3. 3
2014년 8월 24일 새벽 3시 20분
왜 잠에서 깼을까요?
NAPA
OAKLAND
SAN JOSE
SANTA CRUZ
4. 4
2014년 8월 24일 새벽 3시 20분
- 나파밸리에 규모 6.0의 지진발생
NAPA
OAKLAND
SAN JOSE
SANTA CRUZ
5. 초연결 사회의 시작
- Hyper-connected Society is coming
We are here!
Connected Things > People
5
6. 사물인터넷(Internet of Things)
- IT산업에서 가장 빠르게 성장하고 있는 분야
IoT
M2M
Source: Gartner's 2013 Hype Cycle for Emerging Technologies
6
7. 7
History of Internet of Things : ~ 1990
1832
사무엘 모스(Samuel Morse)
최초의 모스 코드 전송
"What hath God wrought?"
from Washington, D.C. to Baltimore.
1844
전신기의 발명
(Electromagnetic Telegraph)
by Paul Schilling in Russia
1926
ARPANET 개발
세계 최초의 패킷
스위칭 네트워크로
현재의 인터넷의 원형
1974
1969
TCP/IP 개발
Domain Name System
(DNS)의 시작
1984
니콜라스 테슬라(Nikola Tesla )의 Colliers 잡지 인터뷰:
"When wireless is perfectly applied the whole earth will
be converted into a huge brain, which in fact it is, all
things being particles of a real and rhythmic whole.
… We shall be able to communicate with one another
instantly, irrespective of distance.
… A man will be able to carry one in his vest pocket."
1989
WWW(World Wide Web )의 시작
by Tim Berners-Lee(TimBL)
1876
전화기
by Bell,
Gray
8. IPv6 시작
인터넷에 연결되는
기기의 폭발적
증가를 대응
8
History of Internet of Things : 1990 ~
1990
WearCam의 발명
by Steve Mann
1994
최초의 인터넷 디바이스
'89 INTEROP 컨퍼런스에서
John Romkey는 TCP/IP로
컴퓨터에 연결되어 원격으로
on/off 가능한 토스터기를 시연
1999
최초의 인터넷 냉장고
by LG
Internet of Things 용어 등장
MIT Auto-ID Center의 공동 설립자인
캐빈 애쉬턴(Kevin Ashton)은 “화장품
가게에서 립스틱을 찾지 못하는 일이
발생했는데, 이를 찾으려다 새로운
방식을 적용하게 됐다” 말함
2003
2000
iPhone 출시
by Apple
RFID의 시대
미 국방부(US Department of
Defense)와 월마트를
시작으로 다양한 분야에
RFID가 활용되기 시작함
2011
2008 ~ 2009
IoT 시대의 시작
Connected Device > People
*Source: Cisco
2007
1992 최초의 스마트폰
사이먼(Simon by IBM)
1995
9. IoT 기술 로드맵
기술 발전
소프트웨어 에이전트 및
진보된 센서 융합 기술
소형화, 전력 효율적인
전자제품 및 적용 범위 확대
실내에 있는 사물들의
위치 정보 신호 감지
비용절감을 통한 2세대
애플리케이션의 확산
신속한 물류 지원
감시, 보안, 의료,
교통, 식품 안전,
문서 관리
물류, 재고 관리 및
분실 방지를 위한
RFID 태그 공급망 관리 지원
사람 그리고
일상사물의 위치
추적
원격운영 및 원격
현장감: 원거리
사물에 대한 제어
및 감시
유비쿼터스의 확대
수직 시장 애플리케이션
물리적인 월드 웹
2000 2010 2020 시간
Source: SRI Consulting Business Intelligence
9
10. IoT 디바이스의 지능화 수준
위치 정보 태그가
부착된 수화물
“I’m here and haven’t
moved in 11 hours”
반려동물 ID 태그
“I’m Fido 122”
음료수 캔
“Let me point to content”
지능형 가로등
“I’m off, Turn me on?
