Support Vector Machines for Inhabitant Identification in Smart Houses View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010

AUTHORS

Rachid Kadouche , Hélène Pigot , Bessam Abdulrazaka , Sylvain Giroux

ABSTRACT

Authentication is the process by which a user establishes his identification when accessing a service. The use of password to identify the user has been a successful technique in conventional computers. However, in pervasive computing where computing resources exist everywhere, it is necessary to perform user identification through various means. This paper addresses the inhabitant identification issue in smart houses. It studies the optimum time and sensor set required to unobtrusively detect the house occupant. We use a supervised learning approach to address this issue by learning Support Vector Machines classifier (SVM), which predict the users by their daily life habits. We have analyzed the early morning routine with six users. From the very first minute, users can be recognized with an accuracy of more than 85%. Then we have applied an SVM feature selection algorithm to remove noisy and outlier features. Thus, this increases the accuracy to 88% using less then 10 sensors. More... »

PAGES

83-95

References to SciGraph publications

Book

TITLE

Ubiquitous Intelligence and Computing

ISBN

978-3-642-16354-8
978-3-642-16355-5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-16355-5_9

DOI

http://dx.doi.org/10.1007/978-3-642-16355-5_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1047515356


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0806", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information Systems", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Universit\u00e9 de Sherbrooke", 
          "id": "https://www.grid.ac/institutes/grid.86715.3d", 
          "name": [
            "DOMUS Lab, Universit\u00e9 de Sherbrooke, Sherbrooke, Qu\u00e9bec, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kadouche", 
        "givenName": "Rachid", 
        "id": "sg:person.015353410751.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015353410751.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universit\u00e9 de Sherbrooke", 
          "id": "https://www.grid.ac/institutes/grid.86715.3d", 
          "name": [
            "DOMUS Lab, Universit\u00e9 de Sherbrooke, Sherbrooke, Qu\u00e9bec, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pigot", 
        "givenName": "H\u00e9l\u00e8ne", 
        "id": "sg:person.0744660572.88", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0744660572.88"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universit\u00e9 de Sherbrooke", 
          "id": "https://www.grid.ac/institutes/grid.86715.3d", 
          "name": [
            "DOMUS Lab, Universit\u00e9 de Sherbrooke, Sherbrooke, Qu\u00e9bec, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Abdulrazaka", 
        "givenName": "Bessam", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universit\u00e9 de Sherbrooke", 
          "id": "https://www.grid.ac/institutes/grid.86715.3d", 
          "name": [
            "DOMUS Lab, Universit\u00e9 de Sherbrooke, Sherbrooke, Qu\u00e9bec, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Giroux", 
        "givenName": "Sylvain", 
        "id": "sg:person.01140034726.32", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01140034726.32"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/1475-925x-5-51", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003609459", 
          "https://doi.org/10.1186/1475-925x-5-51"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/328236.328110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036532408"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-24646-6_10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037469747", 
          "https://doi.org/10.1007/978-3-540-24646-6_10"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-24646-6_10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037469747", 
          "https://doi.org/10.1007/978-3-540-24646-6_10"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1012487302797", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048573168", 
          "https://doi.org/10.1023/a:1012487302797"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/scientificamerican0496-68", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056527474", 
          "https://doi.org/10.1038/scientificamerican0496-68"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/98.626980", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061251662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tcsvt.2003.818349", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061574495"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aos/1028144844", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064406105"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iembs.2006.260649", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1096109013"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iembs.2006.260649", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1096109013"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9780511809682", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098667572"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/9781119013563", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107030376"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2010", 
    "datePublishedReg": "2010-01-01", 
    "description": "Authentication is the process by which a user establishes his identification when accessing a service. The use of password to identify the user has been a successful technique in conventional computers. However, in pervasive computing where computing resources exist everywhere, it is necessary to perform user identification through various means. This paper addresses the inhabitant identification issue in smart houses. It studies the optimum time and sensor set required to unobtrusively detect the house occupant. We use a supervised learning approach to address this issue by learning Support Vector Machines classifier (SVM), which predict the users by their daily life habits. We have analyzed the early morning routine with six users. From the very first minute, users can be recognized with an accuracy of more than 85%. Then we have applied an SVM feature selection algorithm to remove noisy and outlier features. Thus, this increases the accuracy to 88% using less then 10 sensors.", 
    "editor": [
      {
        "familyName": "Yu", 
        "givenName": "Zhiwen", 
        "type": "Person"
      }, 
      {
        "familyName": "Liscano", 
        "givenName": "Ramiro", 
        "type": "Person"
      }, 
      {
        "familyName": "Chen", 
        "givenName": "Guanling", 
        "type": "Person"
      }, 
      {
        "familyName": "Zhang", 
        "givenName": "Daqing", 
        "type": "Person"
      }, 
      {
        "familyName": "Zhou", 
        "givenName": "Xingshe", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-16355-5_9", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-642-16354-8", 
        "978-3-642-16355-5"
      ], 
      "name": "Ubiquitous Intelligence and Computing", 
      "type": "Book"
    }, 
    "name": "Support Vector Machines for Inhabitant Identification in Smart Houses", 
    "pagination": "83-95", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-16355-5_9"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "e258f600086ae3b82cd6772748ec57f5e097275b6ceeb24e7f9318cf857fa3b5"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1047515356"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-16355-5_9", 
      "https://app.dimensions.ai/details/publication/pub.1047515356"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T15:58", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8672_00000594.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-3-642-16355-5_9"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-16355-5_9'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-16355-5_9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-16355-5_9'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-16355-5_9'


