Key benefits

• Hazards surface as glowing AR markers in real time, projected directly into your surroundings
• Potential disruptions like closures or construction highlighted seamlessly, without menus or digging
• Community reports strengthen accuracy, creating a living, evolving awareness layer
• Shared instantly across the network—when one user sees it, everyone benefits
• Trust reinforced through a balance of AI detection and human validation

Experience overview

Crowdsourced Awareness transforms every Zynqar user into part of a shared safety network. Instead of waiting for delayed updates or relying on static icons, the system blends advanced detection with community input to create a dynamic picture of what’s happening right now.

Hazards aren’t hidden in lists—they appear as glowing signals in your field of view. A cluster of cones may warn of construction before you even approach it. Subtle markers might notify you of traffic stops or slowdowns. And when unexpected events occur, alerts pulse in the moment, giving you the chance to adapt instantly.

It’s not just information sharing—it’s awareness that grows stronger with every participant.

Core features

Intelligent Detection
The system identifies disruptions and conditions automatically, surfacing them without user effort.

Community-Strengthened Updates
Users can enhance and validate what’s detected, ensuring reliability and trust across the network.

Immersive Safety Markers
Warnings appear where they matter most—in the path ahead—through glowing cones, subtle overlays, or pulsing signals.

How it works

Crowdsourced Awareness fuses two streams: real-time detection and human insight. Automated scanning brings speed, while community contributions refine accuracy. Together, they create a loop where every observation enriches the system for all users, building a stronger layer of awareness.

Pipeline highlights

• Live detection — conditions identified as they emerge
• User input — confirmations and corrections improve accuracy
• Shared visibility — updates distributed instantly across the network

Validation process

Crowdsourced Awareness has been tested to ensure trust and reliability under varied conditions.

• Urban trials — handling construction, congestion, and bottlenecks
• User verification loops — reducing false positives through collective input
• Continuous learning — the system grows more accurate with every contribution