Camera Applications

Get insights into how embedded cameras are revolutionizing various applications across the industrial, retail, and medical markets.

Dilip Kumar

Dilip Kumar is a computer vision solutions architect having more than 8 years of experience in camera solutions development & edge computing. He has spearheaded research & development of computer vision & AI products for the currently nascent edge AI industry. He has been at the forefront of building multiple vision based products using embedded SoCs for industrial use cases such as Autonomous Mobile Robots, AI based video analytics systems, Drone based inspection & surveillance systems.

What AI Vision Brings: Traditional vs. Modern Traffic Enforcement

Dilip KumarDecember 30, 20250

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

Top 5 Imaging Requirements Every Drone Needs for Reliable Surveillance

Ram PrasadDecember 23, 20250

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

How to Ensure Wrong-Way Driving Detection With AI Vision Cameras

Dilip KumarDecember 19, 20250

Wrong-way driving remains one of the highest-risk events on highways and ramps, driven by impaired driving, poor visibility, and entry confusion. Traditional monitoring methods struggle to react during the first few seconds, when response speed matters most. AI vision cameras are now reshaping how ITS teams detect, verify, and respond

Proactive Road Safety: Detecting Near-Miss Incidents with AI Vision

Dilip KumarDecember 11, 20250

Road networks are under pressure as traffic grows and junctions stretch human awareness. Near-miss analytics step in with real-time insight, turning close calls into measurable indicators of where risk concentrates. This moves safety planning from delayed crash reports to forward-looking intelligence across intersections and expressways. AI vision gives cities a

How Edge AI Cameras Enhance Risk Management and Yield Recovery in Precision Farming

Ram PrasadDecember 10, 20250

Edge AI cameras give farming teams a steady flow of field visuals that expose leaf color shifts, canopy gaps, soil texture changes, moisture imbalance, and early pest traces long before manual scouting can catch them. Continuous imaging also helps crews understand how growth changed through each stage, which zones began

How Intelligent Cameras Help Monitor Public Transport and Emergency Lanes

Dilip KumarDecember 5, 20250

Dedicated lanes for buses and emergency vehicles face growing misuse as cities struggle with congestion. Vision systems help supervisors track lane activity with real-time proof, vehicle classification, and automated alerts. These systems also link to larger ITS platforms that handle logging, escalation, and time-based enforcement. This blog shows you how

Why PPE Non-Compliance Is a Hidden Risk – and How Smart Cameras Can Fix It

Ram PrasadDecember 5, 20250

Industrial floors shift constantly as lighting, movement, and workloads change throughout the day. These shifts make manual PPE checks unreliable across aisles, platforms, and machinery zones. Smart cameras study posture, visibility, and motion to spot missing helmets, vests, gloves, or boots in real time. In this blog, you'll get expert

Slips, Trips & Falls How Smart Cameras Can Prevent These Critical Workplace Hazards

Ram PrasadDecember 10, 20250

Workplace slips, trips, and falls keep rising across factory floors, warehouses, service corridors, and public zones where hazards appear suddenly, and inspection cycles miss fast-forming threats. Smart cameras remove these blind spots by spotting spills, clutter, damaged flooring, cables, posture loss, and immobility the moment they surface in frame. They

What is The Role of Embedded Cameras at Different Levels of Autonomous Driving?

Suresh MadhuNovember 21, 20250

Autonomous driving depends on vision that can keep up with moving traffic, variable light, and decisions that change within seconds. Embedded cameras supply the visual detail needed for lane detection, sign interpretation, hazard tracking, close-range maneuvering, and interior vigilance. As automation rises, imaging has to deliver higher resolution, stronger HDR

How AI-Based Surveillance Systems Use Cameras to Safeguard Critical Infrastructure

Ram PrasadNov 21, 20250

Critical infrastructure relies on steady oversight across power yards, transit corridors, and port terminals, so imaging workflows must capture movement clearly and supply usable signals for control rooms. Vast outdoor spans, unpredictable light, constant motion, and high data volume push cameras to sustain strong brightness handling, stable frame output, and