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NICT REPORT 29packet transport capability can be quickly created via the cooperation between carri-ers and a third-party organization which efficiently and smoothly interconnects both the surviving optical network re-sources and various types of packet net-work resources. We first time demonstrat-ed the principles and successfully validated the feasibility of these technologies for di-saster recovery with experiments.Disaster-resilient wireless com-munication technology(a) Technology for enhancing regional networksIn a conventional system, the load is con-centrated on VPN servers and it is not possi-ble to establish multi-stage connections. To improve on this, we need mesh gateway functions to facilitate load distribution through the use of a mesh configuration for direct communication, improved reliability through redundancy, and improved security for IoT devices and the like in local independent net-works. To implement such functions, we have developed new technology for the construc-tion of logical independent networks in a mesh configuration using an L2 overlay net-work via a completely new wide-area net-work that combines mesh network technol-ogy, software switching technology, and multi-layer SSL-VPN connection technology that we have already developed (Fig.3).(b) Agile network configuration tech-nologyIn order to keep network functions avail-able for as long as possible using limited terminal batteries in the event of a disaster or the like, we are developing a smart-phone app that can control multiple wire-less devices installed in a smartphone to allow neighboring smartphones to work cooperatively. According to a computer simulation, the use of this app can be ex-pected to result in an overall reduction in power consumption of about 30%. Also, in the development of a seismic observation system that can be immediately deployed across a wide area, we have built a proto-type LoRa system that can remotely alter setting parameters. By measuring the ac-tual file transfer speeds, we have confirmed that this system is fast enough for transfer-ring data in the event of an earthquake.(c) Social demonstration and social implementationIn training for the support of people who have difficulty in returning home in Tokyo’s Chuo ward, and preparatory training for the establishment of a central Cabinet Office Disaster management headquarters in the Tachikawa district where there is a large-scale backup disaster management facility, we have contributed to training through use of the NerveNet system that we devel-oped as a means of ensuring communica-tions between disaster management cen-ters if the public telecommunications network is disabled. Also, in the R&D proj-ect aimed at the early detection of disas-ters by a network of acoustic and electro-magnetic sensors that we are working on as a SCOPE research project for the Minis-try of Internal Affairs and Communications, we have partnered up with Tohoku Univer-sity to develop an infrasound sensor device that combines a MEMS sensor with a Raspberry Pi. This device costs approxi-mately a hundred times less than conven-tional equipment. In field tests, we success-fully observed the infrasound waveforms accompanying a volcanic eruption.Real-time analysis of disaster in-formation from social knowl-edgeDuring real disasters such as extreme rain-fall in the northern part of Kyushu, people were able to make effective use of our disas-ter information analyzer system (DISAANA), which uses deep semantic analysis to ana-lyze information posted to Twitter during a disaster, and our disaster summarizer system (D-SUMM), which makes it easy to under-stand the disaster status of specified local authorities. These systems were also used in map-based disaster prevention drills in Oita Prefecture and Tokyo, and for civic protection training in Iwate Prefecture.In order to provide information of greater accuracy by analyzing not only Twitter tweets (the original target of these systems), but also real-world observation data, we have devel-oped a framework that crawls websites that provide weather forecasts and traffic informa-tion, and integrally analyzes this information in DISAANA and D-SUMM together with Twitter contributions.Data‐plane recoverySubstitute the broken communication equipmentControl & Management‐plane recoveryControl UnitADDUnitDROPUnitOSCHandshake UnitFirst‐Aid Units10G‐WDMtransport systemRestore the broken Control & Management‐plane by wireless accessControl & Management-planeFig.2 : Demonstrations of optical network quick recovery with the rst-aid units.Fig.3 : Development of mesh-like logic overlay networkResearch and Development