{"id":"https://openalex.org/W2519933381","doi":"https://doi.org/10.1109/cscwd.2016.7566051","title":"Behavior prediction using an improved Hidden Markov Model to support people with disabilities in smart homes","display_name":"Behavior prediction using an improved Hidden Markov Model to support people with disabilities in smart homes","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2519933381","doi":"https://doi.org/10.1109/cscwd.2016.7566051","mag":"2519933381"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd.2016.7566051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd.2016.7566051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","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/A5035892352","display_name":"Eying Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Eying Wu","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084276524","display_name":"Peng Zhang","orcid":"https://orcid.org/0000-0002-6417-9375"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004237040","display_name":"Tun Lu","orcid":"https://orcid.org/0000-0002-6633-4826"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tun Lu","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071156485","display_name":"Hansu Gu","orcid":"https://orcid.org/0000-0002-1426-3210"},"institutions":[{"id":"https://openalex.org/I131787340","display_name":"Seagate (United States)","ror":"https://ror.org/04p1xtv71","country_code":"US","type":"company","lineage":["https://openalex.org/I131787340"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hansu Gu","raw_affiliation_strings":["Seagate Technology, Longmont, Colorado, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seagate Technology, Longmont, Colorado, USA","institution_ids":["https://openalex.org/I131787340"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091087409","display_name":"Ning Gu","orcid":"https://orcid.org/0000-0002-2915-974X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Gu","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"560","last_page":"565"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9994999766349792,"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.996999979019165,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6627295017242432},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6435668468475342},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.5038406252861023},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4616900682449341},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4540387988090515},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4202724099159241},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3925301134586334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37553873658180237},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.3221682906150818},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10527843236923218},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08173927664756775}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6627295017242432},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6435668468475342},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.5038406252861023},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4616900682449341},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4540387988090515},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4202724099159241},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3925301134586334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37553873658180237},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.3221682906150818},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10527843236923218},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08173927664756775}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd.2016.7566051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd.2016.7566051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W115396333","https://openalex.org/W1536416207","https://openalex.org/W1549494557","https://openalex.org/W1575431606","https://openalex.org/W1589398210","https://openalex.org/W1908693391","https://openalex.org/W1980070248","https://openalex.org/W2089908638","https://openalex.org/W2105594594","https://openalex.org/W2109606294","https://openalex.org/W2122962140","https://openalex.org/W2125838338","https://openalex.org/W2156324385","https://openalex.org/W2184481373","https://openalex.org/W4251968409"],"related_works":["https://openalex.org/W4313547211","https://openalex.org/W2350115929","https://openalex.org/W2039473210","https://openalex.org/W3129972734","https://openalex.org/W4313547478","https://openalex.org/W2157200163","https://openalex.org/W2131524408","https://openalex.org/W1536753830","https://openalex.org/W2569579427","https://openalex.org/W2793260526"],"abstract_inverted_index":{"Smart":[0],"environment":[1],"has":[2,164],"been":[3],"evolved":[4],"as":[5,115,153],"a":[6,121,141],"hot":[7],"research":[8],"topic":[9],"with":[10,36,84],"the":[11,103,128,135,169,178],"development":[12],"of":[13,92,117,137,145,161],"machine":[14],"learning":[15],"algorithms":[16],"and":[17,41,55,62,94,119,151],"wireless":[18],"communication":[19],"technologies.":[20],"Existing":[21],"smart":[22],"home":[23],"solutions":[24],"usually":[25],"need":[26],"inhabitants":[27,98],"to":[28,43,52,58,77,97,126,133,177],"operate":[29],"device":[30],"controllers":[31],"directly.":[32],"However,":[33],"for":[34,82],"people":[35,83],"disabilities,":[37],"it":[38,49],"is":[39,50,75],"inconvenient":[40],"difficult":[42],"perform":[44],"such":[45],"manual":[46],"operations.":[47],"Therefore,":[48],"important":[51],"develop":[53,120],"automatic":[54],"intelligent":[56],"services":[57,96],"reduce":[59],"operation":[60],"inconvenience":[61],"improve":[63],"comfort":[64],"level.":[65],"In":[66],"this":[67],"paper,":[68],"an":[69],"Improved":[70],"Hidden":[71,108],"Markov":[72,109],"Model":[73],"(IHMM)":[74],"presented":[76],"support":[78],"personalized":[79],"behavior":[80,90],"prediction":[81,170],"disabilities.":[85],"The":[86],"model":[87],"can":[88],"learn":[89],"patterns":[91],"users":[93],"provide":[95],"automatically.":[99],"Moreover,":[100],"by":[101,172],"breaking":[102],"time":[104,113],"invariant":[105],"hypothesis":[106],"in":[107],"Model,":[110],"we":[111],"incorporate":[112],"information":[114],"positions":[116],"states,":[118],"temporal":[122],"state":[123,130,138],"transition":[124,131],"matrix":[125,132],"replace":[127],"fixed":[129],"demonstrate":[134],"probabilities":[136],"transitions.":[139],"As":[140],"result,":[142],"different":[143],"values":[144],"daily":[146],"temperature":[147],"sections":[148],"are":[149],"characterized":[150],"identified":[152],"hidden":[154],"variables,":[155],"which":[156],"guide":[157],"user":[158],"activities.":[159],"Evaluation":[160],"proposed":[162],"work":[163],"shown":[165],"that":[166],"IHMM":[167],"improves":[168],"accuracy":[171],"at":[173],"least":[174],"10%":[175],"compared":[176],"traditional":[179],"HMM.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}