There are more than 100 billion network-ready sensor devices around the world but as of 2013 only a small percentage of these devices
were actually connected and capable of sending data. More so, there is no existing platform capable of processing several 10’s of billions of
data records in several minutes. To address this, we will construct an ultra big data platform that far exceeds the scale of today’s big data
processing. Using this platform, we will use national and local public medical data and continuous measurement data to offer predictive and
preemptive healthcare and medical services, through which we will achieve Health Security that helps extend healthy life expectancy and
reduce medical costs. We also will aim to realize the social application of Factory Security, which will help eliminate cyberattacks on
factories and improve productivity and profitability by safely connecting control devices in factories into groups of one thousand units.
This program will be comprised of the following four projects and the Implementation & Utility project fusing together the results of each individual project.
Ultra Big Data creation Driver project (BDD)
Comprised of the “Narrow-area Wi-SUN System” (BDD1) and “Wide-area Wi-RAN System” (BDD2) subprojects (SPs). The former will use a distributed autonomous structure to develop a high-speed, efficient, smart wireless network that gathers data from monitors and sensors distributed over an area several kilometers wide. The latter will be in charge of a multi-hop, ultra wide area, highly efficient wireless relay line network that connects this area over a range of several tens of kilometers. These will be used to gather and control several tens of billions of records, generated daily while maintaining high reliability and a high response speed (several 10ms).
Ultra Big Data processing Engine project (BDE)
Based on the knowledge gained through the research results of the previous R&D support program (the FIRST Program), this project will develop a non-order-type big data engine capable of analyzing, within several minutes, the massive big data generated on a daily basis (several tens of billion records per year). This will be expanded to a cloud scale and implemented as an ultra high-speed processing engine.
Health Security project (HS)
Comprised of SPs that will develop simulators; for “Medical, Nursing Care and Social Risks” (HS1), using tens of billions of public medical big data records and conducting ultra high-precision macro estimates based on the individual, region, time, etc, and for “Cardiac disease Risks” (HS2), using consecutive-measurement big data collected in a super wide area
Factory Security project (FS)
Comprised of the “Connected Factory Simulator” (FS1) and “Malfunction/Attack Detection Algorithm” (FS2) SPs. The former will develop a simulator that outputs command flows to sequencer (PLC) assembly and processing machinery (robots) after a production plan is input. The latter will be in charge of a malfunction and attack early-detection algorithm that uses these results and real-time data from actual factories to improve factory health and productivity.
Approach to selection of institutions
For program success, the world‘s top researchers and research institutions have been selected in the fields of wireless communications technology, big data processing technology, health security, and factory security. The research structure is built around the following Project Leaders (PLs): Harada (Kyoto Univ.) whose track record includes his international leadership in wireless communications; Kitsuregawa (The Univ. of Tokyo) and Nagai (Jichi Medical Univ.) who have produced superb results in data information processing and medical information for the Cabinet Office FIRST Project; and Hayakawa who boasts a world class track record in the field of security/factory automation. The structure above will be the core, around which, new research institutions will be recruited as needed.
Keys of the implementation structure
- BDD (Wi-SUN and Wi-RAN) will be researched at institutions that have a track record in R&D, standardization, and commercialization for the respective topic.
- BDE will be researched at an institution that has a track record for non-sequential big data processing engines and has R&D and commercialization capability.
- HS will be researched at an institution that has access to national public medical and regional medical databases (from the perspective of access to regional medical databases, national receipt data analysis, national DPC (Diagnosis Procedure Combination) data analysis, and future social security needs estimation) and a track record in risk simulator development.
- FS will be researched at an institution that provides comprehensive FA solutions for productivity improvements, covering factory automation and even energy savings management. The institution will also have a track record in attack detection security based on international standards.
- Input from legal, business strategy, and international strategy advisers will be incorporated. Research outcomes will be proactively publicized through workshops and other events.
The Cabinet Office
ImPACT: An Ultra Big Data Platform for Reducing Social Risk
Associate Program Manager