حالياً ، الأنجليزية تستخدم إذا لم تتوفر لدينا ترجمات . *
Dear Crowd4U volunteers,
This is the “Crowd4U Digital Humanitarians” project. Our project aims to solve problems related to natural disasters in the collaboration between Human Intelligence and AI. For this purpose, we need your help, not only for the sake of our project but to help all the people affected by the huge flood in Japan.
* Example photo of a flooded area
As you know, huge floods occurred in many areas of Western Japan in July 2018, because of the seasonal rain front. In Japan, the last huge floods causing over 100 mortalities occurred in 1983, that was 35 years ago. Now, the flood in 2018 affected many prefectures, and central and local governments are struggling to collect and accumulate as much information as possible about disaster damages. At the moment we still do not have a whole picture of damage situation. To build an effective disaster response and life reconstruction it is essential to have a clear idea of the damage situation in all of the affected area.
Many responders and volunteers have already prepared for visiting the affected area in order to support survivors. In addition, we can provide support from outside the disaster area. Crowdsourcing, in fact, has the potential power to realize outreach support. Crowdsourcing team could detect inundated areas and flooded buildings through the overlaid satellite images on the building base-map.
To complete this mission the most severe issues are “the urgency” and “human resources”. Now, we believe in the realization of this project and in the creation of an effective and fast disaster response, with your help. Furthermore, we will appreciate if you ask your friends and other disaster volunteers to help with this important project. We are confident that with your help we can do it!
Crowd4U Digital Humanitarians Project is supported by JST CREST CyborgCrowd Project, and develped from the collaboration of University of Tsukuba, University of Toyama and Kyoto University.
© 2018 Kei Horie Photography