A Model for Boat Accident Prediction Using Geographical and Topological Data
Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Vasavi, S. [verfasserIn] LeelaBhavani, Anumolu [verfasserIn] Badeti, Puja [verfasserIn] Harikiran, C. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: SN Computer Science - Singapore : Springer Singapore, 2020, 2(2021), 3 vom: 10. März |
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| Übergeordnetes Werk: |
volume:2 ; year:2021 ; number:3 ; day:10 ; month:03 |
| Links: |
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| DOI / URN: |
10.1007/s42979-021-00517-8 |
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| Katalog-ID: |
SPR04345867X |
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| 100 | 1 | |a Vasavi, S. |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A Model for Boat Accident Prediction Using Geographical and Topological Data |
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| 520 | |a Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions. | ||
| 650 | 4 | |a Location primarily based services |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Boat accident prediction |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Disaster management |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Geo location |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Transportation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Marine traffic safety |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a LeelaBhavani, Anumolu |e verfasserin |4 aut | |
| 700 | 1 | |a Badeti, Puja |e verfasserin |4 aut | |
| 700 | 1 | |a Harikiran, C. |e verfasserin |4 aut | |
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2021 |
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10.1007/s42979-021-00517-8 doi (DE-627)SPR04345867X (DE-599)SPRs42979-021-00517-8-e (SPR)s42979-021-00517-8-e DE-627 ger DE-627 rakwb eng Vasavi, S. verfasserin aut A Model for Boat Accident Prediction Using Geographical and Topological Data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions. Location primarily based services (dpeaa)DE-He213 Boat accident prediction (dpeaa)DE-He213 Disaster management (dpeaa)DE-He213 Geo location (dpeaa)DE-He213 Transportation (dpeaa)DE-He213 Marine traffic safety (dpeaa)DE-He213 LeelaBhavani, Anumolu verfasserin aut Badeti, Puja verfasserin aut Harikiran, C. verfasserin aut Enthalten in SN Computer Science Singapore : Springer Singapore, 2020 2(2021), 3 vom: 10. März (DE-627)1668832976 (DE-600)2977367-2 2661-8907 nnns volume:2 year:2021 number:3 day:10 month:03 https://dx.doi.org/10.1007/s42979-021-00517-8 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_105 GBV_ILN_110 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_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 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_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 2 2021 3 10 03 |
| spelling |
10.1007/s42979-021-00517-8 doi (DE-627)SPR04345867X (DE-599)SPRs42979-021-00517-8-e (SPR)s42979-021-00517-8-e DE-627 ger DE-627 rakwb eng Vasavi, S. verfasserin aut A Model for Boat Accident Prediction Using Geographical and Topological Data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions. Location primarily based services (dpeaa)DE-He213 Boat accident prediction (dpeaa)DE-He213 Disaster management (dpeaa)DE-He213 Geo location (dpeaa)DE-He213 Transportation (dpeaa)DE-He213 Marine traffic safety (dpeaa)DE-He213 LeelaBhavani, Anumolu verfasserin aut Badeti, Puja verfasserin aut Harikiran, C. verfasserin aut Enthalten in SN Computer Science Singapore : Springer Singapore, 2020 2(2021), 3 vom: 10. März (DE-627)1668832976 (DE-600)2977367-2 2661-8907 nnns volume:2 year:2021 number:3 day:10 month:03 https://dx.doi.org/10.1007/s42979-021-00517-8 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_105 GBV_ILN_110 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_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 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_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 2 2021 3 10 03 |
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10.1007/s42979-021-00517-8 doi (DE-627)SPR04345867X (DE-599)SPRs42979-021-00517-8-e (SPR)s42979-021-00517-8-e DE-627 ger DE-627 rakwb eng Vasavi, S. verfasserin aut A Model for Boat Accident Prediction Using Geographical and Topological Data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions. Location primarily based services (dpeaa)DE-He213 Boat accident prediction (dpeaa)DE-He213 Disaster management (dpeaa)DE-He213 Geo location (dpeaa)DE-He213 Transportation (dpeaa)DE-He213 Marine traffic safety (dpeaa)DE-He213 LeelaBhavani, Anumolu verfasserin aut Badeti, Puja verfasserin aut Harikiran, C. verfasserin aut Enthalten in SN Computer Science Singapore : Springer Singapore, 2020 2(2021), 3 vom: 10. März (DE-627)1668832976 (DE-600)2977367-2 2661-8907 nnns volume:2 year:2021 number:3 day:10 month:03 https://dx.doi.org/10.1007/s42979-021-00517-8 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_105 GBV_ILN_110 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_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 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_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 2 2021 3 10 03 |
