Safety & Surveillance

AI in security and surveillance is launching a new era of defending persons and organizations from various dangers while providing sharper face, object, and event recognition capabilities with little room for mistake.

Training Data for AI in Safety & Surveillance

AI provides security in ways that surveillance cameras alone cannot. With top-tier AI skills such as real-time surveillance and improved picture processing, one can detect any potentially dangerous behavior that a human could overlook.

To build such powerful systems for security and surveillance, diversified and high-quality training datasets are required. FutureBeeAI provides huge datasets that are ready to deploy. FutureBeeAI can assist you with gathering real-world bespoke video, picture, and even synthetic datasets, as well as annotating the data with our skilled team.

Browse Structured Datasets in Safety & Surveillance

Train & Deploy models with more than 200+ unique real-world Speech, Video, Text, Image, and Synthetic datasets

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Data Security
Security Comes First

Face Recognition

Many of us are concerned about security in today's fast-paced world, and it takes a lot of time, money, and human resources to avoid security breaches. Artificial intelligence-enabled video analytics can assist us in detecting any illegal behavior or threat. Artificial intelligence video analytics can discover and report irregularities in a fraction of a second, making it a proactive security solution. This is critical for high-traffic areas and vast campuses, such as airports, retail stores, and tourist destinations.

Traffic & Road Safety

AI-enabled video analytics can aid in traffic management and improve road safety by detecting: no-helmet and triple riding detection, wrong-way driving or illegal turn detection, no-parking violation detection, license plate detection, stop-line crossing detection, no-seatbelt detection, mobile usage detection, and over-speeding detection.

Smart Object Tracing

Using computer vision techniques, each item in a frame can be identified and segmented, and then matched against a list of predefined categories, such as a car, bike, truck, man/woman wearing a cap, jacket, or bag, and so on. Once the item of interest has been recognized and matched, the object segmentation describes the pixels used by the object, and the movement of those pixels across video frames can be traced from numerous CCTV cameras, providing the object's entry/exit path.

Video Forensics

If a crime is caught on CCTV, AI-based deep learning can aid in the investigation. When forensic teams are trying to identify certain cars or items during the post-incident investigation, machine learning algorithms can be employed for color conversion, regeneration, and comparison between two video backdrops.