Day 1

27 June 2018

Data analytics for AI & IoT

Topics including:
  • Big Data
  • Edge processing
  • Data analytics for sport
  • Predictive analytics
  • Data architecture


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

Hans Schepers

Data Scientist Precision Horticulture Monsanto


Associated Talks:

10:10AM - Day 1

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Peter Jackson

Chief Data Officer

Southern Water

Associated Talks:

10:10AM - Day 1

View Panel: IoT and AI data analytics for intelligent decision making

11:45AM - Day 1

View How to build a team and get business value out of AI

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  • 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
. Hans Schepers, Data Scientist Precision Horticulture Monsanto, Monsanto
. Peter Jackson, Chief Data Officer, Southern Water


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


Cognitive Outcomes: The Magical Formula Behind Smart Manufacturing

Michael McDaid

Sales Director Europe

Progress DataRPM

Associated Talks:

12:10PM - Day 1

View Cognitive Outcomes: The Magical Formula Behind Smart Manufacturing

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Industries across the spectrum are witnessing data explosion. With the data we’re generating every day now running into beyond humanly manageable proportions (and 80% of it being unstructured), the time has come for manufacturers to scale up with cognitive predictive maintenance. Join this session to learn how you can leverage the IoT data into meaningful insights to get real-time equipment health updates on the go to facilitate agile, smart decisions.

. Michael McDaid, Sales Director Europe, Progress DataRPM


Solo: Can AI replace Human Analysts?


Networking Lunch


Solo: Beyond predictive analytics to full artificial intelligence for the IoT

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

Filippo F.G. Della Casa

Head of Analytics

Leithà – Unipol Group

Associated Talks:

02:40PM - Day 1

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  • 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
. Filippo F.G. Della Casa, Head of Analytics, Leithà – Unipol Group


Networking Break


Data and ML architecture

  • Frameworks for data acquisition
  • Creating big data and ML pipelines to power algorithms
  • Model training and evaluation
  • Designing a scalable and robust infrastructure
  • How to utilize cloud-based systems for complex computing


Solo: AI, Big Data and Autonomous vehicles


Session Close