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Geo-tag’s Visual Data for Earthquake Mitigation
Nugraha A.C.a, Supangkat S.H.a, Nugraha I.G.B.B.a, Thahir R.A.b
a Institut Teknologi Bandung, Sekolah Teknik Elektro Dan Informatika, Bandung, Indonesia
b Politeknik Negeri Bandung, D4 Teknik Telekomunikasi, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 IEEE.In our daily lives, society always live up side by side with disaster. The causes of a disaster can possibly come from either (or both) natural or human technological factors. Several studies have stated that : improving the disaster preparedness will reduce the impact / risk of disasters. Therefore, an ICT ecosystem will be developed to increase community preparedness in facing earthquakes. Earthquake is a natural phenomenon which is pretty difficult to predict, so that one of the actions that can be taken before a disaster occurs is to increase awareness, for example by analyzing the readiness of buildings to experience earth shocks.In this paper, we will present the process of analyzing textual and image data from the condition of the building, then classifying it based on the level of readiness of the building to receive shocks caused by earthquakes. The classification process will be executed through a perceptual assessment carried out by both lay users and experts in the field of building construction and disaster. The classification results will be the input data for the process of determining the location of the building by applying the Deep Convolutional Neural Network approach. The output of this identification process is a geo-tagged photos that can be used as a reference so that disaster mitigation can be carried out by related parties.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Building construction,Classification process,Classification results,Disaster preparedness,Earthquake mitigations,Identification process,Perceptual assessment,Technological factors[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]geo-tagged photo,kesiapsiagaan gempa,lifelong machine learning,preparedness disaster[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICISS50791.2020.9307542[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]