On building a smarter ecosystem using the internet of intelligent things: progress and future challenges
Abstract With a growing interest in the Internet of Things (IoT), the businesses are undergoing a revolution in the way they monitor and control. In the recent past, many applications were developed using the IoT system architectures in various business verticals such as industrial, healthcare, farm...
Ausführliche Beschreibung
Autor*in: |
Rajalakshmi, P. [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Übergeordnetes Werk: |
Enthalten in: CSI transactions on ICT - New Delhi : Springer India, 2013, 7(2019), 3 vom: 03. Juli, Seite 243-250 |
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Übergeordnetes Werk: |
volume:7 ; year:2019 ; number:3 ; day:03 ; month:07 ; pages:243-250 |
Links: |
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DOI / URN: |
10.1007/s40012-019-00256-5 |
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Katalog-ID: |
SPR032640110 |
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10.1007/s40012-019-00256-5 doi (DE-627)SPR032640110 (SPR)s40012-019-00256-5-e DE-627 ger DE-627 rakwb eng 004 ASE Rajalakshmi, P. verfasserin aut On building a smarter ecosystem using the internet of intelligent things: progress and future challenges 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract With a growing interest in the Internet of Things (IoT), the businesses are undergoing a revolution in the way they monitor and control. In the recent past, many applications were developed using the IoT system architectures in various business verticals such as industrial, healthcare, farming, transportation, etc. However, with the development of low-complex artificial intelligence frameworks which are capable of operating on the edge devices, the IoT architectures have taken a major leap leading to the Internet of Intelligent Things (IoIT). In this paper, we discuss our focused research and applications of IoIT across the following verticals: (1) healthcare, (2) smart buildings, (3) farming, along with the recent state of the art methodologies and future challenges. Under the healthcare, we laid our main focus on the development of AI enabled computer-aided diagnosis framework, which acquires the scanning information from a wireless ultrasound transducer and automatically identifies the abnormalities present. Also, we developed a low-complex brain-controlled IoT environments framework which automatically classifies the motor imagery task performed by the user using 22 channel electroencephalography. Using IoIT, we developed a novel non-invasive technology capable of monitoring various electrical parameters without any need for cutting the wires. This developed non-invasive power monitor is capable of generating real-time alerts in the case of system malfunctions and will be a key enabler for smart buildings. Also, we developed mathematical, simulation, and experimental models for analyzing the performance of channel access mechanisms of dense traffic IoT networks. IoIT (dpeaa)DE-He213 Tele-sonography (dpeaa)DE-He213 Brain controlled IoT environments (dpeaa)DE-He213 Crop management (dpeaa)DE-He213 Channel access (dpeaa)DE-He213 Enthalten in CSI transactions on ICT New Delhi : Springer India, 2013 7(2019), 3 vom: 03. Juli, Seite 243-250 (DE-627)736559264 (DE-600)2703329-6 2277-9086 nnns volume:7 year:2019 number:3 day:03 month:07 pages:243-250 https://dx.doi.org/10.1007/s40012-019-00256-5 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_65 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2019 3 03 07 243-250 |
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10.1007/s40012-019-00256-5 doi (DE-627)SPR032640110 (SPR)s40012-019-00256-5-e DE-627 ger DE-627 rakwb eng 004 ASE Rajalakshmi, P. verfasserin aut On building a smarter ecosystem using the internet of intelligent things: progress and future challenges 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract With a growing interest in the Internet of Things (IoT), the businesses are undergoing a revolution in the way they monitor and control. In the recent past, many applications were developed using the IoT system architectures in various business verticals such as industrial, healthcare, farming, transportation, etc. However, with the development of low-complex artificial intelligence frameworks which are capable of operating on the edge devices, the IoT architectures have taken a major leap leading to the Internet of Intelligent Things (IoIT). In this paper, we discuss our focused research and applications of IoIT across the following verticals: (1) healthcare, (2) smart buildings, (3) farming, along with the recent state of the art methodologies and future challenges. Under the healthcare, we laid our main focus on the development of AI enabled computer-aided diagnosis framework, which acquires the scanning information from a wireless ultrasound transducer and automatically identifies the abnormalities present. Also, we developed a low-complex brain-controlled IoT environments framework which automatically classifies the motor imagery task performed by the user using 22 channel electroencephalography. Using