But there is still daylight”
주차 미터기
“Forty-four minutes
left on meter”
집안 조명
“Turn me on remotely”
스마트 카
“Satellite navigation
rerouting, using traffic flow
monitors and crowd alert”
스마트 벤딩 머신
“Imminent stock-out of
soda, I’m reordering”
청소 로봇
“It’s 9 a.m. Time to work”
수동형 사물
(Passive Object)
응답형 사물
(Responder Object)
능동형 사물
(Autonomous Object)
사물 +
컨텍스트 정보
(Object +
Context Information)
10
사물 자체만의 정보
(Object-Only
Information)
정보가 없거나
또는 일반적인 정보
(No Information or
Generic Information)
11. 11
최신 IoT 사례 : Sproutling Smart Baby Monitor
“Sproutling Smart Baby Monitor” Video
https://www.youtube.com/watch?v=slyXHix8hLg
12. 12
최신 IoT 사례 : Sproutling Smart Baby Monitor
- 아기의 수면 습관을 관찰 및 학습하고 예측
아이용 웨어러블 밴드
• 심장박동수 스마트폰
• 체온
• 움직임
• 자세
• 취침 여부
• 예상 기상 시간
• 외부 소음
• 심장 박동수 이상
14. IoT 기반 융합 서비스 분야
분야 활용 예 CAGR 2017
Telematics
텔레메틱스, 차량 종합관리(Fleet Mgmt), 운전자 성향 보험(Usage Based
Insurance), 인포테인먼트(Infotainment) 17% $834M
Farming
인터넷에 연결된 농업 장비(Connect farming equipment), 농산물
모니터링(Monitoring crops), 가축 모니터링(Monitoring livestock)
15% $661M
Industrial Automation
제조 장비 자기 관리(Manufacture equipment self-management), 원격 장비
모니터링(Monitoring remote equipment)
Utilities
스마트 미터(Smart meters), 그리드 자기 관리(Grid self-management), 태양광
발전 및 풍력 발전 시설 관리(Solar and wind power plant management) 8% $468M
Home
Automation
난방 시설, 조명 시설 및 가전 제품의 원격 제어 및 모니터링(Remote
monitoring and control of heating, lighting, appliances.)
16% $417M
Security
가정 및 기업의 보안 감시(Home and business security and surveillance), 스마트
화재 경보(Smart fire alarm), 원격지 감시(Remote video monitoring)
Health
Care
자택치료(Homecare), 노인 부양(Elderly care), 원격 의료(Tele-health), 응급
구조(Emergency help) 15% $355M
Retails
스마트 키오스크(Smart kiosk), 디지털 신호기반 타깃 광고(targeted
advertisement based on digital signage) 14% $209M
Source: Infonetics 2013
14
15. Value Added Service
& Service Enablement
IoT 기반 융합 서비스의 중요성
Source: “Designing an M2M Platform for the Connected World”, Beecham Research
> Network
15
16. The IoT Value Chain
- 애플리케이션 | 네트워크 | 디바이스
Core Network
Service Enablement & Delivery
Area
Network
Gateway
IoT Services
End User
Applications
Business Operations
Application Domain Network Domain Device Domain
16
17. Managing Complexity
- 수많은 기기에서 발생하는 빅데이터의 실시간 처리 기술 필요
17
CEP 즉, Complex Event Processing
기술은 다양한 소스에서 발생하는
방대한 양의 복잡한 이벤트를
실시간으로 감지하고 대응하는 기술
Big Data Fast Data
Data at Rest Data in Motion
Mine large static Files Process Events at high Velocity
Analyze Later Analyze Now
On Disk In Memory
Hadoop, MapReduce, NoSql Complex Event Processing (CEP)
19. 19
Cascading Architecture
- Devices Gateways Servers
• 이벤트가 발생하는 디바이스
단에서 기본적인 필터링,
통계 처리, 룰 적용 등을 수행
디바이스 단에서의 의사결정
• 노이즈 제거 등 서버 단으로
불필요한 데이터가 전달되지
않으며 다수의 스트림 간의
연관관게 분석 등을 광의의
이벤트 처리를 수행.
