HORIZONTAL PLATFORMS OFFER FAST TRACK TO VERTICAL APPLICATIONS – APPLICABILITY OF ONEM2M TO SMART CITY AND SMART LIVING
Presenter: Omar Elloumi, oneM2M TP Chair, Alcatel‐Lucent (acknowledgment: the author thanks oneM2M members who provided input to this presentation)
oneM2M www.oneM2M.org
© 2015 oneM2M Outline
• Introduction • Technology trends • Smart cities • Smart living • take‐away
© 2015 oneM2M 2 IoT, the next internet evolution
And so what?
© 2015 oneM2M 3 It’s all about quality of life
Needs/enables Smart Smart Smart Home security/ buildings infrastructure mobility automation Smart Smart governance/ healthcare education Smart Smart Smart technology energy Health, fitness energy and lifestyle Smart grid‐micro grid
What makes cities smart What makes living smart (adapted from Frost & Sullivan report) (adapted from Ovum report)
There are more of this
© 2015 oneM2M 4 The IoT empowers a long tail of applications
Source: Alcatel‐Lucent
© 2015 oneM2M 5 TECHNOLOGY TRENDS
© 2015 oneM2M Trend1: horizontalization
NICHE VERTICALS BROAD ADOPTION Low volumes, high ARPC, high TCO High volume, low ARPC, low TCO
• Devices and Applications are designed as “stove‐pipes” • Devices and Applications are designed to collaborate • Devices dedicated for single application use across “clouds” • Solutions are closed and not scalable: duplication of • Devices are used for multiple application purposes dedicated infrastructure • Devices and Applications offering continuously evolve • High development & delivery cost • Easy app development and device integra‐tion through APIs and standard interfaces
Horizontal platform with common functions and interfaces
Source: Alcatel‐Lucent
© 2015 oneM2M 7 Trend 2: softwarization
Source: ITU‐T Focus Group IMT2020 © 2015 oneM2M 8 Trend 3: connectivity, plenty to chose from
Range (extended)
Native Low Power Wide‐area Access LTE enhancements 3GPP Cellular and/or CIoT (GSM/LTE)
Device cost (low) Device cost (high) Bitrate (low) Bitrate (high)
WPAN WLAN (e.g. 802.15.4, DECT (e.g. 802.11) ULE)
Range (low)
Source AIOTI, modified from an ALU contribution © 2015 oneM2M 9 Trend 4: Semantic interoperability
Source: Gridwise interoperability framework http://www.gridwiseac.org/pdfs/ © 2015 oneM2M 10 SMART CITIES
© 2015 oneM2M Vision for building smart cities
2. Digitalize and «sensorise»
1. Build a 3. Build vision Dashboards
4. Expand the vision, Integrate and Innovate
Source: Based on discussions with Dr. Martin Serrano, Insight centre © 2015 oneM2M 12 Smart cities: Challenge 1: integrate – role of open platforms
Automotive Home Energy e‐Health Applications Applications Applications Applications
Common Service Layer
Communication Devices & Hardware Communication Technologies & Protocols
Automotive CommunicationHome NetworksEnergy Health
Platform based integration Based on open standards
Source: CRYSTAL project/Philips
© 2015 oneM2M 13 Smart cities: Challenge 1: integrate – role of semantic interop things Things representation Source: AIOTI represents Common Service layer
Data (e.g. temperature) ontology
Metadata
Semantic description instantiates Other metada (e.g. digital right management and privacy related) Discovery – Consistency – Scalability ‐ Efficiency © 2015 oneM2M 14 Smart cities: Challenge 2: innovate
• App developer focus on app logic: use of Restful APIs • Hide WAN and Area Network How do I address technologies specificities the needs of app developers (interworking exposed as a service by the platform) • Free access to city open data – Controlled access to other data
© 2015 oneM2M 15 oneM2M based smart city deployment example ‐ Busan
Source: SKT © 2015 oneM2M 16 Smart city Busan use case examples
image
LoRa
© 2015 oneM2MSource: SKT 17 Smart city –takeaway • Enable scalable Smart City platform to support multiple vendor, protocol and industry standards
• Uniform service layer across range of applications, semantic abstraction, interoperability
• Ease of integration Smart City Platform
Control Vendor 1 Platform 1 Lighting App
• Big Data & Analytics Control Vendor 2 Lighting On2M2M Platform 2 • Storage App 2 service layer & • Application Mash Up Semantics Abstraction & data reusability (semantics) Video App Video Platform 1
Water Mgt App Water management platform
Source: Sierra Wireless © 2015 oneM2M SMART LIVING
© 2015 oneM2M Home/building automation challenges • For consumers, putting • Almost half of today’s together a smart home projects involve remains mostly a do‐it‐ multiple legacy control yourself project. protocols—such as [New York Times 2014‐ BACnet, LonTalk, DALI, 06] C‐Bus, Modbus, KNX, etc —that don’t interoperate. [knxtoday 2014‐04]
© 2015 oneM2M 20 oneM2M Interworking example – home automation Example implementation by KETI AllJoyn Google Nest
oneM2M oneM2M Interworking Interworking onePass Proxy Proxy App (for AllJoyn) (for Nest) Powertech Smart Plug Pebble
Open oneM2M oneM2M API Service Entity Service Entity AllJoyn(MN-CSE) (IN-CSE)Nest Dawon DNS Smart Plug
oneM2M
oneM2M oneM2M Jawbone Hue Service Entity Service Entity Open (IN-CSE) (IN-CSE) Open API API
OIC onePass oneM2M oneM2M onePass App Interworking Interworking App Proxy Proxy (for Jawbone) (for Hue)
Jawbone U24 Philips Hue ConnecThing App
© 2015 oneM2M 21 oneM2M Interworking example – home automation
Interworking Proxy Entity
AE AE IPE
Mca Mca Mca
CSE CSE
Mcc
OMA LWM2M
Source: Sierra Wireless © 2015 oneM2M 22 Continua example
Source: LNI and Interdigital oneM2M webinar © 2015 oneM2M 23 TAKE AWAY
© 2015 oneM2M Take‐away
• City – Every city is unique – Build a vision: initial set of use cases – Build an architecture that leverages cross sector applications using open standards – Stimulate and cultivate a collaborative culture for innovation • Living – All of the above – Citizen engagement is key. Projects should be participatory, inclusive and social.
© 2015 oneM2M 25 Big data is the new oil, clearing up mis‐perceptions
© 2015 oneM2M 26