IoIT, we developed a novel non-invasive technology capable of monitoring various electrical parameters without any need for cutting the wires. This developed non-invasive power monitor is capable of generating real-time alerts in the case of system malfunctions and will be a key enabler for smart buildings. Also, we developed mathematical, simulation, and experimental models for analyzing the performance of channel access mechanisms of dense traffic IoT networks. IoIT (dpeaa)DE-He213 Tele-sonography (dpeaa)DE-He213 Brain controlled IoT environments (dpeaa)DE-He213 Crop management (dpeaa)DE-He213 Channel access (dpeaa)DE-He213 Enthalten in CSI transactions on ICT New Delhi : Springer India, 2013 7(2019), 3 vom: 03. Juli, Seite 243-250 (DE-627)736559264 (DE-600)2703329-6 2277-9086 nnns volume:7 year:2019 number:3 day:03 month:07 pages:243-250 https://dx.doi.org/10.1007/s40012-019-00256-5 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_65 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2019 3 03 07 243-250 |
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10.1007/s40012-019-00256-5 doi (DE-627)SPR032640110 (SPR)s40012-019-00256-5-e DE-627 ger DE-627 rakwb eng 004 ASE Rajalakshmi, P. verfasserin aut On building a smarter ecosystem using the internet of intelligent things: progress and future challenges 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract With a growing interest in the Internet of Things (IoT), the businesses are undergoing a revolution in the way they monitor and control. In the recent past, many applications were developed using the IoT system architectures in various business verticals such as industrial, healthcare, farming, transportation, etc. However, with the development of low-complex artificial intelligence frameworks which are capable of operating on the edge devices, the IoT architectures have taken a major leap leading to the Internet of Intelligent Things (IoIT). In this paper, we discuss our focused research and applications of IoIT across the following verticals: (1) healthcare, (2) smart buildings, (3) farming, along with the recent state of the art methodologies and future challenges. Under the healthcare, we laid our main focus on the development of AI enabled computer-aided diagnosis framework, which acquires the scanning information from a wireless ultrasound transducer and automatically identifies the abnormalities present. Also, we developed a low-complex brain-controlled IoT environments framework which automatically classifies the motor imagery task performed by the user using 22 channel electroencephalography. Using IoIT, we developed a novel non-invasive technology capable of monitoring various electrical parameters without any need for cutting the wires. This developed non-invasive power monitor is capable of generating real-time alerts in the case of system malfunctions and will be a key enabler for smart buildings. Also, we developed mathematical, simulation, and experimental models for analyzing the performance of channel access mechanisms of dense traffic IoT networks. IoIT (dpeaa)DE-He213 Tele-sonography (dpeaa)DE-He213 Brain controlled IoT environments (dpeaa)DE-He213 Crop management (dpeaa)DE-He213 Channel access (dpeaa)DE-He213 Enthalten in CSI transactions on ICT New Delhi : Springer India, 2013 7(2019), 3 vom: 03. Juli, Seite 243-250 (DE-627)736559264 (DE-600)2703329-6 2277-9086 nnns volume:7 year:2019 number:3 day:03 month:07 pages:243-250 https://dx.doi.org/10.1007/s40012-019-00256-5 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_65 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2019 3 03 07 243-250 |
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10.1007/s40012-019-00256-5 doi (DE-627)SPR032640110 (SPR)s40012-019-00256-5-e DE-627 ger DE-627 rakwb eng 004 ASE Rajalakshmi, P. verfasserin aut On building a smarter ecosystem using the internet of intelligent things: progress and future challenges 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract With a growing interest in the Internet of Things (IoT), the businesses are undergoing a revolution in the way they monitor and control. In the recent past, many applications were developed using the IoT system architectures in various business verticals such as industrial, healthcare, farming, transportation, etc. However, with the development of low-complex artificial intelligence frameworks which are capable of operating on the edge devices, the IoT architectures have taken a major leap leading to the Internet of Intelligent Things (IoIT). In this paper, we discuss our focused research and applications of IoIT across the following verticals: (1) healthcare, (2) smart buildings, (3) farming, along with the recent state of the art methodologies and future challenges. Under the healthcare, we laid our main focus on the development of AI enabled computer-aided diagnosis framework, which acquires the scanning information from a wireless ultrasound transducer and automatically identifies the abnormalities present. Also, we developed a low-complex brain-controlled IoT environments framework which automatically classifies the motor imagery task performed by