21. 스마트 그리드
- ENERNOC
• 전력 블랙 아웃과 같은 재난을 미연에 방지하고, 녹색
에너지 사용을 촉진하고자 설립된, 전력 수급 조절
기업인 EnorNOC은 미국 각 지역에 설치된 전력망
설비로부터 실시간으로 데이터를 수집하여, 전력 수급
대응을 성공적으로 수행
• 스마트 그리드 (Energy Demand & Response Solutions)
- ‘에너지 인터넷’이라고 불림
- 4개의 솔루션(DemandSmart[Killer App],
EfficiencySmart, SupplySmart, CarbonSmart)을 통하여
실시간으로 기업이 필요로 하는 전력 소요량을
측정하여, 이를 전력 공급망과 매칭을 시킴
- 이를 위하여 각 지역에 설치된 전력망(송배전 배선로,
변압 설비, 사용자측 설비)에서 실시간으로 수집되는
데이터를, 역시 실시간으로 분석하여, 전력 수급 대응
액션을 취함
21
23. 샌프란시스코 스마트 주차 관리 시스템
- San Francisco Parking Management
• The global first implementation of a
city wide “smart” parking
management system and technology
to manage parking supply and
demand more intelligently.
• “We have sensors at 8,200 of the
city’s 27,000 metered parking spaces,
and we get information from the gate
arms at the city’s 14 garages”
23
24. 스마트 자동차 관리
- Delphi Connect
• Delphi Connect is a small device that allows drivers
to monitor and control their vehicle remotely via the
Verizon LTE network.
• The device connects to the on-board diagnostics
port found in all vehicles made after 1996, and
monitors information about the vehicle’s overall
health, such as battery voltage, fuel level, and
engine status.
• The device sends drivers alerts for maintenance
issues, so that they know what is wrong before they
take their car in to be serviced.
• The device includes GPS, so vehicle owners can see
both historical maps of when, where, and how far
they have driven, as well as real-time information
about their vehicle’s location.
• Drivers can use their smart phone to control their car,
such as remotely locking or unlocking the doors.
Parents can enable additional controls to monitor
their teenage drivers, so that they receive an alert if
their children leave a pre-established geographic
region or go over a set speed limit.35
24
26. 스마트 해충 방제 시스템
- Z-Trap
• Z-Trap is an electronic insect trap that helps farmers
remotely monitor an insect population and protect
their crops from insect damage.
• In 2010, insects cost U.S. farmers around $20 billion
in damaged crops and an additional $4.5 billion for
insecticide.13 Z-Trap helps prevent crop damage by
using pheromones to trap insects and then compile
data on the number of different types of insects in
the trap.
• Z-Trap wirelessly transmits the data, including its
GPS coordinates, allowing farmers to view a map of
the types of insects that have been detected.14 By
remotely monitoring pests, farmers can place traps
at a density dictated by specific needs, thereby
saving time and money and minimizing the use of
insecticides.
26
28. 스마트 공공 쓰레기통 관리 시스템
- BigBelly
• BigBelly is a solar-powered trash receptacle and
trash compactor that alerts sanitation crews when it
is full. Waste management facilities use historical
data collected from each BigBelly bin to plan their
collection activities and make adjustments, such as
adjusting the size of a receptacle.
• BigBelly systems are found throughout cities,
corporate campuses, college campuses, parks, and
beaches. Boston University has reduced its pickup
from an average of 14 to 1.6 times a week.
• The university not only saves time, but also energy
since its trash collectors are using fewer garbage
bags and producing less CO2 during trash pickup.
Given that household waste is expected to rise to
2.2 billion tons by 2025 from the current 1.3 tons
produced now, additional tools will be needed to
handle higher volumes of trash.
28
30. 개인화된 건강관리와 새로운 라이프스타일 경험
- Nike : Nike+ , FuelBand
30
• Nike+ platform represents a shift
for NIKE from a "product" to a
"product +" experience.
