Day 1

28 November 2018

Data Analytics for AI & IoT


Data Analytics for AI and IoT: Chair’s Welcome and Opening Remarks


Keynote: Information is Everything

Data is the new oil is a familiar paradigm in 2018, but until we learn to process and derive actionable insights from this data how valuable is it?  This talk will cover a real life case study where a business has successfully taken data generated by the IoT and converted into into real business actions.  Hear about their journey, and their recommendations for uncovering new economic structures made available by access to intelligent data.


Panel: IoT and AI Data Analytics for Intelligent Decision Making

  • Identifying target-rich, high-value data that can be used to generate business intelligence
  • Using cloud analytics platforms to derive value from IoT data
  • Discussing the barriers to widespread IoT/ AI /Big Data value delivery and how these might be overcome.
  • Real time data analytics in practice – examples of how IoT / AI data is creating business efficiency and revolutionising working practices


Solo: Edge Processing for Data Analytics and Training AI Algorithms

  • How the huge influx of data will require fit-for-purpose architecture. What is the distance from the edge to your device and how to consider this during the creation of your IOT / AI architecture?
  • Discussing how IoT / AI architectures need to be put in place to ensure increased compatibility across domains.
  • Using cloud analytics platforms to derive value from IoT / AI data vs physical gateways -pros and cons.


Networking Break


Case study: Cognitive Anomaly Detection & Prediction for IIoT

Hear a real life case study about a cognitive anomaly detection and prediction within the Industrial IoT sector.


Panel: Raising the Bar – How Can IoT and AI Improve Our Performance and Fitness?

  • Many fitness companies are borrowing techniques from sports teams and integrating them into consumer IoT/AI technologies.
  • What are the issues surrounding data collection from these types of devices – who has access and ownership to this type of sensitive health data?
  • How can predictive analytics can play a role in improving sports performance in personal and a team setting?
  • Exploring innovations in smart textiles, sensors and platforms and examining which areas will provide future growth


Sport Science – The S.L. Benfica´s Approach

  • What is in fact Sports Science?
  • The importance of Multidisciplinary teams.
  • Data and meta-data analysis. Why to do it? How to do it? When to do it? What data?
  • Sports Science vs Data Science.
  • The crucial role of IT and IoT.
  • The Benfica Vision towards an holistic intervention in sport.


Networking Break


Solo: Beyond Predictive Analytics to Full Artificial Intelligence for the IIoT

The future of manufacturing and many other industries is moving from descriptive to prescriptive analytics and operational intelligence, and even beyond this to adopting machine learning and artificial intelligence into the management of its IoT devices.  What will this shift do the existing role of IoT in businesses?  What are the benefits and dangers to those using IoT devices?  What can predictive platforms: devices that can autonomously adjust parameters based upon measured and received data, and artificial intelligence that creates its own rules and outcomes based on learned experiences play within the modern business?  Real life examples from across the industrial IoT.  Finally this talk will address one of the fundamental issues with moving towards AI – Where should the responsibility behind AI lie?


Panel: Big Data – Creating Intelligent Data Models

  • The increased need for big data analytics to drive AI & Machine learning
  • How to successfully unlock unstructured data & transform into learnable features
  • The advancement of self-service big data tools & its benefit for your organisation


Solo: Can AI Replace Human Analysts?


Networking Break


Panel: Data and ML Architecture

  • Frameworks for data acquisition, Hadoop, Spark and more
  • Creating big data and ML pipelines to power algorithms
  • Model training and evaluation


Solo: AI, Big Data and Autonomous Vehicles


Session Close