IoT

4/28, 2016

Preferred Networks,

2

2012IT

3

??

IoT

IBM

3Web)

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4

Conjecture Edge-Heavy Data

5

Codd, 1970)

6

App1

App2

App3

App n

7

they are generating a tremendous amount of digital exhaust data, i.e., data that are created as a by-product of other activities.

http://www.mckinsey.com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation

1.

2.

3.

8

IEEE Second Workshop on Architectures and Systems for Big Data (ASBD 2013)

9

Edge-Heavy

2016, DIMo

10

418PFNRA

11

http://ascii.jp/elem/000/001/152/1152084/

FANUC

12

http://www.fanuc.co.jp/ja/profile/advertise/2016/20160418fieldsystem.html

Edge-Heavy Computing Edge Computing

13

14

https://www.youtube.com/watch?v=7A9UwxvgcV0

https://www.youtube.com/watch?v=7A9UwxvgcV0

16

https://research.preferred.jp/2015/06/distributed-deep-reinforcement-learning/

https://www.youtube.com/watch?v=a3AWpeOjkzw

IoT+ML

17

1.

2. ()

3. ()

DevOps

https://www.youtube.com/watch?v=a3AWpeOjkzw

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=

19

20

provenance ()

https://www.youtube.com/watch?v=a3AWpeOjkzw

GoogleMSGE

21

22

(IoT)

AI

Thank You

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IoT 22012ITIoTConjectureEdge-Heavy Data Codd, 1970) IEEE Second Workshop on Architectures and Systems for Big Data (ASBD 2013)2016, DIMo418PFNRAFANUC 13 14IoT+ML GoogleMSGE 22 23