• Fuelband monitors active lifestyle
of 8 million users on a daily basis
• Current data grid volume is
approximately 150,000 request per
minute with about 40 million
objects at any given time on the
grid
32. 토목 구조물 안전 모니터링의 필요성
- Smart Bridge
• I-35W 다리 붕괴 사건
– 미국 미니애플리스 도심과 미네소타 대학교를
이으며 미시시피 강을 가로 지르는 다리
– 1967년 완공 되어 2020년 교체 예정이었음
– 2007년 8월 1일 아침 출근 러시아워에 다리가
붕괴되는 사고(13명 사망, 100여명 부상)
• 오래된 토목 건축물에 대한 안전 감시
체계의 필요성
– 온도, 진동, 긴장도 등을 모니터링 하는 센서 설치
• 한국 진도 대교에서 실험 중
32
Key Messages:
CSPs have a unique opportunity to deliver innovative IoT solutions and grow revenue
The money will not be in delivering M2M connectivity, but in delivering value added IoT services
CSPs will require a flexible, re-usable, and scalable technology platform to address the plethora of IoT services to come
Oracle provides the industry’s most comprehensive portfolio of capabilities to power CSPs’ IoT offerings
So, how can service providers seize the IoT and M2M revenue opportunity?
From this diagram it is clear that that value added service and service enablement revenues represent a much larger share of a company’s spend than connectivity revenues.
Let’s look at this diagram in more detail.
The bars in purple represent revenues that CSPs can earn from basic network connectivity. There is incremental growth in connectivity revenues.
However if you look at the light blue bars for service enablement services (which include enablement platforms that provide API’s and building blocks for M2M applications, such as device configuration, diagnostics and over-the-air updates) the rate of growth for SE services outstrips connectivity revenues.
The dark green bars denote value added service revenues, which represent M2M application and services revenues, and these represent a much larger portion of the spend in M2M.
Let’s take a look at the classical ETSI architecture for M2M.
This architecture is composed of a device domain, a network domain, and an application domain.
The device domain includes the various M2M devices: the telematics control unit in a car or truck, security cameras, smart meters, smart smoke alarm, health monitoring devices and so on. Device gateway are also part of this domain.
<CLICK>
The network domain includes various types of networks, wireline, or satellite, but mainly mobile networks, traditionally 2G and 3G and lately 4G networks. M2M area networks are often used to connect devices to a public network.
<CLICK>
The application domain includes 3 main types of applications: applications implementing the M2M services such as your telematics applications, 3rd party or client applications such as Facebook, Pandora, Netflix, but also ad-hoc applications implemented by independent developers and published to an apps store, and those used to manage your business and operations such as CRM to handle customers, charging and billing systems, and the system used to fulfill orders and provision and activate M2M services.
<CLICK>
The 3 different types of application in the application domain often need interactions with each other and use Service Enablement and Delivery applications to interface with the network.
Other applications of the Oracle stack include leveraging our middleware, analytics and technology in smart city deployments, including the SF Park initiative in San Francisco.
This is a global first implementation of a city wide “smart” parking management system and technology to manage parking supply and demand more intelligently.
In this project, they have deployed sensors at 8,200 of the city’s 27,000 metered parking spaces, and they obtain information from the gate arms at the city’s 14 garages”
This IoT solution is powered by Oracle Service Bus, Oracle BI Analytics, ADF and Oracle RAC Database
Other applications of the Oracle stack include leveraging our middleware, analytics and technology in smart city deployments, including the SF Park initiative in San Francisco.
This is a global first implementation of a city wide “smart” parking management system and technology to manage parking supply and demand more intelligently.
In this project, they have deployed sensors at 8,200 of the city’s 27,000 metered parking spaces, and they obtain information from the gate arms at the city’s 14 garages”
This IoT solution is powered by Oracle Service Bus, Oracle BI Analytics, ADF and Oracle RAC Database
Other applications of the Oracle stack include leveraging our middleware, analytics and technology in smart city deployments, including the SF Park initiative in San Francisco.
