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Use	
  Cases	
  of	
  Cyber-­‐Physical	
  Data	
  Cloud	
  
Compu8ng	
Kyoungsook	
  Kim	
  
(ksookim@nict.go.jp)	
  
Informa8on	
  Services	
  Pla>orm	
  Laboratory	
  
Universal	
  Communica8on	
  Research	
  Ins8tute	
  
Na8onal	
  Ins8tute	
  of	
  Informa8on	
  and	
  Communica8ons	
  
	
  
Cyber-­‐Physical	
  Data	
  Cloud	
  Compu8ng	
(C)	
  NICT	
 2	
	
 
CYBER SPACE	
 
PYSICAL/SOCIAL SPACE	
	
 
Sensors	
Smart phones	
Digital signage	
Sensing data	
 	
Actionable 	
information	
Physical sensing	
Social sensing	
Ubiquitous Internet	
Web	
 
Cloud	
collection, archive, organization,
manipulation, sharing	
 
 
Goals	
•  Real-­‐world	
  Awareness	
  Compu8ng	
  
–  Intelligent	
  cloud	
  compu8ng	
  to	
  autonomously	
  support	
  useful	
  (data/
informa8on/knowledge)	
  services	
  by	
  being	
  aware	
  of	
  rela8onships	
  between	
  
elements(objects,	
  events,	
  situa8ons)	
  in	
  the	
  real	
  world	
  
–  (Near)	
  real-­‐8me	
  interac8ng	
  with	
  the	
  physical	
  world	
  
•  Observa8on:	
  to	
  monitor	
  processes	
  in	
  physical	
  world	
  
•  Percep8on:	
  to	
  analysis	
  informa8on/situa8on	
  
•  Communica8on:	
  to	
  share	
  informa8on/situa8on	
  
•  Ac8on:	
  to	
  control	
  physical	
  elements	
  directly	
  or	
  indirectly	
  
(C)	
  NICT	
 3	
	
  
Observa8on	
  
(Monitoring)	
  
	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  Ac8on	
  
(Controlling)	
  
Percep8on	
  
(Processing)	
  
	
  
	
  
	
  
Data	
  Cloud	
  
Physical	
  world	
   Cyber	
  world	
  Awareness	
  
Communica8on	
  
(Networking)	
  
Cyber-­‐Physical	
  Social	
  Data	
  Cloud	
  Infrastructure
•  NIST	
  &	
  NICT	
  Collabora8on	
  Project	
  
R&D	
  of	
  a	
  cloud	
  pla>orm	
  specialized	
  for	
  collec8ng,	
  archiving,	
  organizing,	
  
manipula8ng,	
  and	
  sharing	
  very	
  large	
  (big)	
  cyber-­‐physical	
  social	
  data	
  
Standardiza8on	
Testbed	
=	
  Cloud	
  node	
join	
Cyber-­‐Physical	
  Social	
  Data	
  Cloud	
  	
  
Infrastructure	
  	
Applica8on	
Architecture	
  
Security	
  &	
  Privacy	
  
Data	
  Management	
  
Networking	
  
Cyber-­‐Physical	
  Data	
  Cloud	
  Applica8ons	
•  Topics	
  
–  Smarter	
  Healthcare	
  
–  Smarter	
  Disaster	
  Informa8on	
  
–  Smart	
  City	
  
–  Social	
  Life	
  Networks	
  
•  Passim	
  Situa8on-­‐aware	
  Applica8ons	
  
–  De-­‐centralized	
  
–  Ad-­‐hoc	
  
–  Rela8onship-­‐based	
  
–  Level	
  of	
  measurement	
  
–  Autonomous	
  
Use	
  Cases	
  (1)	
•  	
  Healthcare	
  data	
  publishing	
  &	
  sharing	
  
(C)	
  NICT	
 6	
disaster	
No	
  health	
  record	
  
:	
  cannot	
  con8nue	
  treatment	
  quickly	
Cloud	
move	
If	
  two	
  hospital	
  share	
  their	
  data	
  each	
  other,	
  
doctors	
  can	
  restart	
  the	
  treatment	
  	
  
without	
  overlapping	
  examina8on	
  pa8ent	
  
cloud	
  	
  
consumer	
  
cloud	
  	
  
consumer	
  
A	
  pa8ent	
  gives	
  hospital(doctor)	
  
the	
  authority	
  to	
  par8ally	
  	
  
access(read/write/copy/…)	
  his/
her	
  cloud	
  data.	
  
