Disasters have caused serious damage on human beings throughout their long history. In a major natural disaster such as an earthquake, a key to mitigate the damage is evacuation. Evidently, secondary collateral disasters is account for more casualty than the initial one. In order to have citizens to evacuate safely for the sake of saving their lives, collecting information is vital. However at times of a disaster, it is a difficult task to gain environmental information about the area by conventional way. One of the solutions to this problem is crowd-sensing, which regards citizens as sensors nodes and collect information with their help. We considered a way of controlling the mobility of such sensor nodes under limitation of its mobility, caused by road blockage, for example. Aiming to make a mobility control scheme that enables high-quality information collection, our method uses preceding result of the measurement to control the mobility. Here it uses kriging variance to do that. We evaluated this method by simulating some measurements and it showed better accuracy than baseline. This is expected to be a method to enable a higher-quality input to the agent-based evacuation simulation, which helps to guide people to evacuate more safely.

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