- Intel IoT platform
- Intel IoT Platform
- Sensors and things
- Gateway
- transfer data between different types of networks
- some data processing as well
- moving quickly: different types of data
- flexibility is important for scalability
- PMA: protocol mapper and adapter (UPAL)
- Security
- not only data, but also physical security
- data storage
- physically distributed
- depend on the data types, and there are so many of them
- different users use the same data in many different ways
- provide different sets of APIs at business level
- Real world IoT challenges
- 3 major areas
- connected things and devices
- intelligence and the edge
- turn data in to insight
- different applications
- cities: e.g. drain block sensor network
- connected things and devices
- regulatory:delay tolerance
- harsh conditions: device robust
- long distance: zigbee is not useful anymore
- security
- intelligence ant ht edge
- low power
- OOB ML
- sensor fusion
- turn data into insight
- diverse ecosystem
- multiuse data
- data ownership
- smart grid
- high freq
- extreme reliabliity
- manageablity
- security
- demand response
- actuation
- data privacy
- data volumen
- public/private
- industrial
- legacy integration
- multi-protocols
- zero downtime
- security
- bespoke feeds
- data translation
- ML customisation
- enterprise/network
- integration
- business rules
- Smart cities
- future of flood management
- approach
- work with cicies
- city managers have the requirements and most of the experience
- prototype
- Intel IoT gateway: extend the life of equipment by make use of old equipments that already exists
- custom flood detecting sensor
- software and simulation in matlab (openTSDB)
- deploy and iterate
- deploy the implementation is time consuming and fruastrating for engineers
- iteration is important for this kind of experiment projects
- Smart grids: enernet
- put sensors in families and get their energy usage profiles
- and make use of these data
- Data center
- to increase visibility to resource usage
- Data analytics and machine learning Intel fellow
- what is machine learning
- a computer program learns, if tis performance improves with experience, Tom Mitchell
- 3 types
- superviesed learning: large amount of learning data, and people label data out
- unsupervised learning: make inferences without labeled data
- reinforcement learning: act in an env to maximize reward, real learning process
- why now, tech is decades old, why sudden hot now
- machine makes real decisions now
- big opportunity: extract value from data. things x data = value
- relationship to other workloads
- similar to high performance computing, and showing more and more similarities
- traditional: inside-out process
- emerging: outside-in process, from data to knowledge
- machine learning combines both of these 2 processes
- models
- algorithms
- database primitives
- graph algo
- machine learning
- numeric cmputing
- intel architecture-specific optimization
- key msg
- machine learning is the most significant emergin algorithm class today
- publicly available code is highly inefficent in terms of its parallelism-awareness
- code modernization: signle-node or distributed
- enhance both processor and tool chain
- how intel tools accelerate machine learning
- why deep learning is so exciting
- shallow learning: one layer
- deep network layers can apply to parallelism
- go deeper in the layers, the system learn and got more clear idea of the target
- Intel Xeon + FPGA (from Altera)
- Internet of things software standards unscrambled
- Creating a Model
- Simple Layer Model
- application and service <-> data & control points
- profiles, data & resource models
- how IoT devices are represetned to app and servcies
- how app and servcie interact vith the represetnations
- comms protocols <->
- high level protocols, multi-layers
- transports <->
- physical layers and low level protocols
- standards for locao IP, internet and cloud
- local to local via internet?
- cloud to cloud connect?
- deliverables
- traditional standard
- specification
- certification
- code
- for developers, open source projects, de facto standard
- IP
- trademark
- copyright
- patent
- standard
- intel is behind both IIC & OIC
- open source is changing the formation of standard. so intel is contributing open source code
- Future?
- never be one standard to rule them all
- recurring themes
- consistency
- low power and constrained services
- security
- machine to machine communication
- different user/admin will have different level of access
- IP, REST-based
- cooperation
- interoperation
- collaboration
- consolidation
- Realsense
- 3D camera and develope kit
- IoT (windriver & VxWorks)
- 2015 is the peak of inflated expectations
- tech wave: 1B+ desktop internet » 10B+ mobile device » 50B+ IoT
- 2 business interests
- optimization
- new efficientcies: more data of things that cannot collectable before
- transformation
- new revenue streams
- transitionsing business models
- positive shifts in value creation and value capture
- how to get started with IoT
- platform, integrited from left (things) to right (cloud)
- things side
- gateway
- cloud side
- network
- data center
- cloud analytics
- secure from end to end: edge-to-enterprise
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