Role of Cloud and analytics in IoT

1. Role of Cloud and Analytics in IoT
Dr.Selvaraj Kesavan
selvarajkesavan@gmail.com

2. Agenda
2
 Cloud and IoT
 Data collection, storage, processing and visualization
 Different IoT and cloud platforms
 Cloud infrastructure and platform services for IoT
 Security for IoT
 Architecture - Example

3. IOT & IIOT
 Billions of connected devices to server via network and deliver connected
industry solutions. The connectivity is just an enabler but the real value of
IoT is on data (business insight/data-driven economy).
 Use of smart sensors and actuators to enhance manufacturing and
industrial processes.
 Industry 4.0 focusses on the interconnectedness of machines and systems
to improve operational efficiency and productivity
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4. IoT- Key Technology Enablers
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(1) Cloud Computing
(2) Web 2.0 and 3.0
(3) Big Data and Analytics
(4) Evolution of high speed communication technologies

5. Technology Landscape
5
Industry verticals -
Dashboard
Platform and
services
Protocols and
Communication
Sensors ,Devices and
Gateway
Light
Sensor
Voltage
Sensor
Temp/
humidity
Vibration
Sensor
Ultrasonic
Sensor
Gas
Sensor
BLE
Sensor
GPS
Pi 3
gateway
Gateway
PLC
• Username/
Password
• API Security
• Data At
Transit
• Data At Rest
• Firewall
• DoS
prevention
• Certificates/
Encryption
• Policies
• SSO/MFA
Security

6. IOT- Sensors to Application
Beacons
Industrial
plants
Sensors
Senor/Machine
Parameters
Device Gateway
Edge
Analytics
Platform
Agent
Sensor
Data
Agent
IoT & Cloud platform
AnalyzeStore
Application
Alert
Data
Visualization
 Edge Devices/Sensors source for the real time data .
 Device gateway collects data from multiple edge devices, filter aggregate and ingest the data to the cloud
platform for further processing and analyzing
 IoT platform enable device onboarding, data ingestion, device to cloud and cloud to device communication
 Cloud platform receive data, store, process and generate insights
 Application helps to visualize the dashboard ,monitor and control the devices.
Monitor
and Control
Edge
Devices/Sensors
Device
Provision &
Onboard
Data Ingestion
Rules
Device
Management Compute Hosting
Security
Delivery

7. IOT Sensors &Gateway
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Acquire and Transmit
Beacon
Sensor
Device
Thing
Gateway
Monitor Transmit Aggregate Analyze Send to Cloud
Analyze and ActAggregate
Gateway Provides
 Authentication
 Data Filtering
 Edge Analytics
 Control and management
Communication between sensors and
Gateway , Gateway to cloud platform
using
 Zigbee
 BLE
 Wi-Fi
 RF
 LoRa
 MQTT
 AMQP
 CoAP
 HTTP/HTTPS
 NFC,TCP/UDP
 UART,SPI
Different field sensors/Devices
 Sensors: Temperature, pressure, accelerometer ,vibration ,RPM,
Beacons etc..
 Devices: Camera, activity tracker, smart glass etc..

8. IOT- Protocol
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Application Layer
Transport Layer
Network Layer
Data link Layer
Physical Layer
HTTP, MQTT, CoAP, AMQP, XMPP
TCP, UDP
IPV4, IPV6, IPSec, ICMP, 6LowPAN
ZigBee, BLE, Wi-Fi, LoRa, NFC, Cellular, ZWave

9. IoT & IIoT – Platform/Service requirement
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 Provision the device
 Onboard the device
 Authenticate & Authorize
 Data Ingestion from devices/Sensors
 Store the data
 Process the data
 Derive Meaningful insights
 Maintenance, failure prediction, classify, anomaly etc..
 View key performance metrics
 Alert/Notification
 Control floor assets/machines from remote
 Visualize the floor asset status

10. Device Provision, onboard and management
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 Hundreds of thousands to millions of IoT devices
deployed, it is essential to track, monitor, and
manage connected device fleets.
 Device Provision
 Connect and bootstrap
 Certificates and keys
 Device Registration and Decommissioning
 Register single, bulk
 Manage/Group Devices
 OTA
 Monitor State
 Decommission
 Remote troubleshoot
 Protocols and
Standard
 LwM2M
 OMA-DM
 MQTT
 TR-069
 Out-of-Band DM
 IBM MaaS360
 VMWare Airwatch
 ARM Pelion
 Cisco Meraki
Where to deploy the Tools ? Or Does DM available as Managed Service??

11. Data Collection, Storage and processing
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Data Collection Data Storage Data Processing Descriptive Tasks
Predictive Tasks• What can we do with Vast amount of data?
• Business process efficiency
• Improve quality of life
• Research
• How?
• Analyze the data
• How to analyze Terabytes of data ?
• Large repositories
• Complex data analysis techniques
• Distributed/parallel processing .
• Data warehousing -> Data analytics -> Decision
derived from data analysis.

