💸 TALON’s SPS API Fights Back Against Cloud Costs. Dynamic pricing + demand forecasting = 25% savings. Choose bundles (Basic to Ultimate) or pay-per-use—all optimized via Stackelberg game theory.

🔄 “Move Aside, Overloaded Node!”—TALON’s Task Offloader Why waste resources? Our orchestrator live-migrates tasks to idle nodes, cutting hotspots by 35%. Efficiency isn’t magic—it’s math. 🧮

📊 TALON's Dashboard Just Got Upgraded. TALON’s Grafana panels don’t just show cluster health—they predict fires. CPU/Memory/Disk trends + auto-healing alerts = ops teams breathing easier.

🥊 TALON’s Self-Healing Duo: Scale vs. Reschedule RULE 1: Scale replicas during CPU overload. RULE 2: Taint nodes + pod resets. Which won in Pilot 2? Spoiler: Both did. See the Node-RED flows in action!

🚨 Why 70% CPU Usage Triggers an Intervention. TALON’s Grafana rules (like excess_CPU_any_node) are tripwires for autonomous healing. No tickets. No delays. Just silent fixes.

♻️ Wasted Device Power? TALON Turns It Into Cash. Our SPS incentivizes sharing idle phones/laptops for edge computing. Earn discounts + boost participation.

🚀 TALON’s Pilots: Where Theory Met Factory Floors. In Pilot 2, we: • Cut energy 20% • Automated 100% of healing • Hit 70% non-commercial device use Real industry. Real results.

🔮 TALON’s Next Act? AI Forecasting. We’re evolving from reactive to predictive: Kafka queues + online learning + pre-emptive scaling. The future is autonomous.

🌍 TALON’s Recipe: 1 Part AI, 2 Parts Sustainability. Federated learning + energy-aware benchmarking + smart pricing = 20% less CO₂.

✨ Ready to Orchestrate the Unmanned Factory? TALON’s architecture is open, scalable, and battle-tested. Explore the deliverables. Pilot with us. Let’s build the self-driving industrial future—together.

🌐 Through a seamless edge-cloud architecture, TALON maximizes resource use, elevates performance, and reduces energy consumption across manufacturing ecosystems. • 90% reduction in latency between drone and edge nodes • 20% decrease in energy per autonomous flight

🚁 TALON’s unified autonomous UAV and autonomous vehicle trial achieves sub-10ms inter-drone coordination latency. AI-optimized swarm management now reduces energy draw by 30% while maintaining precision. 🔥 Data payload size downshifted from kilobytes to 16 bytes per message.

🏭 TALON’s Industry 5.0 Automation and Planning work package delivers unprecedented OEE gains. Target metrics include: • Quality yield raised to 99% (prior baseline 98%) • 79% machinery availability, translating to a monthly uptime increase of 7.2 hours

👓 TALON decreases AR-to-node latency by 90% (from 2 s to 200 ms). Our AR/VR pilot delivers expedited maintenance guidance and training with a 90.03% accuracy in environmental recognition. 🔧Personal protective equipment detection reached 96.4% mean average precision.

🤖 TALON’s accelerates safety inspection cycles by 75%. Units navigate industrial sites in 4 to 6 minutes (versus 20 to 25 minutes for manual teams) and enforce 100% PPE compliance through anonymized computer vision. 🛡️ Quicker notifications and more secure workplaces.

🔒 TALON delivers 100% preservation of personally identifiable information. Our facial and metadata anonymization techniques secure worker privacy in hazardous environments, while maintaining high detection precision. ✅ Oversight audit reported zero re-identification instances.

⚡ TALON’s untethered drone validation trial lowers average power draw to 20 W (down from 30 W+), achieving 94.7% accuracy in object detection. 🌿Reduce transfer size to 4 bytes (down from 16B) without loss.

🎯 TALON I5.0 field trials reveal: every 1% quality gain equates to €10K saved. AI-driven models target scrap reduction and dynamic machine uptime. 📈 Latest quality ratio: 98.54% (goal: 99.0%).

👷 TALON’s HRC pilot marries drones and AI to flag PPE violations in under 4 seconds. Current accuracy: 90%, inspection rate up 4x. 🚀 Next target: 70% fewer safety incidents on site.

🔮 Milestone: All pilots are running. Final KPI metrics in D5.4 (month 36). We’ll deliver: • Zero-touch AI orchestration • Blockchain-traced AI/ML artefacts • Federated learning for distributed edge models