 

This table displays all metadata directly associated to this object as RDF triples.

142 TRIPLES      23 PREDICATES      38 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-16355-5_9 schema:about anzsrc-for:08
2 anzsrc-for:0806
3 schema:author Ne20de7b95918479da1bdaf4ef02f9ccf
4 schema:citation sg:pub.10.1007/978-3-540-24646-6_10
5 sg:pub.10.1023/a:1012487302797
6 sg:pub.10.1038/scientificamerican0496-68
7 sg:pub.10.1186/1475-925x-5-51
8 https://doi.org/10.1002/9781119013563
9 https://doi.org/10.1017/cbo9780511809682
10 https://doi.org/10.1109/98.626980
11 https://doi.org/10.1109/iembs.2006.260649
12 https://doi.org/10.1109/tcsvt.2003.818349
13 https://doi.org/10.1145/328236.328110
14 https://doi.org/10.1214/aos/1028144844
15 schema:datePublished 2010
16 schema:datePublishedReg 2010-01-01
17 schema:description Authentication is the process by which a user establishes his identification when accessing a service. The use of password to identify the user has been a successful technique in conventional computers. However, in pervasive computing where computing resources exist everywhere, it is necessary to perform user identification through various means. This paper addresses the inhabitant identification issue in smart houses. It studies the optimum time and sensor set required to unobtrusively detect the house occupant. We use a supervised learning approach to address this issue by learning Support Vector Machines classifier (SVM), which predict the users by their daily life habits. We have analyzed the early morning routine with six users. From the very first minute, users can be recognized with an accuracy of more than 85%. Then we have applied an SVM feature selection algorithm to remove noisy and outlier features. Thus, this increases the accuracy to 88% using less then 10 sensors.
18 schema:editor N38b240ddcb484f06b49817014186ba1d
19 schema:genre chapter
20 schema:inLanguage en
21 schema:isAccessibleForFree false
22 schema:isPartOf N403933f0463343bc89c1e758cd2a19d5
23 schema:name Support Vector Machines for Inhabitant Identification in Smart Houses
24 schema:pagination 83-95
25 schema:productId N0ca8fd37b4da4369b378fff2746563ca
26 N1d54d50c8fa74bad83852ffa7b6b7285
27 N77669576d52a468ab4c226eaeca4b46b
28 schema:publisher Na0f37908a98a4f89aaea541123a79725
29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047515356
30 https://doi.org/10.1007/978-3-642-16355-5_9
31 schema:sdDatePublished 2019-04-15T15:58
32 schema:sdLicense https://scigraph.springernature.com/explorer/license/
33 schema:sdPublisher N619bc5e9e9594e38a4fa5dafdde1428e
34 schema:url http://link.springer.com/10.1007/978-3-642-16355-5_9
35 sgo:license sg:explorer/license/
36 sgo:sdDataset chapters
37 rdf:type schema:Chapter
38 N0ca8fd37b4da4369b378fff2746563ca schema:name dimensions_id
39 schema:value pub.1047515356
40 rdf:type schema:PropertyValue
41 N15e4516e03644002855d8be45d14b3c8 rdf:first Nd373bd8c3419449e9808da0bfeca6e2e
42 rdf:rest N8ef496775b844ae28993784cd729483e
43 N1d54d50c8fa74bad83852ffa7b6b7285 schema:name readcube_id
44 schema:value e258f600086ae3b82cd6772748ec57f5e097275b6ceeb24e7f9318cf857fa3b5
45 rdf:type schema:PropertyValue
46 N20d0dffbbafa44a2ae5ac79260cb4c7e schema:familyName Zhou
47 schema:givenName Xingshe
48 rdf:type schema:Person
49 N336a3b6c116a4b3d88bd47c36faeda63 schema:familyName Chen
50 schema:givenName Guanling
51 rdf:type schema:Person
52 N38b240ddcb484f06b49817014186ba1d rdf:first N9d4665facb3f4c638e82f95ccf39923b
53 rdf:rest Nb8506bc0a0f748a0828cb8fb0cec10c1
54 N403933f0463343bc89c1e758cd2a19d5 schema:isbn 978-3-642-16354-8
55 978-3-642-16355-5
56 schema:name Ubiquitous Intelligence and Computing
57 rdf:type schema:Book
58 N5329cccf2a374021a1b954656962c0bf rdf:first sg:person.01140034726.32
59 rdf:rest rdf:nil
60 N619bc5e9e9594e38a4fa5dafdde1428e schema:name Springer Nature - SN SciGraph project
61 rdf:type schema:Organization
62 N64fae944606144438451a48a92885dbc schema:affiliation https://www.grid.ac/institutes/grid.86715.3d
63 schema:familyName Abdulrazaka
64 schema:givenName Bessam
65 rdf:type schema:Person
66 N6b7c7829b7e84a7dbaa5d8701929b33b rdf:first N64fae944606144438451a48a92885dbc
