The document discusses the impact of the Internet of Things (IoT) on cloud computing, big data, and analytics, emphasizing its pervasive nature and the need for real-time decision-making. It outlines the importance of various technologies converging with IoT, including artificial intelligence and data science, to improve customer insights and process efficiencies. The document highlights the necessity for standard analytical models and collaborative frameworks to ensure interoperability and enhance security within IoT ecosystems.

1. The Impact of IoT on Cloud, Big Data & Analytics
Syam Madanapalli | Chair, IEEE P1931.1 | Roof Computing

2. The Outline
2
Internet of Things The Impact Data Science for IoT

3. Everything has a State; Many Things need Data
3
User 1
Data
Thing
State
User 2
Data
User 3
Data
Internet

4. 4
The Internet of Things

5. The Characteristics of IoT that impacts Big Data
5
Scope
Objects, devices,
machines and
planets
Frequency
Connected and
continuous
Scale
Billions of devices
and peta bytes of
data

6. The Ecosystem of Ever Increasing Complexity
6
Convergence
of technologies
Artificial
intelligence
Humanization
of objects

7. Big data Analytics
7
Data Science for IoT has significant differences.
Recommendations
Planning
New features
New products
New staff
Customer targeting
Insights
Process improvement

8. Data Science for IoT
8
Data Privacy Working with hardware
Specific analytical models Realtime edge processing

9. The Need for Different Strategy for IoT Analytics
9
IoT is pervasive
computing
Direct impact on
connectivity & big data
IoT requires continuous computing while the data is in motion.
The need for realtime
decisions and actions

10. The Design Philosophy for IoT
10
An IoT system should have
various decision and automation
tools that operate and cooperate
autonomously within the context
of a local environment.

11. IoT and the Data Context
11
Context
History
Raw
data
InsightsRealtime actions
The Environment The Roof The Cloud The Rest of the World
Useful
data
Big data
Analytics

12. IoT and the Spatiotemporal Location
12
It is important to treat all events with respect to their spatiotemporal location!
If (this)
then (plan)
Time
Realtime
Near Realtime
Future
Roof
Fog
Cloud
If (this)
then (optimize)
If (this)
then (act)
If (this)
then (react)

13. Federated Analytics for the Internet of Things
13
Computing and analytics move downwards from Cloud for the IoT
DataServices
InformationServices
IntelligenceServices
TheEnvironment
TheRestofTheWorld
Context
Building
Storage
&
Analytics
Stream
Process
-ing
Reactions
Realtime
actions
Near realtime
actions
Predictive
actions
Information
sharing

14. Distributed Analytics
14
Establish peer-to-peer trust & reputation
Information sharing and collaboration
Cloud
Blockchain
Blockchain, machine learning, analytics and
IoT together will lead to Artificial Intelligence
to play a significant role in advancing the
civilization.

15. Security through Analytics
15
Roles&
AccessControl
NetworkSecurity
Contextual Fusion
Authorization
Authentication

16. The Need for a Standard Analytical Models
16
Standard IoT analytical services -
data processing, storage, remote
management and analytics.
This will allow interoperability,
portability and manageability as
well as to focus on innovation.

17. smadanapalli@gmail.com | @smpalli
Thank you!