Highlights:✅ PQC deployment on DPUs for quantum-resilient networks✅ Middleware enabling adaptive AI applications✅ Concept drift frameworks for reliable edge intelligence✅ Sustainable photonics-powered AI✅ CPS & IoT security and trustworthinessCLEVER is building the foundation for secure, adaptive, and intelligent edge-cloud networks!…
This week we focused on:✅ PQC deployment at line-rate DPUs for quantum-safe edge communication✅ Middleware solutions for efficient AI application deployment✅ Concept drift detection for adaptive smart systems✅ Sustainable, energy-efficient AI and photonic networks✅ Strengthening CPS/IoT infrastructures with trustworthy AIStay…
This week we highlighted:✅ PQC deployment on NVIDIA DPUs✅ Middleware enabling AI at the edge✅ AI-driven data-driven decision making✅ Sustainable, energy-efficient technologiesStay tuned for more updates on cutting-edge edge-AI and quantum-resilient infrastructures! 🚀🌟 Explore more: www.cleverproject.eu
Our research focuses on energy-efficient solutions that minimize environmental impact. CLEVER contributes to sustainable, future-proof infrastructures for AI and edge computing. 🌟 Explore more: www.cleverproject.eu
Future 6G networks will merge intelligence and sustainability. Photonic-based AI drastically cuts energy consumption versus electronics. By performing inference in the optical domain, latency drops to sub-microsecond levels. Green computing becomes a built-in feature, not an add-on.🌟 Follow us on LinkedIn! Check…
Edge storage systems must minimize active nodes while respecting collocation, hardware, and privacy constraints. Our CATER framework achieves this with a hybrid optimization-heuristic approach, reducing energy consumption and data movement by up to 61%. 🌟 Follow us on LinkedIn! …
Proud to share our latest publication on synthetic tabular data generation and its impact on energy-efficient Digital Twins for Industry 4.0. In many industrial settings, real data is sensitive, incomplete, or hard to share—especially when it includes energy consumption, machine…
CLEVER is committed to developing sustainable technologies that reduce energy consumption and environmental impact. Our research aims to create solutions that contribute to a greener and more sustainable future.
CLEVER is committed to developing sustainable technologies that reduce energy consumption and environmental impact. Our research aims to create solutions that contribute to a greener and more sustainable future.
CLEVER’s research compares various machine learning models—Neural Networks (NN), Support Vector Machines (SVM), XGBoost (XGB), Logistic Regression (LR), and Random Forest (RF)—for underwater debris classification. Neural Networks and SVM lead with up to 84% accuracy, showcasing the potential of AI…
