Sensor and ISPTechnology Deep Dive

Clear HDR vs DOL HDR: Which HDR Technology is Right for Your Application?

Prabu Kumar
Embedded vision applications require the camera image sensor to capture a clear image under challenging illumination conditions, with no motion artifacts. The Sony STARVIS 2 image sensor family will meet this requirement by supporting advanced HDR modes, including clear HDR and DOL HDR, enabling high-end embedded vision cameras to deliver...
Camera ApplicationsEdge AI Vision KitsMobility

From ADAS to Robotaxi: How Vision Systems Must Level Up to Meet New Mobility Use Cases (Part 1)

Suresh Madhu
ADAS-era vision systems handled short, supervised driving tasks with limited scene scope and intermittent operation. Robotaxi deployments replace that model with continuous, fleet-scale autonomy in dense urban settings, where cameras face constant motion and lighting swings. These conditions raise pressure on imaging consistency, synchronization, and data continuity. In this blog,...
Camera ApplicationsSmart Surveillance

3D Mobile Mapping for Digital Twins: Camera Features That Ensure Accuracy

Ram Prasad
Digital twins depend on how accurately physical environments are captured, reconstructed, and updated over time. Mobile mapping systems feed imaging data of streets, facilities, and structures into photogrammetry and SLAM pipelines to create virtual models. Therefore, camera performance determines if a digital twin can support simulation, planning, and monitoring with...
Sensor and ISPTechnology Deep Dive

Sony Pregius IMX264 vs. IMX568: A Detailed Sensor Comparison Guide

Prabu Kumar
IMX264 and IMX568 both belong to the Sony Pregius family of image sensors, which feature global-shutter pixels. Both sensors are renowned for their sensitivity, low noise, and distortion-free imaging, and are well-suited to high-speed vision applications, especially those requiring light sensitivity. While both sensors belong to the same Pregius family,...
Camera ApplicationsSmart Traffic

How ALPR Cameras Empower Violation Ticketing Systems to Help Law Enforcement Agencies

Dilip Kumar
Urban traffic enforcement faces scale pressure as vehicle density rises and manual monitoring struggles to keep pace. ALPR-based violation ticketing systems address this gap through camera-led capture, edge processing, and backend automation that records, verifies, and processes violations across multiple zones in parallel. From high-speed capture in uncontrolled traffic conditions...
Edge AI Vision KitsOur Product Insights

What is Secure Boot and How Does it Safeguard Edge AI Vision Deployments?

Prabu Kumar
Edge AI vision systems execute inference and data processing directly on embedded devices deployed outside controlled environments. Any compromise during startup can expose firmware, models, or connected sensors before applications even load. Secure Boot addresses this risk by enforcing a hardware-rooted chain of trust that validates every stage of the...
Camera ApplicationsSmart Traffic

What Vision Systems Can Do To Protect Pedestrians at Crosswalks

Dilip Kumar
Urban intersections have become complex, unpredictable zones where vehicles, cyclists, and pedestrians intersect within seconds. While signal-based systems handle timing, they rarely perceive intent or movement patterns. Human error, poor lighting, and limited visibility continue to cause pedestrian injuries across cities. However, not every crosswalk requires enforcement-grade accuracy. In most......
Autonomous Mobile RobotsCamera ApplicationsEdge AI Vision Kits

What Sensor Fusion Architecture Offers for NVIDIA Orin NX-Based Autonomous Vision Systems

Prabu Kumar
Autonomous edge AI vision systems depend on synchronized inputs from cameras, LiDAR, radar, IMU, and GNSS to interpret motion and depth in real time. On NVIDIA Orin NX platforms, even minor timing offsets between sensors can disrupt perception, leading to depth misalignment, tracking drift, and weaker inference outcomes. GNSS-disciplined sensor...
Camera ApplicationsSmart Traffic

What AI Vision Brings: Traditional vs. Modern Traffic Enforcement

Dilip Kumar
Modern traffic enforcement relies on vision-led systems that interpret full road scenes in real time. Traditional inductive loops used to focus on vehicle presence, which limited insight into movement patterns, intent, and safety risk. AI vision cameras bring scene awareness through continuous visual analysis, enabling cities to detect violations, assess...
Camera Applications

Top 5 Imaging Requirements Every Drone Needs for Reliable Surveillance

Ram Prasad
Drones now support continuous, real-time monitoring across large or hard-to-reach areas such as coastlines, forests, and dense urban zones. Hence, it’s important for surveillance cameras to handle long flight durations, weather exposure, and continuous data streaming. After all, the footage quality directly shapes situational awareness. In this blog, you'll learn...