Data	
  is	
  dynamically	
  integrated(virtualized)	
  by	
  the	
  pa8ent	
  
Rela8onships	
  	
  
between	
  pa8ents	
  and	
  data	
  
<Problems>	
  
1)  Reserved	
  sharing	
  
2)  Global	
  schema	
  
3)  Sta8c	
  systems	
  
4)  Private-­‐Public	
  data	
  control	
  
De-­‐centralized	
  
Ad-­‐hoc	
  
Rela8onship-­‐based	
  
Level	
  of	
  measurement	
  
Autonomous	
  
Use	
  Cases	
  (2)	
•  Awarable	
  Loca8on-­‐based	
  Service	
(C)	
  NICT	
 7	
Now,	
  I	
  have	
  no	
  
idea	
  which	
  area	
  
will	
  be	
  dangerous	
Danger!	
Where	
  is	
  
my	
  family	
  
or	
  friend	
  
now?	
I’m	
  
here!	
How	
  can	
  I	
  escape	
  
from	
  the	
  dangerous	
  
situa8on?	
Geo-­‐Fencing	
  
Geo-­‐Advising	
  
Geo-­‐Q&A	
  
<Problems>	
  
1)  Monitoring	
  users’	
  loca8on	
  
2)  Request/Response	
  ac8vity	
  
3)  New	
  data(service)	
  adapta8on	
  
4)  Manually	
  publish/share	
  data	
  
5)  Private-­‐Public	
  data	
  control	
  
Ex)	
  	
  
-­‐  Automa8cally	
  "check-­‐in"	
  subscribers	
  
when	
  they	
  enter	
  a	
  (disaster	
  approaching/
event/favorite)	
  place.	
  No	
  ac8on	
  outside	
  
of	
  the	
  place.	
  	
  	
  
-­‐  Automa8cally	
  and	
  par8ally	
  “share”	
  my	
  
loca8on	
  
-­‐  Autonomous	
  service	
  discovery	
  and	
  
composi8on	
  depending	
  on	
  the	
  situa8ons
Use	
  Cases	
  (2)	
•  Globally	
  monitoring	
  and	
  locally	
  fencing	
  (safe	
  and	
  rapid	
  evacua8on)	
(C)	
  NICT	
 8	
advisory	
  
message	
GIS	
TsunamiAlert	
  
Event	
IncreaseAlert	
  
Loca8onEvent	
Alert	
  
(broadcas8ng)	
High	
  level	
  of	
  dangerous	
  
report	
  	
  
geoloca8on	
  	
  
WarningEvent	
HighLevelEvent	
It	
  starts	
  to	
  compute	
  risk	
  areas	
  
using	
  relevant	
  data	
  
and	
  generates	
  “alert”	
  event.	
  
Alert	
  
Peer-­‐to-­‐peer(Ad-­‐hoc)	
  	
  
communica8on	
  
ShelterNaviga8on	
  
Event	
Shelter	
  Informa8on	
  
(mul8cas8ng)	
  
It	
  starts	
  to	
  search	
  shelters	
  using	
  	
  
relevant	
  data	
  and	
  generates	
  “naviga8on”	
  event.	
  
*Japan	
  experience:	
  the	
  shelter	
  assessment	
  system	
  was	
  up	
  and	
  running	
  two	
  weeks	
  aler	
  the	
  disaster.	
  
coast	
  	
  
watch	
Shelter	
Aid	
  informa8on	
ShelterMonitoring	
  
Event	
Social	
  networks	
Remote	
  diagnosis	
Pa8entSitua8on	
AidSitua8on	
<Considera8on>	
  
1.  Physical	
  monitoring	
  
2.  Rela8onships	
  between	
  en88es	
  
3.  Real-­‐8me	
  data	
  aggrega8on	
  
4.  Situa8on	
  analysis	
  
5.  …	
  

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Cyber physical-data-cloud-computing-use-cases--kyoungsook kim-20120315