67 rdf:rest N5329cccf2a374021a1b954656962c0bf
68 N77669576d52a468ab4c226eaeca4b46b schema:name doi
69 schema:value 10.1007/978-3-642-16355-5_9
70 rdf:type schema:PropertyValue
71 N8ef496775b844ae28993784cd729483e rdf:first N20d0dffbbafa44a2ae5ac79260cb4c7e
72 rdf:rest rdf:nil
73 N9d4665facb3f4c638e82f95ccf39923b schema:familyName Yu
74 schema:givenName Zhiwen
75 rdf:type schema:Person
76 Na0f37908a98a4f89aaea541123a79725 schema:location Berlin, Heidelberg
77 schema:name Springer Berlin Heidelberg
78 rdf:type schema:Organisation
79 Nb8506bc0a0f748a0828cb8fb0cec10c1 rdf:first Ne1b2bd960caf4e4b930815d952f698ee
80 rdf:rest Nd55084cd74404a848599f949d74c89fb
81 Nd373bd8c3419449e9808da0bfeca6e2e schema:familyName Zhang
82 schema:givenName Daqing
83 rdf:type schema:Person
84 Nd55084cd74404a848599f949d74c89fb rdf:first N336a3b6c116a4b3d88bd47c36faeda63
85 rdf:rest N15e4516e03644002855d8be45d14b3c8
86 Ne1b2bd960caf4e4b930815d952f698ee schema:familyName Liscano
87 schema:givenName Ramiro
88 rdf:type schema:Person
89 Ne20de7b95918479da1bdaf4ef02f9ccf rdf:first sg:person.015353410751.46
90 rdf:rest Ne66c3c9bf6dd48f19c878c2a3b0f5774
91 Ne66c3c9bf6dd48f19c878c2a3b0f5774 rdf:first sg:person.0744660572.88
92 rdf:rest N6b7c7829b7e84a7dbaa5d8701929b33b
93 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
94 schema:name Information and Computing Sciences
95 rdf:type schema:DefinedTerm
96 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
97 schema:name Information Systems
98 rdf:type schema:DefinedTerm
99 sg:person.01140034726.32 schema:affiliation https://www.grid.ac/institutes/grid.86715.3d
100 schema:familyName Giroux
101 schema:givenName Sylvain
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01140034726.32
103 rdf:type schema:Person
104 sg:person.015353410751.46 schema:affiliation https://www.grid.ac/institutes/grid.86715.3d
105 schema:familyName Kadouche
106 schema:givenName Rachid
107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015353410751.46
108 rdf:type schema:Person
109 sg:person.0744660572.88 schema:affiliation https://www.grid.ac/institutes/grid.86715.3d
110 schema:familyName Pigot
111 schema:givenName Hélène
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0744660572.88
113 rdf:type schema:Person
114 sg:pub.10.1007/978-3-540-24646-6_10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037469747
115 https://doi.org/10.1007/978-3-540-24646-6_10
116 rdf:type schema:CreativeWork
117 sg:pub.10.1023/a:1012487302797 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048573168
118 https://doi.org/10.1023/a:1012487302797
119 rdf:type schema:CreativeWork
120 sg:pub.10.1038/scientificamerican0496-68 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056527474
121 https://doi.org/10.1038/scientificamerican0496-68
122 rdf:type schema:CreativeWork
123 sg:pub.10.1186/1475-925x-5-51 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003609459
124 https://doi.org/10.1186/1475-925x-5-51
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1002/9781119013563 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107030376
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1017/cbo9780511809682 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098667572
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1109/98.626980 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061251662
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1109/iembs.2006.260649 schema:sameAs https://app.dimensions.ai/details/publication/pub.1096109013
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1109/tcsvt.2003.818349 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061574495
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1145/328236.328110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036532408
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1214/aos/1028144844 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064406105
139 rdf:type schema:CreativeWork
140 https://www.grid.ac/institutes/grid.86715.3d schema:alternateName Université de Sherbrooke
141 schema:name DOMUS Lab, Université de Sherbrooke, Sherbrooke, Québec, Canada
142 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...