White Paper

Discover the Future of IoT: Sustainable and Autonomous IoT Ecosystems

Explore how cutting-edge technologies and collaborative efforts are shaping the next generation of IoT solutions

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About this White Paper

At the Digital Transformation World (DTW) 2024 event in Copenhagen, several leading companies unveiled the groundbreaking Sustainable and Autonomous IoT Ecosystems Catalyst, showcasing innovative solutions to complex IoT challenges. The Catalyst project is a collaborative effort among:

  • Symphonica
  • AWS for Telecom
  • BT Group
  • TELUS
  • Intel Corporation
  • Red Hat
  • CGI
  • Innova Solutions
  • Ulster University

This Catalyst demonstrated how to replace current manual operations by developing automation solutions to enable autonomous control and optimization of IoT service delivery operations. The goal was to show how such an approach can improve network support for existing use cases while also providing a sustainable infrastructure suitable for future dynamic applications. In demonstrating these automated management capabilities for the IoMT, the Catalyst hopes to remove barriers to autonomous and sustainable IoT ecosystems.

Our white paper, “Sustainable and Autonomous IoT Ecosystems,” provides an in-depth look at this Catalyst project. It details how advanced technologies like Multi-access Edge Computing (MEC), AI, and machine learning are used to solve key IoT challenges.

Key Takeaways

  • Resource Optimization: Learn how to efficiently manage computational and network resources to reduce operational costs and achieve a sustainable environmental impact.
  • Data Privacy: Explore advanced anonymization techniques, such as video blurring, to protect sensitive data and comply with privacy regulations.
  • Automation: Understand how to reduce human intervention in IoT operations by enabling autonomous decision-making and self-management capabilities.
  • MEC Orchestration: Learn about the benefits of MEC orchestration in enhancing service continuity and optimizing resource allocation.
  • Telemetry and AI/ML Integration: Explore how real-time telemetry data, combined with AI and ML algorithms, drives informed decision-making and predictive analytics.

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