Title :
Modeling unpredictable data and moving object in disaster management information system based on spatio-temporal data model
Author :
Laksmiwati, Hira ; Widyani, Yani ; Hafidhoh, Nisa´ul ; Yusuf, Atika
Author_Institution :
Sch. of Electr. Eng. & Inf., Inst. Teknol. Bandung, Bandung, Indonesia
Abstract :
On a workshop to improve the compilation of reliable data on disaster occurrence and impact in April 2006, the National Agency for Disaster Management (BNPB) has raised the challenge of Indonesia Disaster Management Information system. It is stated that Indonesia needs to develop effective Disaster Management Information System (DIMaS) to cope with geographical situation (archipelago country) together with time frequency and variety of disaster. In 2009, a generic disaster data model has been defined to handle several simple types of disaster data. Then in 2012, the disaster data model based on the spatio-temporal aspect is extended to handle natural and non-natural disaster data. These disaster data is limited only to the disaster data which can be predicted. The research that has conducted in 2014, aim to contribute more significance on spatial and temporal aspects of disaster management information systems. In theoretical and conceptual levels, this research is expected to fill the gap of any kind of disaster data representation including predictable and unpredictable disaster data. This paper presents two important aspects. First, a general architecture of spatio-temporal unpredictable data processing system in DIMaS is proposed. Second, the spatio-temporal data model which supports unpredictable data and moving object handling in DIMaS, is developed.
Keywords :
data handling; data models; emergency management; information systems; DIMaS; disaster data model; disaster data representation; disaster management information system; unpredictable data handling; Data models; Disaster management; Emergency services; Information systems; Object recognition; Spatial databases; Trajectory; moving object; natural disaster data; spatio-temporal; unpredictable;
Conference_Titel :
Data and Software Engineering (ICODSE), 2014 International Conference on
Print_ISBN :
978-1-4799-8175-5
DOI :
10.1109/ICODSE.2014.7062662