong Song","orcid":"https://orcid.org/0009-0008-0127-0228","observed_orcids":["https://orcid.org/0009-0008-0127-0228"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yihong Song","raw_affiliation_strings":["China Agricultural University, Beijing 100083, China","Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049189767"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I52158045"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"22","first_page":"7120","last_page":"7120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.0007999999797903001,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5893999934196472},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5831999778747559},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5468000173568726},{"id":"https://openalex.org/C15430695","wikidata":"https://www.wikidata.org/wiki/Q11157999","display_name":"Gross margin","level":3,"score":0.5056999921798706},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4535999894142151},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41200000047683716},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4099000096321106},{"id":"https://openalex.org/C128383755","wikidata":"https://www.wikidata.org/wiki/Q3816336","display_name":"Agricultural productivity","level":3,"score":0.4072999954223633},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4043000042438507},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.4034000039100647},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.3797000050544739},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34220001101493835},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.33410000801086426},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C32198211","wikidata":"https://www.wikidata.org/wiki/Q165044","display_name":"Greenhouse","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C2777764128","wikidata":"https://www.wikidata.org/wiki/Q189539","display_name":"Loan","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C182299520","wikidata":"https://www.wikidata.org/wiki/Q1289588","display_name":"Total cost","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.2718999981880188},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.26919999718666077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/s26227120","doi":"https://doi.org/10.3390/s26227120","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26227120","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/s26227120","doi":"https://doi.org/10.3390/s26227120","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26227120","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Distributed":[0],"multimodal":[1],"sensor":[2],"networks":[3],"support":[4],"agricultural":[5,257],"monitoring":[6],"and":[7,18,21,27,66,70,91,108,124,148,195,220,225],"decision-making,":[8],"but":[9],"sensing":[10,42],"nodes":[11],"differ":[12],"in":[13,143,230],"data":[14,23],"structure,":[15],"sampling":[16],"strategy,":[17],"environmental":[19,57],"distribution,":[20],"centralized":[22],"pooling":[24],"raises":[25],"privacy":[26],"bandwidth":[28],"concerns.":[29],"We":[30],"propose":[31],"a":[32,131,152,172,179,187],"Federated":[33],"Multimodal":[34,52],"Sensor":[35,53],"Decision":[36],"Network":[37],"(FMSD-Net)":[38],"that":[39],"links":[40],"multisource":[41],"to":[43,130,205,256],"net-return":[44],"prediction":[45],"across":[46],"distributed":[47],"production":[48,105,117],"sites.":[49],"A":[50,77,94,244],"Heterogeneous":[51],"Encoder":[54],"(HMSE)":[55],"encodes":[56],"time":[58],"series,":[59],"soil":[60],"measurements,":[61],"red\u2013green\u2013blue":[62],"(RGB)":[63],"canopy":[64],"images,":[65],"structured":[67],"management":[68],"variables":[69],"fuses":[71],"them":[72],"with":[73,238],"cross-modal":[74],"multi-head":[75],"attention.":[76],"non-IID-aware":[78],"federated":[79,208],"aggregation":[80],"(NFA)":[81],"rule":[82],"weights":[83],"client":[84],"updates":[85],"by":[86,155,202],"distribution":[87],"shift,":[88],"update-direction":[89],"consistency,":[90],"node":[92],"reliability.":[93],"Sensor-to-Decision":[95],"Prediction":[96],"Module":[97],"(SDPM)":[98],"jointly":[99],"predicts":[100],"crop":[101],"yield":[102],"(t/ha),":[103],"recorded":[104,116],"cost":[106,118],"(103RMB/ha),":[107,119],"net":[109],"return,":[110],"defined":[111],"as":[112],"gross":[113],"revenue":[114],"minus":[115],"under":[120],"an":[121,196,216,221],"accounting-consistency":[122],"constraint,":[123],"maps":[125],"the":[126,165,206,227],"predicted":[127],"return-on-cost":[128],"margin":[129],"rule-based":[132],"decision":[133],"score.":[134],"FMSD-Net":[135,170],"was":[136],"evaluated":[137],"on":[138],"three":[139],"greenhouse":[140],"tomato":[141],"sites":[142],"Changping":[144],"(Beijing),":[145],"Baoding":[146],"(Hebei),":[147],"Weifang":[149],"(Shandong)":[150],"using":[151],"chronological":[153],"split":[154],"growing":[156],"season":[157],"(2022":[158],"training,":[159],"2023":[160],"validation,":[161],"2024":[162,167],"testing).":[163],"On":[164],"pooled":[166],"test":[168],"set,":[169],"achieves":[171,215],"Mean":[173,181,188],"Absolute":[174,189],"Error":[175,183,191],"(MAE)":[176],"of":[177,185,193,198,218,223,241],"5.21\u00d7103RMB/ha,":[178],"Root":[180],"Squared":[182],"(RMSE)":[184],"7.36\u00d7103RMB/ha,":[186],"Percentage":[190],"(MAPE)":[192],"8.12%,":[194],"R2":[197,222],"0.927,":[199],"reducing":[200],"MAE":[201,217],"5.1%":[203],"relative":[204],"strongest":[207],"baseline,":[209],"FedAWA.":[210],"Under":[211],"client-local":[212],"evaluation,":[213],"it":[214],"5.38\u00d7103RMB/ha":[219],"0.923":[224],"reaches":[226],"convergence":[228],"criterion":[229],"56":[231],"communication":[232],"rounds,":[233],"8.2%":[234],"fewer":[235],"than":[236],"FedAWA,":[237],"4.97":[239],"GB":[240],"total":[242],"communication.":[243],"separate":[245],"farmer\u2013year":[246],"loan":[247],"panel":[248],"provides":[249],"complementary":[250],"econometric":[251],"evidence":[252],"linking":[253],"climate":[254],"exposure":[255],"credit":[258],"risk.":[259]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2026-11-12T00:00:00"}