This is a global first implementation of a city wide “smart” parking management system and technology to manage parking supply and demand more intelligently.
In this project, they have deployed sensors at 8,200 of the city’s 27,000 metered parking spaces, and they obtain information from the gate arms at the city’s 14 garages”
This IoT solution is powered by Oracle Service Bus, Oracle BI Analytics, ADF and Oracle RAC Database
Other applications of the Oracle stack include leveraging our middleware, analytics and technology in smart city deployments, including the SF Park initiative in San Francisco.
This is a global first implementation of a city wide “smart” parking management system and technology to manage parking supply and demand more intelligently.
In this project, they have deployed sensors at 8,200 of the city’s 27,000 metered parking spaces, and they obtain information from the gate arms at the city’s 14 garages”
This IoT solution is powered by Oracle Service Bus, Oracle BI Analytics, ADF and Oracle RAC Database
Other applications of the Oracle stack include leveraging our middleware, analytics and technology in smart city deployments, including the SF Park initiative in San Francisco.
This is a global first implementation of a city wide “smart” parking management system and technology to manage parking supply and demand more intelligently.
In this project, they have deployed sensors at 8,200 of the city’s 27,000 metered parking spaces, and they obtain information from the gate arms at the city’s 14 garages”
This IoT solution is powered by Oracle Service Bus, Oracle BI Analytics, ADF and Oracle RAC Database
Nicole Otto, Sr. Director of Consumer Digital Technology discussed the vision of the Nike+ platform, a platform which represents a shift for NIKE from a "product" to a "product +" experience. There are currently nearly 8 million users in the Nike+ system who are using digitally-enabled Nike+ devices. Once data from the Nike+ device is transmitted to Nike+ application, users access the Nike+ website or via the Nike mobile applicatoin, seeing metrics around their daily active lifestyle and even engage in socially compelling experiences to compare, compete or collaborate their data with their friends. Nike expects the number of users to grow significantly this year which will drive an explosion of data and potential new experiences.
To deal with this challenge, Nike envisioned building a shared platform that would drive a consumer-centric model for the company. Nike built this new platform using Oracle Coherence and Oracle Exadata. Using Coherence, Nike built a data grid tier as a distributed cache, thereby provide low-latency access to most recent and relevant data to consumers. Nicole discussed how Nike+ Digital Sports Platform is unique in the way that it utilizes the Coherence Grid. Nike takes advantage of Coherence as a traditional cache using both cache-aside and cache-through patterns. This new tier has enabled Nike to create a horizontally scalable distributed event-driven processing architecture. Current data grid volume is approximately 150,000 request per minute with about 40 million objects at any given time on the grid.
Nicole Otto, Sr. Director of Consumer Digital Technology discussed the vision of the Nike+ platform, a platform which represents a shift for NIKE from a "product" to a "product +" experience. There are currently nearly 8 million users in the Nike+ system who are using digitally-enabled Nike+ devices. Once data from the Nike+ device is transmitted to Nike+ application, users access the Nike+ website or via the Nike mobile applicatoin, seeing metrics around their daily active lifestyle and even engage in socially compelling experiences to compare, compete or collaborate their data with their friends. Nike expects the number of users to grow significantly this year which will drive an explosion of data and potential new experiences.
To deal with this challenge, Nike envisioned building a shared platform that would drive a consumer-centric model for the company. Nike built this new platform using Oracle Coherence and Oracle Exadata. Using Coherence, Nike built a data grid tier as a distributed cache, thereby provide low-latency access to most recent and relevant data to consumers. Nicole discussed how Nike+ Digital Sports Platform is unique in the way that it utilizes the Coherence Grid. Nike takes advantage of Coherence as a traditional cache using both cache-aside and cache-through patterns. This new tier has enabled Nike to create a horizontally scalable distributed event-driven processing architecture. Current data grid volume is approximately 150,000 request per minute with about 40 million objects at any given time on the grid.