Our Deliverable D4.1 presents a comprehensive report on middleware solutions designed to facilitate Edge-AI applications. This middleware enables seamless integration of AI capabilities at the edge, ensuring efficient data processing and reduced latency. The subsequent report, D4.2, refines these solutions,…
📚 Explore CLEVER’s contributions in the SS-CPS&IoT 2024 proceedings — from edge AI acceleration to quality-driven CPS design.
🧩 Cyber-Physical Systems + IoT are at the core of Europe’s tech innovation. CLEVER research contributes to green systems, trustworthy AI, and energy-efficient processors shaping tomorrow’s IoT.
📈 Class-wise precision and F1-scores from our marine debris study prove the robustness of CLEVER’s AI models — even with high in-class variance.
With DenseNet + NN, our models achieve 84% test accuracy, leading the way in automated underwater monitoring.
🌍 CLEVER’s research on green 6G AI ensures that as networks scale, they remain energy-efficient and secure. Learn how photonics + AI are converging for a sustainable digital future.
📡 Photonic-Aware Neural Networks (PANNs) make real-time cyber defense possible directly at 6G base stations. This means faster mitigation ⚡ and autonomous threat handling.
🧠 CNN architectures like ResNet, VGG19, and DenseNet power our AI-driven monitoring of deep-sea ecosystems. These tools help us protect oceans through automated, precise debris detection.
The future of 6G networks demands intelligent and sustainable security solutions. Our latest research, “Photonic-accelerated AI for cybersecurity in sustainable 6G networks,” introduces a novel approach using photonic-based Convolutional Neural Networks (CNNs) to detect Denial of Service (DoS) Hulk attacks…
🌊 Tackling marine debris with AI! Our research compares machine learning models (NN, SVM, XGB, LR, RF) for underwater debris classification. Neural Networks and SVM lead with up to 84% accuracy.
