Applied IoT & Analytics

Chairpersons welcome and opening remarks. 

• Supply chains building resiliency through the IoT. 
• Responding to demand – the full reboot of supply chains after 2021. 
• Combining IoT sensors and digital capabilities like blockchain and digital twins for process optimisation.  

• Understanding where to utilise digital twin technologies – when to implement and the steps for a successful result.  
• Simulation and digital twins – where does the accountability lie?  
• Considering the next steps for optimisation – input as well as output data, progressing from digital twins to digital prototypes?  
• How to grow the implementation of digital twins across industries. 

• Providing unparalleled insights across environments – the best market product for reduced costs and risks? 
• Understanding the digital transformation process for implementing digital twins.   
• Progressions in this space, e.g. AWS’s IoT TwinMaker 
• Real-life examples of digital twins in practice. 

• Using ML to derive ‘relevant’ data.  
• A closer look at latency, robustness and reliability of the data being used for ML models.  
• Examples of ML in the manufacturing space. 

• Digitalising the factory floor – getting the digital transformation steps right to implement fully autonomous processes.  
• AI, ML, automation, digital twin – knowing where these technologies come into play to optimise processes.  
• Leveraging predictive analytics to stay ahead of potential errors or failures.  
• A sustainable focus on products and services – the advantages of a circular economy approach.  

• The progressions of AI, ML and additive manufacturing in IIoT – the challenges and solutions.   
• Transforming employee capabilities with these technologies.  
• Utilising Edge for optimum response rates and data led decision making.  
• Reaching KPI’s through IoT enabled process optimisation

• Improving business resilience through data led decisions. 
• A look at sustainable practices and having a future focus – the shift to a more sustainable and human-centric approach.   
• Human centricity – empowering the team and utilising digital services like connected work applications.  

• AI and ML advancements to tackle errors in IoT. 
• Combining the capabilities of AI and IoT for risk predictions and rapid response.  
• Driving infrastructure resilience through AI and ML. 

• Collaborative robots in automation, the benefits for ROI.  
• Increased flexibility for the human workforce.  
• The future through hyper-automation enabling lower operating costs and new revenue streams.

• A holistic approach – how to move data from A-B, keeping in mind SSP (security, safety, privacy).  
• Working to collect ‘intelligent’ data and contextualising insights. 
• How to find the balance between standardisation and flexibility for quick response and optimisation.  
• AI, dashboards and digital twins – how employees are key in the decision-making process to optimise technology led systems.

• The key to democratisation through data interoperability.  
• How to approach data movement. 
• Digital democratisation – giving employees the ability to utilise data and build solutions.

To follow soon …

View day 2 content here:  IoT Connected Enterprise 

IoT Connectivity | Smart Cities | Edge | Smart Infrastructures | Industry Use-cases