making sense of iot, m2m and big data
TRANSCRIPT
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Image Source: IEEE Spectrum
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The IoT Architecture
Information Value
Loop
ApplicationsAnalyticsData AggregationNetworksSensors
M2M
Big Data
IoT
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The IoT Equation
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Sensors – The Eyes & Ears
Cost of a Sensor
µ-Processor Clock Speed
Key Issues: Power Constraints Energy
Harvest Data Transfer Event-driven Security Encryption,
Bandwidth Interoperability Std. vs Prop.
Small, Low Power, Low Memory Devices
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Networks – The Lifeline
Home Area Network(Bluetooth, 6LoPAN, ZigBee, WiFi)
Neighborhood Area Network
(WiFi-Mesh, Cellular)
Wide Area Network(Fixed, Cellular WAN)
Key Issues: Coverage Range, Reliability Capacity Uplink-biased, Protocol
Overhead Security Authentication, Privacy Multiple Access Last Grasp, Sleep
Mode Addressing IPv6, Multicast/Broadcast Protocol s MQTT, COAP QoS Variability OFDM, DSCP
Too Many Devices, Too Many Types
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Data Processing – The Brian
SQL/NoSQL Queries
Key Techniques: Distributed Storage (Hadoop HDFS) Parallel Processing (MAP-Reduce, Apache
Pig/Hive/HBase) In-memory Processing (Apache Spark)
Too Many, Too Much, Too FastDATA BIG DATA
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Analytics – The Mind
Open-source Analytics Tools
Key Areas:Artificial Intelligence (AI)Machine LearningDeep LearningComplex Event Processing (CEP)Natural Language Processing (NPL)
Making Sense of Data
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Applications – The Life of IoT
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Case Study – Connected Vehicles
Autopilot Smart Charging
Solar Charging
Vehicle to Grid
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