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Morikawa Laboratory:Building a future with Big data

Building a future with Big data
Hiroyuki Morikawa (Networks and Mobile Systems)

 "Big Data" is the most popular new key word in the IT field today. Hopes are high for the potential to use big data to create new value in various fields. The Morikawa Laboratory (led by professor Hiroyuki Morikawa) is developing core big data technologies, as well as engaging in applied research in using big data to create innovative services, contribute to a safer and more secure society, improve industrial efficiency, and more. How will society change as the result of big data? We visited this cutting edge research laboratory, creating a new information society, to find out.
 


Morikawa Lab
The Morikawa Laboratory's "ROSSO System".
This area is used to provide demonstrations to visiting high school students, companies, and ministry officials.







PASERI
Verification testing of sensors for visualizing crop growing conditions. Development is also underway on a "Smart Greenhouse" which automatically controls the growing environment.




 

■ Big Data's Potential

RCAST Building 3 is home to the Morikawa Laboratory's verification testing space, "ROSSO System".
Big data-related verification testing and demonstrations are held in this stylish site. It doesn't have any large experimental equipment, but it is designed to allow flexible installation of sensors and actuators, and also serves as a living room for researchers. Professor Morikawa explains, "By conducting experiments in a living room, we are able to perform verification testing of big data applications that are tightly focused on people's daily lives."
Big data, as its name indicates, refers to massive collections of data. Not only is the amount of data large, but the data is also extremely diverse. Even as you read this, new data is constantly being created in real-time.
Professor Morikawa divides big data into two categories. The first is virtual data, generated by Internet-connected computers. This includes social networking data and online shopping purchase history data. The other is real data, produced by sensors and devices. Particular attention is being focused on this machine-to-machine (M2M) big data. "M2M big data has unlimited potential for improving productivity in areas such as agriculture, medical care, and distribution," says Professor Morikawa. That is because this M2M big data is "information which until now could only be recognized by expert observers."

 

■ Visualization of Crop Growing Conditions

The Morikawa Laboratory has developed numerous core technologies for collecting M2M data, such as sensor networks and wireless transmission technologies. Since last year 250 sensors have been installed inside RCAST, successfully collecting temperature, humidity, and other data at each sensor position and transmitting the data via the sensors. This technology has made it possible to collect data which was impossible to collect in the past. Merely collecting massive amounts of data, however, is pointless unless that information is then used. How can collected M2M data be put to use? "One possibility is agriculture. At the Morikawa Laboratory, we're now conducting verification experiments in which we visualize the growing conditions of crops," explains Professor Morikawa. Sensors have been installed in a greenhouse to measure weather data such as brightness. These sensors are collecting data on light transmission rates to estimate leaf surface areas. The leaf surface area can be used to predict optimal harvest times. Many farmers currently check fruit and vegetable growing conditions visually. A system which assessed growing conditions based on objective indices could potentially promote entry into the agricultural field by new farmers and lead to efficient agricultural management which doesn't depend on personal experience.


Crop Sensing Platform for Improving Agricultural Efficiency 区切り線

Farming relies on the experience and intuition of farmers. This creates a hurdle to new entry into the agricultural field, and produces inefficiency. Collecting and analyzing data could make farming efficient. This is the foundation of the new "evidence-based farming" agricultural management approach.

Why measure "light"?
Leaf growth is an indicator of crop growth. When plants have many leaves, they block out light, making the area under the leaves dark. Light transmission rate measuring sensors can be used to assess plant growth and help predict optimal harvest times.

Sensing Platform
PASERI:Photosynthetically Active Radiation Sensor for Evidence-based agRIculture
 

■ Solving Social Problems with Big Data

The Morikawa Labo is performing verification testing of big data applications not only in the agricultural field, but various other areas, such as earthquake monitoring, medical care, and infrastructure maintenance for bridges, roads, and more. Even if technology is not absolutely cutting edge, collecting a sufficient amount of data can make it possible to achieve levels of efficiency not possible in the past. "We don't just create technologies," explains Professor Morikawa, "we also focus on searching for social problems and using technologies in various industries."
An essential part of big data research is, after gathering data, to always be alert for possible ways it can be used, and to seek out the opinions of various experts. Professor Morikawa established the ICT Field Test Consortium and the New Generation M2M Consortium to provide these opportunities. The goals of these consortiums are the exchange of information with participating companies and the application of these technologies to benefit actual society.
Professor Morikawa plans to use big data in the future to provide public benefits, such as using it in urban development. "Big data shows us information which until now could only be recognized by expert observers. I hope it can be used to forecast the expenses that will be involved in tax collection and infrastructure maintenance, and help show which issues should be tackled through government policy and community action," he says. Big data offers unlimited potential. You can hear the joy Professor Morikawa feels in creating new industries and social systems when he says, "I want to expand the range of applications of big data to make peoples' lives even richer."


 
< Some of the big data application projects being implemented by the Morikawa Laboratory >
区切り線 Structure/earthquake Monitoring
Earthquake Monitoring
Steady monitoring is essential for maintaining the safety of public property and structures. Stream data (continuous chronologically ordered data) from acceleration sensors installed in buildings, bridges, and other sites which it has not been possible to monitor in the past makes it possible to perform structural analysis, including structure soundness evaluation.
  区切り線 Smart health management for a wide range of people - Health Monitoring Health Monitoring  Continuous blood pressure measurement can be used to help prevent lifestyle-related diseases and assist with cardiac rehabilitation for seniors. Ambulatory stream data and behavior history data are linked and used to create a usable stream database.

Researcher Profile

Professor Hiroyuki Morikawa
"I chose to go to university just by process of elimination. I haven't really made any of my life choices on my own," says Professor Morikawa indifferently. During high school he "wanted to go to law school, become a government official, and help steer the nation," but his best grades were in his science classes, so he chose to go to a science faculty, where he had a better chance of making it into university immediately upon graduation. He didn't plan on becoming a researcher, either. He received a recommendation, and went on to graduate school as recommended. His nature is to consider what life presents to him as fate and to do his best at it. He spent months working on his doctoral thesis, and when he submitted it, he says, "I felt a tremendous sense of accomplishment." While he may not have reached where he is by actively choosing and following a path, he reflects, "The future may have opened up for me by just letting the tide take me where it would."
 

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