Unlocking IoT Potential: Strategic Approaches to Sensors and Communication
Date: Thursday, October 10 2024
Time: 10:00 PM (PST)
Location: Virtual
Register Here
SDV ADAS: Advanced Driver Assist Features
Building Intelligent Driver Monitoring (DMS) & Pothole Detection (PDS) on NVIDIA Jetson
Duration
2 Hrs
Preferred Date
NA
Preferred Location
Virtual
Time
12:00 PM CST
Register Here
About the Workshop
Modern vehicles are becoming intelligent, software-defined platforms—but safety still depends on how effectively we transform raw sensor data into real-time, actionable decisions. This workshop equips engineering teams to design and deploy Level-0 (alert-only) AI-driven ADAS features on NVIDIA Jetson, focusing on two high-impact capabilities:
- Driver Distraction Monitoring (DMS)
- Pothole & Road Hazard Detection (PDS)
Participants will gain hands-on insight into building edge-native AI pipelines that operate with sub-50 ms latency, without cloud dependency, and integrate seamlessly with in-vehicle and fleet systems.
Workshop ObjectiveÂ
Enable engineering teams to design, prototype, and deploy Level 0 (alert-only) AI-driven ADAS features on NVIDIA Jetson, focusing on driver distraction monitoring and pothole detection, with real-time edge inference and seamless system integration.
By the end of this workshop, participants will understand how to move from detection to actionable alerts while integrating AI insights into in-vehicle and fleet systems.
Who Should Attend
ADAS Engineering Teams
Auto Software Developers
Fleet Operations & Mobility Platform Teams
Why You Should Attend
Transition from reactive safety to predictive, AI-driven alerts
Achieve real-time edge performance without cloud dependency
Gain a clear roadmap from PoC to deployment
Reduce vehicle wear, improve safety outcomes, and lower operational costs
Key Takeaways
Practical understanding of deploying Level 0 ADAS on Jetson
Real-time ecosystem integration patterns
Multi-stage alert design strategiess
A clear roadmap from PoC to deployment
Hands-on exposure to DMS and PDS live demos
Agenda
Use Case 1: Driver Distraction Monitoring (DDMS)
Driver fatigue, distraction, and drowsiness are major contributors to preventable accidents. Reactive alerts are insufficient without temporal and behavioral context.
- Real-time facial analysis on Jetson
- Signals monitored:
- Eye closure (PERCLOS)
- Head pose deviation
- Gaze tracking
- Temporal behavior tracking across rolling time windows
- Intelligent outputs:
- Multi-stage alerts
- Event logging
- Immediate ADAS intervention triggers when required
- Reduced fatigue-related incidents
- Improved regulatory readiness
- Lower total cost of ownership
- Higher driver trust and acceptance
Use Case 2: Pothole Detection System (PDS)
Road hazards often go undetected, leading to safety risks, vehicle damage, and unplanned maintenance costs.
- Vision + IMU sensor fusion
- Real-time pothole localization and severity scoring
- GPS-tagged hazard events
- Trip-based damage reporting
- Adaptive severity classification
- Predictive heatmaps
- Driver-friendly UI prompts
- OTA model updates
- Privacy-first, edge-based data sampling
- Reduced vehicle wear
- Lower maintenance costs
- Improved ride comfort
- Smarter route planning through data-driven insights
Integration Architecture
- In-vehicle systems (IPC, cluster, CAN bus)
- Jetson integration node with:
- Protocol adapters
- Security layer (TLS, encryption)
- Data buffering and forwarding
- Cloud ecosystem:
- Event ingestion
- Analytics dashboards
- Model updates via OTA
- Discovery & Data
- PoC on Jetson
- Pilot Program
- System Integration
- Scale & Operations
- Driver Monitoring scenarios:
- Fatigue detection
- Distraction events
- Alert escalation
- Pothole Detection scenarios:
- Visual detection
- IMU correlation
- Map-based hazard logging
Target metrics include real-time latency, high confidence detection, and stable frame rates on Jetson.
- Technical deep-dive discussions
- Identification of pilot deployment targets
- Review of integration requirements
- Definition of success metrics
- Alignment on next-phase execution plan
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