the user using 22 channel electroencephalography. Using IoIT, we developed a novel non-invasive technology capable of monitoring various electrical parameters without any need for cutting the wires. This developed non-invasive power monitor is capable of generating real-time alerts in the case of system malfunctions and will be a key enabler for smart buildings. Also, we developed mathematical, simulation, and experimental models for analyzing the performance of channel access mechanisms of dense traffic IoT networks. IoIT (dpeaa)DE-He213 Tele-sonography (dpeaa)DE-He213 Brain controlled IoT environments (dpeaa)DE-He213 Crop management (dpeaa)DE-He213 Channel access (dpeaa)DE-He213 Enthalten in CSI transactions on ICT New Delhi : Springer India, 2013 7(2019), 3 vom: 03. Juli, Seite 243-250 (DE-627)736559264 (DE-600)2703329-6 2277-9086 nnns volume:7 year:2019 number:3 day:03 month:07 pages:243-250 https://dx.doi.org/10.1007/s40012-019-00256-5 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_65 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2019 3 03 07 243-250 |
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10.1007/s40012-019-00256-5 doi (DE-627)SPR032640110 (SPR)s40012-019-00256-5-e DE-627 ger DE-627 rakwb eng 004 ASE Rajalakshmi, P. verfasserin aut On building a smarter ecosystem using the internet of intelligent things: progress and future challenges 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract With a growing interest in the Internet of Things (IoT), the businesses are undergoing a revolution in the way they monitor and control. In the recent past, many applications were developed using the IoT system architectures in various business verticals such as industrial, healthcare, farming, transportation, etc. However, with the development of low-complex artificial intelligence frameworks which are capable of operating on the edge devices, the IoT architectures have taken a major leap leading to the Internet of Intelligent Things (IoIT). In this paper, we discuss our focused research and applications of IoIT across the following verticals: (1) healthcare, (2) smart buildings, (3) farming, along with the recent state of the art methodologies and future challenges. Under the healthcare, we laid our main focus on the development of AI enabled computer-aided diagnosis framework, which acquires the scanning information from a wireless ultrasound transducer and automatically identifies the abnormalities present. Also, we developed a low-complex brain-controlled IoT environments framework which automatically classifies the motor imagery task performed by the user using 22 channel electroencephalography. Using IoIT, we developed a novel non-invasive technology capable of monitoring various electrical parameters without any need for cutting the wires. This developed non-invasive power monitor is capable of generating real-time alerts in the case of system malfunctions and will be a key enabler for smart buildings. Also, we developed mathematical, simulation, and experimental models for analyzing the performance of channel access mechanisms of dense traffic IoT networks. IoIT (dpeaa)DE-He213 Tele-sonography (dpeaa)DE-He213 Brain controlled IoT environments (dpeaa)DE-He213 Crop management (dpeaa)DE-He213 Channel access (dpeaa)DE-He213 Enthalten in CSI transactions on ICT New Delhi : Springer India, 2013 7(2019), 3 vom: 03. Juli, Seite 243-250 (DE-627)736559264 (DE-600)2703329-6 2277-9086 nnns volume:7 year:2019 number:3 day:03 month:07 pages:243-250 https://dx.doi.org/10.1007/s40012-019-00256-5 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_65 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2019 3 03 07 243-250 |
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Rajalakshmi, P. |
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Rajalakshmi, P. ddc 004 misc IoIT misc Tele-sonography misc Brain controlled IoT environments misc Crop management misc Channel access On building a smarter ecosystem using the internet of intelligent things: progress and future challenges |
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004 ASE On building a smarter ecosystem using the internet of intelligent things: progress and future challenges IoIT (dpeaa)DE-He213 Tele-sonography (dpeaa)DE-He213 Brain controlled IoT environments (dpeaa)DE-He213 Crop management (dpeaa)DE-He213 Channel access (dpeaa)DE-He213 |
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on building a smarter ecosystem using the internet of intelligent things: progress and future challenges |
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On building a smarter ecosystem using the internet of intelligent things: progress and future challenges |
abstract |
