Camera Applications Archives

What AI-Powered Vision Means for Workplace Burn Prevention in High-Risk Industries

Ram PrasadFebruary 5, 20260

Burn injuries at work can frequently be traced back to routine conditions that are in place longer than they should be. Hot zones remain exposed during changeovers. Chemical handling areas run with small leaks or residue. Temporary wiring and open panels persist during maintenance windows. The risk is in plain...

What are the Certifications required by Intelligent Transportation Systems?

Dilip KumarJan 30, 20260

Camera-based Intelligent Transportation Systems (ITS) cannot operate in isolation. Roadside cameras, controllers, sensors, and compute units must function within strict engineering, safety, and procurement frameworks to be deployed in public infrastructure. Therefore, compliance remains a top priority. Without it, no traffic enforcement system, smart signal controller, or edge camera can...

How Multi-Sensor Vision Powers Biometric eGates for Modern Border Control

Ranjith KumarFebruary 2, 20260

Biometric eGates form a key part of the automated border and transit infrastructure. Airports, seaports, and high-traffic land crossings use these systems to process rising passenger volumes while meeting identity verification and operational targets. Every eGate uses multiple vision inputs that operate together within a tightly timed interaction. Facial cameras...

How Edge AI Cameras Help Public Surveillance Systems Reduce Compliance Risks

Ram PrasadJanuary 28, 20260

As public surveillance expands across cities, the tension between operational monitoring and strict data privacy regulations intensifies. Legacy systems that stream raw video to central servers create significant compliance exposure around personal data collection and evidentiary integrity. This blog explores how modern Edge AI cameras fundamentally shift this paradigm by

From ADAS to Robotaxi: How Vision Systems Must Level Up to Meet New Mobility Use Cases (Part 2)

Suresh MadhuJanuary 27, 20260

Robotaxis operate in dense urban settings where lighting changes rapidly, motion stays constant, and perception runs continuously. Camera performance governs how lanes, signals, vehicles, cyclists, and pedestrians are readable. Hence, features such as HDR, low-light capture, global shutter, and more determine how reliably scenes get interpreted. In this blog, you’ll

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

Suresh MadhuJanuary 21, 20260

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,

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

Ram PrasadJanuary 28, 20260

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

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

Dilip KumarJan 9, 20260

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

What Vision Systems Can Do To Protect Pedestrians at Crosswalks

Dilip KumarDec 31, 20250

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...

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

Prabu KumarJanuary 8, 20260

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