12. 12
Data Collection, Storage and processing – Tools/Framework
 Storage( Data Lake, Data
Warehourse, Database )
 MS SQL, POSTGRESQL
,oracle SQL
 Mongo DB(Document) ,
Redis (Key-value)
,Amazon Redshift
(Columnar) , Cassandra
(Columnar), HBase
(Columnar) , Dynamo
DB(Document DB-
stores JSON/XML),
GraphDB (Neo4j)
 Processing Big Data
 Apache Hadoop
 Spark - distributed stream
processing
 Storm - distributed stream
processing
 Mango DB
 Casandra
 Talend –ETL
 Kafka – Event Processing
 Splunk – Log analysis
Platform
 Hive – Data warehouse
 Hbase – No SQL
 Pig- Scripting
 Zookeeper – Coordination
 Hadoop yarn – Resource
mgt
 Streams and Complex
Event Processing
 Kafka, AWS Kinesis, JMS ,
Azure Event hub, Google
pub/sub
Where to install Big Data Tools ? Who is providing process/memory/Storage/
Network Capabilities?
 Language/Tools
 Python, Scala, R, Java

13. 13
Data Visualization
 To capture and communicate insights from Big Data analytics, move from standard
reporting to more sophisticated visualization.
 Visualization -> presenting information in such a way that people can consume it
effectively.
 The most impactful visualizations are often the most interactive
 Explore and have a conversation with the data.
 it capitalizes on visual advantage to recognize and understand patterns, represents
a large amount of data in one place, and gives users access to actionable insights.
Heat Map Tag Cloud History Flow

14. How to Visualize Raw/Processed/Analytics output?
Applications/Visualization Tools
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Web Applications:
• Application that is accessed via a web browser over a
network
• JavaScript, CSS, and HTML5
• Web apps became really popular when HTML5 came
around and people realized that they can obtain
native-like functionality in the browser.
Native Applications:
• Native apps are written in languages that the platform
accepts
• Swift or Objective-C for iOS
• Java for Android
• C# for Windows Mobile
Hybrid Application:
• Combination of Native with Web Component
• Xamarin -Slack, Pinterest.
• React Native -Facebook, Walmart, Tesla, and Airbnb
• Titanium -eBay, ZipCar, PayPal
• Angular JS -PubNub Chat, YouTube on PS3
• Advanced BI tools – Power BI, Qlikview, Tableau

15. IoT Platform
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IoT Platform makes up the foundational building block for a true eco system. It enables
multiple stakeholder to work together and deliver.
 Device and sensor manufacturer
 Network and connectivity
 Cloud platform and service providers
 Application and tools provider
 Big data and analytics applications/vendors
 Users
Provides
 Device Management
 Connectivity Management
 Data Management/storage
 Managed service/Model
 Provision to application Development
 Security

16. IoT Platforms
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AWS IoT
Azure IoT
GE Predix
IBM Watson IoT
Thingworx
Google Cloud IoT
Bosch IoT
Mindsphere
Alibaba IoT
C3 IoT
Jasper
leonardo
Telit IoT
 Platform ability to centrally manage of
multiple devices at scale, provide
remote configuration, monitoring and
decommissioning.
 Facilitate seamless connection
between device to platform, platform
to device and direct connectivity
between sensors to platform.
 Ability to provide infrastructure, tools
to manage, store, process and real
time analysis of streaming data.
 Platform to host in public, private,
hybrid environments,
 Friendly environment, programming,
framework options to develop,
integrate, connect, host and run the
applications
 Platform capability to provide fine
grained security and data privacy.

17. IoT & IIoT – Non Functional requirements
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 Availability
 Scaling
 Interoperability
 Disaster management
 Deployment
 Distribution
 Automation
 Cost optimization
 Security

18. Cloud Platforms
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AWS
Azure
GCP
Alibaba
 PaaS and IaaS
 Ramp up or ramp down resource on need
basis
 Compute/memory/storage/GPU optimized
 Route the load to difference instances
 Virtual Network Environment
 Environment to host applications and run
 Auto scaling and Load Balancing
 Disaster management
 Automatic Deployment with Zero downtime
 Scaling and Elasticity
 Failure fallback
 Managed Machine learning, Deep Learning ,
Notification/Alert engine
 API management
 Identity and Access Management
 Compute, Storage, Network
 Serverless, Microservice
Open shift
Rackspace
Heroku

19. Programming/Connecting to Cloud Platform
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Programming Toolkits:
• Portal
• CLI
• Power Shell
• REST API’s
Front end Application:
• SDK’s
• REST API’s
Device/Gateway:
• Device SDK
• REST API’s

20. Core Services: VPC,EC2,S3,Glacier,EBS,RDS,Dynamo DB, IAM
Deploy Applications : EC2,Beanstalk
Highly available : Auto scaling ,Load Balancing
Automation: Cloud formation, Elastic Beanstalk, EC2 Run command
Decouple infrastructure: SQS,SNS, API Gateway, Lambda, Dynamo DB
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AWS Services

21. Security for IoT
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Application Security
Network Security
Device Security
User Security
Security applications and development tools to enable only trusted
instances of applications and tools communicating
Availability of communication networks, network connections and
prevent unauthorized access
Ensure devices securely join the network, authentication and
authorization as securing data within the devices
User - certificates, keys, user name/password, access token, SSO, MFA

22. Security and Identity Services
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Authentication :
- Allow Apps to authenticate on behalf of users
- Allow users
Authorization:
- Fine-grained access control
- Attribute management
- Policy evaluation
- Policy Management
Implementation:
OpenID- Created for federated authentication. User obtain account with OpenID
Provider and use the account into sign in with any other web services. Allows
communication between IDP and SP.
OAuth (Open Authorization) is for token-based authentication and authorization. Allows
users/application to access resources.
SAML: Security Assertion Markup Language. Open standard for authentication and
authorization.
SSO( Single Sign On) for Federation and Identity Management. One user name and
password to access multiple services.

23. 23
Monetization
 Subscribe
 Freemium
 Pay-for-use
 Data monetization
 API monetization
 Targeted Advertisement
 Revenue Sharing

24. IoT asset management and Predictive Maintenance

25. Thank You
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