Building Intelligent connected products using Artificial Intelligence, Cognitive & Blockchain.
In this session, we will look at how to build intelligent connected products using a generic Enterprise IoT stack. We will discuss some of the key enabling technologies such as Artificial Intelligence, Machine Learning, Cognitive IoT and Blockchain and how to infuse intelligence at each layer of the IoT stack.
The session would cover 3 architecture patterns - Applying intelligence at the Edge, At the cloud and Hybrid approach. Various use cases would be covered - Real-time-decision at the edge using computer vision (security and surveillance), Cognitive IoT in Sports, Connected Car and Trust and compliance for security and connectivity using Blockchain.
The session will also include a brief analysis of different Enterprise IoT platforms like IBM Watson IoT, GE Predix, Amazon IoT, Microsoft Azure IoT and open source software for building smart connected products.
Outline/structure of the Session
The session would start off with an generic Enterprise IoT Stack, providing an end to end view on how to build intelligent connected applications.
Followed by 3 architecture and use case patterns - Building intelligence at the Edge, At the cloud and Hybrid approach and demystify each layer of the IoT stack
2. Edge Computing - Topics covered would be analytics at the edge, deep learning and computer vision at the edge ( real examples/scenario) using deep learning framework.
3. Cognitive IoT - Cognitive IoT and use cases on connected cricket - expert guidance for batsman and bowler using embedded IoT and algorithms solution.
Connected Car use case - personalization and expert guidance. How to create machine learning models for IoT using connected car use case.
4. Trust and compliance using Blockchain - Use case covered would be smart contracts, manufacturing and after sales services
- Understand End to End Enterprise IoT stack
- Edge Computing and Deep Learning - Strategy for building and deploying computer vision technologies at the Edge.
- Cognitive IoT - Approach to build cognitive applications
- Use cases on Cognitive IoT - Realize Connected Cricket use case
- Edge and Cloud - Realize Connected Car use case.
- Approach to build IoT machine learning models
- Trust and compliance using Blockchain
Technical Audience (IoT, AI and ML)