Abstract With a growing interest in the Internet of Things (IoT), the businesses are undergoing a revolution in the way they monitor and control. In the recent past, many applications were developed using the IoT system architectures in various business verticals such as industrial, healthcare, farming, transportation, etc. However, with the development of low-complex artificial intelligence frameworks which are capable of operating on the edge devices, the IoT architectures have taken a major leap leading to the Internet of Intelligent Things (IoIT). In this paper, we discuss our focused research and applications of IoIT across the following verticals: (1) healthcare, (2) smart buildings, (3) farming, along with the recent state of the art methodologies and future challenges. Under the healthcare, we laid our main focus on the development of AI enabled computer-aided diagnosis framework, which acquires the scanning information from a wireless ultrasound transducer and automatically identifies the abnormalities present. Also, we developed a low-complex brain-controlled IoT environments framework which automatically classifies the motor imagery task performed by the user using 22 channel electroencephalography. Using IoIT, we developed a novel non-invasive technology capable of monitoring various electrical parameters without any need for cutting the wires. This developed non-invasive power monitor is capable of generating real-time alerts in the case of system malfunctions and will be a key enabler for smart buildings. Also, we developed mathematical, simulation, and experimental models for analyzing the performance of channel access mechanisms of dense traffic IoT networks. |
abstractGer |
Abstract With a growing interest in the Internet of Things (IoT), the businesses are undergoing a revolution in the way they monitor and control. In the recent past, many applications were developed using the IoT system architectures in various business verticals such as industrial, healthcare, farming, transportation, etc. However, with the development of low-complex artificial intelligence frameworks which are capable of operating on the edge devices, the IoT architectures have taken a major leap leading to the Internet of Intelligent Things (IoIT). In this paper, we discuss our focused research and applications of IoIT across the following verticals: (1) healthcare, (2) smart buildings, (3) farming, along with the recent state of the art methodologies and future challenges. Under the healthcare, we laid our main focus on the development of AI enabled computer-aided diagnosis framework, which acquires the scanning information from a wireless ultrasound transducer and automatically identifies the abnormalities present. Also, we developed a low-complex brain-controlled IoT environments framework which automatically classifies the motor imagery task performed by the user using 22 channel electroencephalography. Using IoIT, we developed a novel non-invasive technology capable of monitoring various electrical parameters without any need for cutting the wires. This developed non-invasive power monitor is capable of generating real-time alerts in the case of system malfunctions and will be a key enabler for smart buildings. Also, we developed mathematical, simulation, and experimental models for analyzing the performance of channel access mechanisms of dense traffic IoT networks. |
abstract_unstemmed |
Abstract With a growing interest in the Internet of Things (IoT), the businesses are undergoing a revolution in the way they monitor and control. In the recent past, many applications were developed using the IoT system architectures in various business verticals such as industrial, healthcare, farming, transportation, etc. However, with the development of low-complex artificial intelligence frameworks which are capable of operating on the edge devices, the IoT architectures have taken a major leap leading to the Internet of Intelligent Things (IoIT). In this paper, we discuss our focused research and applications of IoIT across the following verticals: (1) healthcare, (2) smart buildings, (3) farming, along with the recent state of the art methodologies and future challenges. Under the healthcare, we laid our main focus on the development of AI enabled computer-aided diagnosis framework, which acquires the scanning information from a wireless ultrasound transducer and automatically identifies the abnormalities present. Also, we developed a low-complex brain-controlled IoT environments framework which automatically classifies the motor imagery task performed by the user using 22 channel electroencephalography. Using IoIT, we developed a novel non-invasive technology capable of monitoring various electrical parameters without any need for cutting the wires. This developed non-invasive power monitor is capable of generating real-time alerts in the case of system malfunctions and will be a key enabler for smart buildings. Also, we developed mathematical, simulation, and experimental models for analyzing the performance of channel access mechanisms of dense traffic IoT networks. |
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title_short |
On building a smarter ecosystem using the internet of intelligent things: progress and future challenges |
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https://dx.doi.org/10.1007/s40012-019-00256-5 |
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10.1007/s40012-019-00256-5 |
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2024-07-03T14:00:11.638Z |
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