Combining relational and NoSQL database sstems for processing sensor data in disaster management
|Autoren|| Reinhard Stumptner|
|Editoren|| A. Quesada-Arencibia et al.|
|Titel||Combining relational and NoSQL database sstems for processing sensor data in disaster management|
|Buchtitel||EUROCAST 2015 Computer Aided Systems Theory Extended Abstracts|
Disaster or emergency management systems should implement a good action plan to handle effects of any emergencies. As time moves on in a disaster situation, and consequently more data becomes available – presuming that environmental sensors can be used and data from humans on site (helpers or inhabitants) can be collected – disaster managers get a good picture of the ongoing situation in the concerned area.
In order to reduce losses of any kind, property or human life, during an emergency situation, emergency managers should identify and/or anticipate potential risks in time, in order to reduce the probability of a disaster or to better react on it. It is essential to include procedures for determining whether and when an emergency situation would occur and at what point of time an emergency management plan should be activated.
In the frame of the research project “INDYCO” a disaster management prototype was developed . One aim was to have the possibility of easily integrating new data into the data base of the system and another one to process even huge sensor data streams near real-time. Using a net of various types of sensors, e.g. “multimedia sensors” or “social sensors”, a heterogeneous sensor data set has developed.