Activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory
Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accel...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Sharma, Purushottam [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Multimedia tools and applications - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995, 82(2022), 2 vom: 22. Juni, Seite 2277-2302 |
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| Übergeordnetes Werk: |
volume:82 ; year:2022 ; number:2 ; day:22 ; month:06 ; pages:2277-2302 |
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| DOI / URN: |
10.1007/s11042-022-13290-4 |
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| Katalog-ID: |
SPR048964883 |
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| 520 | |a Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities. | ||
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| 700 | 1 | |a Sharma, Richa |4 aut | |
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10.1007/s11042-022-13290-4 doi (DE-627)SPR048964883 (SPR)s11042-022-13290-4-e DE-627 ger DE-627 rakwb eng Sharma, Purushottam verfasserin aut Activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities. Biometrics (dpeaa)DE-He213 Data mining (dpeaa)DE-He213 Sensors (dpeaa)DE-He213 Smartphone (dpeaa)DE-He213 Smartwatch (dpeaa)DE-He213 Fuzzy (dpeaa)DE-He213 Alshehri, Mohammed (orcid)0000-0003-1035-311X aut Sharma, Richa aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 82(2022), 2 vom: 22. Juni, Seite 2277-2302 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:82 year:2022 number:2 day:22 month:06 pages:2277-2302 https://dx.doi.org/10.1007/s11042-022-13290-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 82 2022 2 22 06 2277-2302 |
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10.1007/s11042-022-13290-4 doi (DE-627)SPR048964883 (SPR)s11042-022-13290-4-e DE-627 ger DE-627 rakwb eng Sharma, Purushottam verfasserin aut Activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities. Biometrics (dpeaa)DE-He213 Data mining (dpeaa)DE-He213 Sensors (dpeaa)DE-He213 Smartphone (dpeaa)DE-He213 Smartwatch (dpeaa)DE-He213 Fuzzy (dpeaa)DE-He213 Alshehri, Mohammed (orcid)0000-0003-1035-311X aut Sharma, Richa aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 82(2022), 2 vom: 22. Juni, Seite 2277-2302 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:82 year:2022 number:2 day:22 month:06 pages:2277-2302 https://dx.doi.org/10.1007/s11042-022-13290-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 82 2022 2 22 06 2277-2302 |
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10.1007/s11042-022-13290-4 doi (DE-627)SPR048964883 (SPR)s11042-022-13290-4-e DE-627 ger DE-627 rakwb eng Sharma, Purushottam verfasserin aut Activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities. Biometrics (dpeaa)DE-He213 Data mining (dpeaa)DE-He213 Sensors (dpeaa)DE-He213 Smartphone (dpeaa)DE-He213 Smartwatch (dpeaa)DE-He213 Fuzzy (dpeaa)DE-He213 Alshehri, Mohammed (orcid)0000-0003-1035-311X aut Sharma, Richa aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 82(2022), 2 vom: 22. Juni, Seite 2277-2302 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:82 year:2022 number:2 day:22 month:06 pages:2277-2302 https://dx.doi.org/10.1007/s11042-022-13290-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 82 2022 2 22 06 2277-2302 |
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10.1007/s11042-022-13290-4 doi (DE-627)SPR048964883 (SPR)s11042-022-13290-4-e DE-627 ger DE-627 rakwb eng Sharma, Purushottam verfasserin aut Activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities. Biometrics (dpeaa)DE-He213 Data mining (dpeaa)DE-He213 Sensors (dpeaa)DE-He213 Smartphone (dpeaa)DE-He213 Smartwatch (dpeaa)DE-He213 Fuzzy (dpeaa)DE-He213 Alshehri, Mohammed (orcid)0000-0003-1035-311X aut Sharma, Richa aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 82(2022), 2 vom: 22. Juni, Seite 2277-2302 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:82 year:2022 number:2 day:22 month:06 pages:2277-2302 https://dx.doi.org/10.1007/s11042-022-13290-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 82 2022 2 22 06 2277-2302 |
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10.1007/s11042-022-13290-4 doi (DE-627)SPR048964883 (SPR)s11042-022-13290-4-e DE-627 ger DE-627 rakwb eng Sharma, Purushottam verfasserin aut Activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities. Biometrics (dpeaa)DE-He213 Data mining (dpeaa)DE-He213 Sensors (dpeaa)DE-He213 Smartphone (dpeaa)DE-He213 Smartwatch (dpeaa)DE-He213 Fuzzy (dpeaa)DE-He213 Alshehri, Mohammed (orcid)0000-0003-1035-311X aut Sharma, Richa aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 82(2022), 2 vom: 22. Juni, Seite 2277-2302 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:82 year:2022 number:2 day:22 month:06 pages:2277-2302 https://dx.doi.org/10.1007/s11042-022-13290-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 82 2022 2 22 06 2277-2302 |
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Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. 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activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory |
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Activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory |
| abstract |
Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
| abstractGer |
Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
| abstract_unstemmed |
Abstract A Real-time available platform for deployment and implementation of mobile motion-based biometric behavior is provided by smartphones and smartwatches, including sensors. Sensors and physical activity evaluation are quite limited for motion-based commercial devices. In some cases, the accelerometer sensor of the smartwatch is utilized or walking is investigated. The combination of multiple sensors can perform better in terms of sensors, which can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated with biometric authentication. The study’s main objective is to track and monitor the daily lives activities using digital devices like smartphones and smartwatches for healthy human life. The result shows that using the different computing techniques in phones and watching for biometric can provide a suitable output based on the mentioned activities. This indicates that the feasibility results of continuous biometrics analysis in terms of average daily routine activities, can enhance the everyday routine life. The study also shows some of the easy to do activities like clapping, and walking may be a viable alternative for healthy life. Fuzzy based classification system is being utilized to improve the tracking system. In the present research, the Fuzzy Rule-Based Classification System justified the improved classification efficiency over the existing techniques for biometric activities. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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Activities tracking by smartphone and smartwatch biometric sensors using fuzzy set theory |
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https://dx.doi.org/10.1007/s11042-022-13290-4 |
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Alshehri, Mohammed Sharma, Richa |
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10.1007/s11042-022-13290-4 |
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| score |
7.3983088 |