Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy
This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Tan, Zhichao [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2018transfer abstract |
|---|
| Schlagwörter: |
|---|
| Umfang: |
12 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation - Liu, Xiang ELSEVIER, 2015, the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:76 ; year:2018 ; pages:214-225 ; extent:12 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.engappai.2018.08.009 |
|---|
| Katalog-ID: |
ELV044422288 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV044422288 | ||
| 003 | DE-627 | ||
| 005 | 20230626005138.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 181113s2018 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.engappai.2018.08.009 |2 doi | |
| 028 | 5 | 2 | |a GBV00000000000395.pica |
| 035 | |a (DE-627)ELV044422288 | ||
| 035 | |a (ELSEVIER)S0952-1976(18)30172-6 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 540 |q VZ |
| 082 | 0 | 4 | |a 610 |q VZ |
| 084 | |a 44.00 |2 bkl | ||
| 100 | 1 | |a Tan, Zhichao |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy |
| 264 | 1 | |c 2018transfer abstract | |
| 300 | |a 12 | ||
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. | ||
| 520 | |a This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. | ||
| 650 | 7 | |a Position-based stigmergy |2 Elsevier | |
| 650 | 7 | |a Ambient assisted living |2 Elsevier | |
| 650 | 7 | |a Online daily habit modeling |2 Elsevier | |
| 650 | 7 | |a Recognition of activity of daily livings |2 Elsevier | |
| 700 | 1 | |a Xu, Liwen |4 oth | |
| 700 | 1 | |a Zhong, Wei |4 oth | |
| 700 | 1 | |a Guo, Xuemei |4 oth | |
| 700 | 1 | |a Wang, Guoli |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Liu, Xiang ELSEVIER |t Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation |d 2015 |d the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control |g Amsterdam [u.a.] |w (DE-627)ELV013402978 |
| 773 | 1 | 8 | |g volume:76 |g year:2018 |g pages:214-225 |g extent:12 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.engappai.2018.08.009 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a SSG-OLC-PHA | ||
| 936 | b | k | |a 44.00 |j Medizin: Allgemeines |q VZ |
| 951 | |a AR | ||
| 952 | |d 76 |j 2018 |h 214-225 |g 12 | ||
| author_variant |
z t zt |
|---|---|
| matchkey_str |
tanzhichaoxuliwenzhongweiguoxuemeiwanggu:2018----:nieciiyeontoadalhbtoeigosltredryhogi |
| hierarchy_sort_str |
2018transfer abstract |
| bklnumber |
44.00 |
| publishDate |
2018 |
| allfields |
10.1016/j.engappai.2018.08.009 doi GBV00000000000395.pica (DE-627)ELV044422288 (ELSEVIER)S0952-1976(18)30172-6 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Tan, Zhichao verfasserin aut Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy 2018transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings Elsevier Xu, Liwen oth Zhong, Wei oth Guo, Xuemei oth Wang, Guoli oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:76 year:2018 pages:214-225 extent:12 https://doi.org/10.1016/j.engappai.2018.08.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 76 2018 214-225 12 |
| spelling |
10.1016/j.engappai.2018.08.009 doi GBV00000000000395.pica (DE-627)ELV044422288 (ELSEVIER)S0952-1976(18)30172-6 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Tan, Zhichao verfasserin aut Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy 2018transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings Elsevier Xu, Liwen oth Zhong, Wei oth Guo, Xuemei oth Wang, Guoli oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:76 year:2018 pages:214-225 extent:12 https://doi.org/10.1016/j.engappai.2018.08.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 76 2018 214-225 12 |
| allfields_unstemmed |
10.1016/j.engappai.2018.08.009 doi GBV00000000000395.pica (DE-627)ELV044422288 (ELSEVIER)S0952-1976(18)30172-6 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Tan, Zhichao verfasserin aut Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy 2018transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings Elsevier Xu, Liwen oth Zhong, Wei oth Guo, Xuemei oth Wang, Guoli oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:76 year:2018 pages:214-225 extent:12 https://doi.org/10.1016/j.engappai.2018.08.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 76 2018 214-225 12 |
| allfieldsGer |
10.1016/j.engappai.2018.08.009 doi GBV00000000000395.pica (DE-627)ELV044422288 (ELSEVIER)S0952-1976(18)30172-6 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Tan, Zhichao verfasserin aut Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy 2018transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings Elsevier Xu, Liwen oth Zhong, Wei oth Guo, Xuemei oth Wang, Guoli oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:76 year:2018 pages:214-225 extent:12 https://doi.org/10.1016/j.engappai.2018.08.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 76 2018 214-225 12 |
| allfieldsSound |
10.1016/j.engappai.2018.08.009 doi GBV00000000000395.pica (DE-627)ELV044422288 (ELSEVIER)S0952-1976(18)30172-6 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Tan, Zhichao verfasserin aut Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy 2018transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings Elsevier Xu, Liwen oth Zhong, Wei oth Guo, Xuemei oth Wang, Guoli oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:76 year:2018 pages:214-225 extent:12 https://doi.org/10.1016/j.engappai.2018.08.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 76 2018 214-225 12 |
| language |
English |
| source |
Enthalten in Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation Amsterdam [u.a.] volume:76 year:2018 pages:214-225 extent:12 |
| sourceStr |
Enthalten in Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation Amsterdam [u.a.] volume:76 year:2018 pages:214-225 extent:12 |
| format_phy_str_mv |
Article |
| bklname |
Medizin: Allgemeines |
| institution |
findex.gbv.de |
| topic_facet |
Position-based stigmergy Ambient assisted living Online daily habit modeling Recognition of activity of daily livings |
| dewey-raw |
540 |
| isfreeaccess_bool |
false |
| container_title |
Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation |
| authorswithroles_txt_mv |
Tan, Zhichao @@aut@@ Xu, Liwen @@oth@@ Zhong, Wei @@oth@@ Guo, Xuemei @@oth@@ Wang, Guoli @@oth@@ |
| publishDateDaySort_date |
2018-01-01T00:00:00Z |
| hierarchy_top_id |
ELV013402978 |
| dewey-sort |
3540 |
| id |