  • 1. Use  Cases  of  Cyber-­‐Physical  Data  Cloud   Compu8ng Kyoungsook  Kim   (ksookim@nict.go.jp)   Informa8on  Services  Pla>orm  Laboratory   Universal  Communica8on  Research  Ins8tute   Na8onal  Ins8tute  of  Informa8on  and  Communica8ons    
  • 2. Cyber-­‐Physical  Data  Cloud  Compu8ng (C)  NICT 2 CYBER SPACE PYSICAL/SOCIAL SPACE Sensors Smart phones Digital signage Sensing data   Actionable information Physical sensing Social sensing Ubiquitous Internet Web Cloud collection, archive, organization, manipulation, sharing  
  • 3. Goals •  Real-­‐world  Awareness  Compu8ng   –  Intelligent  cloud  compu8ng  to  autonomously  support  useful  (data/ informa8on/knowledge)  services  by  being  aware  of  rela8onships  between   elements(objects,  events,  situa8ons)  in  the  real  world   –  (Near)  real-­‐8me  interac8ng  with  the  physical  world   •  Observa8on:  to  monitor  processes  in  physical  world   •  Percep8on:  to  analysis  informa8on/situa8on   •  Communica8on:  to  share  informa8on/situa8on   •  Ac8on:  to  control  physical  elements  directly  or  indirectly   (C)  NICT 3   Observa8on   (Monitoring)                        Ac8on   (Controlling)   Percep8on   (Processing)         Data  Cloud   Physical  world   Cyber  world  Awareness   Communica8on   (Networking)  
  • 4. Cyber-­‐Physical  Social  Data  Cloud  Infrastructure •  NIST  &  NICT  Collabora8on  Project   R&D  of  a  cloud  pla>orm  specialized  for  collec8ng,  archiving,  organizing,   manipula8ng,  and  sharing  very  large  (big)  cyber-­‐physical  social  data   Standardiza8on Testbed =  Cloud  node join Cyber-­‐Physical  Social  Data  Cloud     Infrastructure   Applica8on Architecture   Security  &  Privacy   Data  Management   Networking  
  • 5. Cyber-­‐Physical  Data  Cloud  Applica8ons •  Topics   –  Smarter  Healthcare   –  Smarter  Disaster  Informa8on   –  Smart  City   –  Social  Life  Networks   •  Passim  Situa8on-­‐aware  Applica8ons   –  De-­‐centralized   –  Ad-­‐hoc   –  Rela8onship-­‐based   –  Level  of  measurement   –  Autonomous  
  • 6. Use  Cases  (1) •   Healthcare  data  publishing  &  sharing   (C)  NICT 6 disaster No  health  record   :  cannot  con8nue  treatment  quickly Cloud move If  two  hospital  share  their  data  each  other,   doctors  can  restart  the  treatment     without  overlapping  examina8on  pa8ent   cloud     consumer   cloud     consumer   A  pa8ent  gives  hospital(doctor)   the  authority  to  par8ally     access(read/write/copy/…)  his/ her  cloud  data.   Data  is  dynamically  integrated(virtualized)  by  the  pa8ent   Rela8onships     between  pa8ents  and  data   <Problems>   1)  Reserved  sharing   2)  Global  schema   3)  Sta8c  systems   4)  Private-­‐Public  data  control   De-­‐centralized   Ad-­‐hoc   Rela8onship-­‐based   Level  of  measurement   Autonomous  
  • 7. Use  Cases  (2) •  Awarable  Loca8on-­‐based  Service (C)  NICT 7 Now,  I  have  no   idea  which  area   will  be  dangerous Danger! Where  is   my  family   or  friend   now? I’m   here! How  can  I  escape   from  the  dangerous   situa8on? Geo-­‐Fencing   Geo-­‐Advising   Geo-­‐Q&A   <Problems>   1)  Monitoring  users’  loca8on   2)  Request/Response  ac8vity   3)  New  data(service)  adapta8on   4)  Manually  publish/share  data   5)  Private-­‐Public  data  control   Ex)     -­‐  Automa8cally  "check-­‐in"  subscribers   when  they  enter  a  (disaster  approaching/ event/favorite)  place.  No  ac8on  outside   of  the  place.       -­‐  Automa8cally  and  par8ally  “share”  my   loca8on   -­‐  Autonomous  service  discovery  and   composi8on  depending  on  the  situa8ons
  • 8. Use  Cases  (2) •  Globally  monitoring  and  locally  fencing  (safe  and  rapid  evacua8on) (C)  NICT 8 advisory   message GIS TsunamiAlert   Event IncreaseAlert   Loca8onEvent Alert   (broadcas8ng) High  level  of  dangerous   report     geoloca8on     WarningEvent HighLevelEvent It  starts  to  compute  risk  areas   using  relevant  data   and  generates  “alert”  event.   Alert   Peer-­‐to-­‐peer(Ad-­‐hoc)     communica8on   ShelterNaviga8on   Event Shelter  Informa8on   (mul8cas8ng)   It  starts  to  search  shelters  using     relevant  data  and  generates  “naviga8on”  event.   *Japan  experience:  the  shelter  assessment  system  was  up  and  running  two  weeks  aler  the  disaster.   coast     watch Shelter Aid  informa8on ShelterMonitoring   Event Social  networks Remote  diagnosis Pa8entSitua8on AidSitua8on <Considera8on>   1.  Physical  monitoring   2.  Rela8onships  between  en88es   3.  Real-­‐8me  data  aggrega8on   4.  Situa8on  analysis   5.  …