The document discusses IoT and AI. It describes how IoT involves sensors collecting large volumes of varied data in real-time that must be processed and made sense of quickly. It outlines some technical challenges in storing and analyzing IoT data. It also presents common IoT architectures involving things, edge devices, and cloud components. The document further discusses major IoT platform vendors and provides an example of the AWS IoT platform and services. It raises questions about machine self-learning capabilities and proposes IoT with AI can provide real-time and batch data insights to enable smart systems.

1. IoT and AI
Lalit Bhatt
Nuro Technologies
https://tech.lalitbhatt.net

2. https://tech.lalitbhatt.net

3. IoT – Nature of Data processing
• Sensors everywhere
• Ability to process data in real time
• Storing the data for long term analytics
https://tech.lalitbhatt.net

4. Characteristic of Data
• Nature of Data:
• Volume
• Variety
• Velocity
• Veracity
• Technical challenges are manifold
• Need to process it and make sense of it.
• React quickly
• In Technical jargon
• Latency
• Throughput
• Fault tolerance
https://tech.lalitbhatt.net

5. IoT – Standard Architecture
Things Edge Cloud
Configuration
Application
and
Storage
Controller
Sense Act
May or may
not be
present.
Acts as a
Gateway.
May provide
local controls
also
User Management
Device
Management
APIEndpoints
Analytics
Machine Learning
Remember Security
Storage
Apps
https://tech.lalitbhatt.net

6. IoT – Major Vendors
• Microsoft Azure IoT
• IBM Watson IoT
• Amazon AWS IoT
• GE Predix
• PTC ThingWorx
https://tech.lalitbhatt.net

7. AWS IoT
Thing
Lambda
S3
RDS
Amazon DynamoDB
Amazon SQS
Amazon SNS
Message
Broker
Rules
Engine
There are more
services that can be
hooked like AWS
ElasticSearch
Scalability for most use cases is not an issue.
Cost implications.
https://tech.lalitbhatt.net

8. AI
https://tech.lalitbhatt.net

9. AI dilemma
Learning vs Self Learning
Can machine self learn or is it still learning extrapolated? What will happen when
machine will really start self learning
https://tech.lalitbhatt.net

10. Roger Penrose: Shadows of Mind
• Penrose hypothesizes that:
• Human consciousness is non-algorithmic, and thus is not capable of being
modelled by a conventional Turing machine type of digital computer.
Source : https://en.wikipedia.org/wiki/Shadows_of_the_Mind
https://tech.lalitbhatt.net

11. AI – Artificial intelligence
• There are known knowns; there are things we know that we
know. There are known unknowns; that is to say, there are
things that we now know we don't know. But there are also
unknown unknowns -- there are things we do not know we
don't know.
• Donald Rumsfield
https://tech.lalitbhatt.net

12. IoT with AI
DATA
https://tech.lalitbhatt.net

13. Promise of IoT with AI
• Smartness in everything in world.
• At what level it’s possible
https://tech.lalitbhatt.net

14. Promise of IoT with AI
• Insights:
• Descriptive
• Predictive
• Prescriptive
• Processing
• Real time
• Batch processing
• Pattern detection
• Anomaly detection
https://tech.lalitbhatt.net

15. IoT with AI – Reference Architecture
Source: http://lambda-architecture.net/https://tech.lalitbhatt.net

16. AWS IoT – AI
AWS Greengrass
AWS IoT
Analytics
AWS Kinesis
Stream
AWS Lambda SQS
PROCESSING INFRASTRUCTURE
AWS
ElasticSearch
AWS
DynamoDB
AWS RDS S3 Glacier
STORAGE INFRASTRUCTURE
AWS ML
AWS
Rekognition
AWS Polly AWS Lex
AI Platforms and Services
https://tech.lalitbhatt.net

17. Questions
https://tech.lalitbhatt.net