Discover the what, why, how, and where to start of delivering on the potential of complete, integrated real-time data, AI + IoT solutions: download our eBook.

With the rapid expansion of technology and improvements in connectivity, businesses today are constantly looking for ways to stay competitive, enhance efficiency, and optimise their operations.

Internet of Things (IoT) technology, with its ability to connect and monitor everything from an individual asset on a factory floor to entire operations spread over vast distances, has become a key enabler for the digital transformation of various industries and a means to achieving key business objectives.

However, the true potential of your real-time data is only unlocked when we combine it with bidirectional data flows and analysis in-the-moment, as well as advanced technologies like workflow automation, Machine Learning and GenAI that can predict an seize optimisations instantaneously.

Gain insights into the market landscape, trends, and applications of IoT, as well as an understanding of how to develop an implementation roadmap that incorporates real-time data, machine learning, and AI.

Understanding IoT in business
The complete IoT technology stack.
What are the different types of IoT platforms and which one do I need?
What’s the difference between Industrial IoT (IIoT) and IoT?

The power of real-time data access + analysis
Common sources and types of real-time data.

Machine Learning + Artificial Intelligence (AI) in IoT
Key machine learning techniques for IoT applications.
Role of AI in data analysis and decision-making.
How to incorporate machine learning and AI into IoT solutions.
Benefits of incorporating machine learning and AI into IoT solutions.

Market landscape + trends
Key trends in the IoT industry.
Innovative applications of IoT technologies.

Real-world applications
Potential industrial IoT use cases.

Selecting a platform
Scalability and flexibility.
Security and compliance.
Data integration and management.
Predictive analytics, Machine Learning and AI integration.
User interface and visualization.

Developing an implementation roadmap

Automation + AI for future performance improvements
The role of automation in IoT solutions.
Predictions for AI-driven industrial automation.
Opportunities for performance optimisation.
Challenges and considerations for AI and automation adoption.
Future outlook and AI recommendations.

Measuring ROI + Key Performance Indicators (KPIs)
Quantifying benefits and cost savings.
Monitoring performance metrics and KPIs.
Analysing data for continuous improvement.
Identifying new opportunities for IoT integration.