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AI in Security & Surveillance
//INDUSTRIES
AI IN SECURITY AND SURVEILLANCE
Annotation in security and surveillance involves labeling and categorizing data to enhance the effectiveness of security systems and surveillance operations. Annotation plays a crucial role in security and surveillance by providing labeled data that enables security systems to detect, analyze, and respond to potential threats effectively
DATA ANNOTATION FOR IMPLEMENTING AI IN SECURITY AND SURVEILLANCE
Object Detection and Recognition
Annotation involves labeling objects of interest in images or video footage captured by surveillance cameras. This includes identifying and classifying objects such as people, vehicles, bags, and suspicious items, enabling security personnel to monitor and respond to potential threats.
Activity Recognition
Annotation is used to label human activities and behaviors observed in video data, such as walking, running, loitering, or suspicious behavior. This enables security systems to detect and alert authorities to unusual or potentially threatening activities in monitored areas.
Facial Recognition
Annotation involves labeling facial features and identities in images or video frames for facial recognition systems. This enables security systems to identify and track individuals of interest, such as suspects or persons of interest, and enhance access control measures in secured
Object Tracking
Annotation involves labeling objects and tracking their movements across multiple frames of video footage. This enables security systems to follow and monitor the trajectory of individuals, vehicles, or objects of interest within surveillance environments
Anomaly Detection
Annotation is used to label anomalous events or behaviors within surveillance data, such as sudden changes in activity levels, abnormal movements, or unusual interactions. This enables security systems to detect potential security breaches, identify threats, and trigger appropriate responses.
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//Industries
INDUSTRIES WE SERVE
RETAIL
Assisting the retail and e-commerce sectors by providing training data to optimize their in-store operations through the implementation of artificial intelligence (AI).ROBOTICS
3D object detection finds extensive application in robotics, particularly to prevent collisions with dynamic entities such as humans, animals, and other objects.AGRICULTURE
Supporting agriculture through computer vision training data involves facilitating the identification of product defects, sorting produce, managing livestock, assessing soil quality, implementing fertilizer applications, and fine-tuning genetic conditions.INSURANCE
Preparing training data to integrate AI into insurance procedures for tasks such as risk assessment, fraud detection, underwriting and minimizing human error.HEALTHCARE
Incorporating annotations and accurate labeling within AI systems is crucial for uncovering connections within genetic codesand enhancing efficiency in healthcare processes.SECURITY & SURVEILLANCE
Facilitating the integration of AI into cameras and sensors enables the detection of potential risks at workplaces, airports, and industrial sites. This involves incorporating computer vision technology into security and surveillance systems.SELF-DRIVING
Bounding boxes serve to annotate the surroundings of a vehicle, aiding in the detection of various objects including pedestrians, vehicles, traffic signs, and barriers.LOGISTICS
Logistics represents one of the growing areas of artificial intelligence application. We specialize in annotating images of goods to generate high-quality training data utilized in logistics.AUTONOMOUS FLYING
Simplifying and broadening access to AI implementations for automated or assisted flight can be achieved by leveraging image annotation conducted at the backend using training data specifically tailored for autonomous flying.