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10.1007/s42979-021-00517-8 doi (DE-627)SPR04345867X (DE-599)SPRs42979-021-00517-8-e (SPR)s42979-021-00517-8-e DE-627 ger DE-627 rakwb eng Vasavi, S. verfasserin aut A Model for Boat Accident Prediction Using Geographical and Topological Data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions. Location primarily based services (dpeaa)DE-He213 Boat accident prediction (dpeaa)DE-He213 Disaster management (dpeaa)DE-He213 Geo location (dpeaa)DE-He213 Transportation (dpeaa)DE-He213 Marine traffic safety (dpeaa)DE-He213 LeelaBhavani, Anumolu verfasserin aut Badeti, Puja verfasserin aut Harikiran, C. verfasserin aut Enthalten in SN Computer Science Singapore : Springer Singapore, 2020 2(2021), 3 vom: 10. März (DE-627)1668832976 (DE-600)2977367-2 2661-8907 nnns volume:2 year:2021 number:3 day:10 month:03 https://dx.doi.org/10.1007/s42979-021-00517-8 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_105 GBV_ILN_110 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_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 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_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 2 2021 3 10 03 |
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10.1007/s42979-021-00517-8 doi (DE-627)SPR04345867X (DE-599)SPRs42979-021-00517-8-e (SPR)s42979-021-00517-8-e DE-627 ger DE-627 rakwb eng Vasavi, S. verfasserin aut A Model for Boat Accident Prediction Using Geographical and Topological Data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions. Location primarily based services (dpeaa)DE-He213 Boat accident prediction (dpeaa)DE-He213 Disaster management (dpeaa)DE-He213 Geo location (dpeaa)DE-He213 Transportation (dpeaa)DE-He213 Marine traffic safety (dpeaa)DE-He213 LeelaBhavani, Anumolu verfasserin aut Badeti, Puja verfasserin aut Harikiran, C. verfasserin aut Enthalten in SN Computer Science Singapore : Springer Singapore, 2020 2(2021), 3 vom: 10. März (DE-627)1668832976 (DE-600)2977367-2 2661-8907 nnns volume:2 year:2021 number:3 day:10 month:03 https://dx.doi.org/10.1007/s42979-021-00517-8 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_105 GBV_ILN_110 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_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 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_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 2 2021 3 10 03 |
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One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. 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| author |
Vasavi, S. |
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Vasavi, S. misc Location primarily based services misc Boat accident prediction misc Disaster management misc Geo location misc Transportation misc Marine traffic safety A Model for Boat Accident Prediction Using Geographical and Topological Data |
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A Model for Boat Accident Prediction Using Geographical and Topological Data Location primarily based services (dpeaa)DE-He213 Boat accident prediction (dpeaa)DE-He213 Disaster management (dpeaa)DE-He213 Geo location (dpeaa)DE-He213 Transportation (dpeaa)DE-He213 Marine traffic safety (dpeaa)DE-He213 |
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A Model for Boat Accident Prediction Using Geographical and Topological Data |
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A Model for Boat Accident Prediction Using Geographical and Topological Data |
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model for boat accident prediction using geographical and topological data |
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A Model for Boat Accident Prediction Using Geographical and Topological Data |
| abstract |
Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions. |
| abstractGer |
Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions. |
| abstract_unstemmed |
Abstract In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions. |
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3 |
| title_short |
A Model for Boat Accident Prediction Using Geographical and Topological Data |
| url |
https://dx.doi.org/10.1007/s42979-021-00517-8 |
| remote_bool |
true |
| author2 |
LeelaBhavani, Anumolu Badeti, Puja Harikiran, C. |
| author2Str |
LeelaBhavani, Anumolu Badeti, Puja Harikiran, C. |
| ppnlink |
1668832976 |
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c |
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false |
| doi_str |
10.1007/s42979-021-00517-8 |
| up_date |
2024-07-03T18:48:42.967Z |
| _version_ |
1803584822805790720 |
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|
| score |
7.401493 |