Outdoor Analytics
Traffic Analytics
Traffic analytics for cities involves analyzing data from vehicles, pedestrians, and public transport to monitor and optimize urban mobility. It uses sensors, cameras, and GPS to track traffic flow, congestion patterns, and accident hotspots, helping improve infrastructure, reduce delays, and enhance transportation efficiency.
Smart Parking
Controlling parking slots involves managing and optimizing the use of parking spaces through technology like sensors, cameras, or IoT devices. It monitors slot availability in real-time, guides drivers to open spots via apps or signage, and automates payment systems. This reduces congestion, improves efficiency, and enhances the overall parking experience.
LPR (License Plate Recognition)
LPR is a technology that uses cameras and image processing to automatically detect and read vehicle license plates. It’s commonly used for parking management, toll collection, law enforcement, and security.
This technology identifies a vehicle’s make/model (brand) and color using computer vision and machine learning. It analyzes visual features like logos, shapes, and color tones, and is often integrated with LPR for enhanced vehicle identification in parking, traffic monitoring, or security systems.
Traffic Violations
Can be identified different types of traffic violations like the below examples :
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Illegal Parking: Vehicles parked in no-parking zones, blocking pedestrian pathways, or occupying restricted areas, leading to congestion and safety hazards.
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Failure to Stop for Pedestrians: Drivers not yielding to pedestrians at crosswalks or designated areas, endangering pedestrian safety and violating traffic laws.
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Wrong-Way Driving: Vehicles entering streets in the opposite direction of traffic flow, creating dangerous situations and increasing the risk of accidents.
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Red Light Violation: occurs when a vehicle enters an intersection after the traffic light has turned red.
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Other cases based on the client needs.
Object Detection
Object detection is a computer vision technology that identifies and locates objects within images or videos. Using algorithms like YOLO, SSD, or Faster R-CNN, it detects multiple objects, classifies them (e.g., cars, people), and provides their precise locations with bounding boxes. It’s widely used in surveillance, autonomous vehicles, and retail.
Hat Detection
A construction area enforces strict safety protocols, including the mandatory use of hard hats. Staff not wearing hats are identified through real-time monitoring systems, such as AI-powered cameras or supervisors conducting inspections. This ensures compliance with safety standards, reduces the risk of injuries, and maintains a secure work environment. Non-compliant workers may be reminded, warned, or required to wear proper protective gear before continuing work.
Blur Functionality
The AI blur functionality in videos, both online and offline, uses artificial intelligence to automatically detect and blur specific objects, faces, or areas within a video. This is commonly used for privacy protection, content moderation, or focusing attention on certain elements. The AI identifies the target areas (e.g., faces, license plates, or sensitive content) and applies a blur effect that can be adjusted for intensity and precision. Online platforms often use this feature in real-time streaming, while offline tools allow users to manually or automatically blur content during editing. This technology is widely used in surveillance, social media, and video production.