ELV044422288 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV044422288</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626005138.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">181113s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.engappai.2018.08.009</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000395.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV044422288</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0952-1976(18)30172-6</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Tan, Zhichao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">12</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Position-based stigmergy</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Ambient assisted living</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Online daily habit modeling</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Recognition of activity of daily livings</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xu, Liwen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhong, Wei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Guo, Xuemei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Guoli</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Liu, Xiang ELSEVIER</subfield><subfield code="t">Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation</subfield><subfield code="d">2015</subfield><subfield code="d">the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV013402978</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:76</subfield><subfield code="g">year:2018</subfield><subfield code="g">pages:214-225</subfield><subfield code="g">extent:12</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.engappai.2018.08.009</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.00</subfield><subfield code="j">Medizin: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">76</subfield><subfield code="j">2018</subfield><subfield code="h">214-225</subfield><subfield code="g">12</subfield></datafield></record></collection>
|
| author |
Tan, Zhichao |
| spellingShingle |
Tan, Zhichao ddc 540 ddc 610 bkl 44.00 Elsevier Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy |
| authorStr |
Tan, Zhichao |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV013402978 |
| format |
electronic Article |
| dewey-ones |
540 - Chemistry & allied sciences 610 - Medicine & health |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
540 VZ 610 VZ 44.00 bkl Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings Elsevier |
| topic |
ddc 540 ddc 610 bkl 44.00 Elsevier Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings |
| topic_unstemmed |
ddc 540 ddc 610 bkl 44.00 Elsevier Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings |
| topic_browse |
ddc 540 ddc 610 bkl 44.00 Elsevier Position-based stigmergy Elsevier Ambient assisted living Elsevier Online daily habit modeling Elsevier Recognition of activity of daily livings |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
l x lx w z wz x g xg g w gw |
| hierarchy_parent_title |
Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation |
| hierarchy_parent_id |
ELV013402978 |
| dewey-tens |
540 - Chemistry 610 - Medicine & health |
| hierarchy_top_title |
Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV013402978 |
| title |
Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy |
| ctrlnum |
(DE-627)ELV044422288 (ELSEVIER)S0952-1976(18)30172-6 |
| title_full |
Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy |
| author_sort |
Tan, Zhichao |
| journal |
Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation |
| journalStr |
Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
500 - Science 600 - Technology |
| recordtype |
marc |
| publishDateSort |
2018 |
| contenttype_str_mv |
zzz |
| container_start_page |
214 |
| author_browse |
Tan, Zhichao |
| container_volume |
76 |
| physical |
12 |
| class |
540 VZ 610 VZ 44.00 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Tan, Zhichao |
| doi_str_mv |
10.1016/j.engappai.2018.08.009 |
| dewey-full |
540 610 |
| title_sort |
online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy |
| title_auth |
Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy |
| abstract |
This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. |
| abstractGer |
This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. |
| abstract_unstemmed |
This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA |
| title_short |
Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy |
| url |
https://doi.org/10.1016/j.engappai.2018.08.009 |
| remote_bool |
true |
| author2 |
Xu, Liwen Zhong, Wei Guo, Xuemei Wang, Guoli |
| author2Str |
Xu, Liwen Zhong, Wei Guo, Xuemei Wang, Guoli |
| ppnlink |
ELV013402978 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth oth |
| doi_str |
10.1016/j.engappai.2018.08.009 |
| up_date |
2024-07-06T21:27:16.184Z |
| _version_ |
1803866589033922560 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV044422288</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626005138.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">181113s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.engappai.2018.08.009</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000395.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV044422288</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0952-1976(18)30172-6</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Tan, Zhichao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Online activity recognition and daily habit modeling for solitary elderly through indoor position-based stigmergy</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">12</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper concerns the issue of monitoring elderly behavior in the context of ambient assisted living (AAL). Under the framework of online daily habit modeling (ODHM), we employ the emergent representation for activities of daily living (ADLs) with position-based stigmergy, and then combine it with convolution neural networks (CNNs) to accomplish the tasks of recognizing ADLs. In addition, we propose a new paradigm of activity summarization with the robustness to break interruptions. Radio tomographic imaging (RTI) is promoted as a simple yet flexible way of facilitating the required position-based stigmergy. Such position-based AAL systems can benefit the advantages of having no need any sophisticated domain models in analyzing and understanding ADLs while no burden training is involved in ODHM. Moreover, the emergent based data aggregation and deep learning of CNN together allow the recognition of ADLs at a fine-grained level, which contributes to the performance improvement of ODHM. Experimental results demonstrate the effectiveness of the proposed approach.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Position-based stigmergy</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Ambient assisted living</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Online daily habit modeling</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Recognition of activity of daily livings</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xu, Liwen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhong, Wei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Guo, Xuemei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Guoli</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Liu, Xiang ELSEVIER</subfield><subfield code="t">Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation</subfield><subfield code="d">2015</subfield><subfield code="d">the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV013402978</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:76</subfield><subfield code="g">year:2018</subfield><subfield code="g">pages:214-225</subfield><subfield code="g">extent:12</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.engappai.2018.08.009</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.00</subfield><subfield code="j">Medizin: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">76</subfield><subfield code="j">2018</subfield><subfield code="h">214-225</subfield><subfield code="g">12</subfield></datafield></record></collection>
|
| score |
7.4017773 |