Surveillance system and surveillance method using multi-dimensional sensor data

This invention describes a surveillance system that gathers information from many different types of sensors, such as cameras, microphones, and even taste, smell, or touch sensors. It first analyzes data from each individual sensor type to identify local objects and their characteristics, including their direction, distance, and roughness. Then, it combines all this local information into a comprehensive global view to recognize overall events or situations within the monitored area.

Why it matters: Since 2018, significant advancements in AI and machine learning, particularly in multi-modal data fusion and object recognition, have made processing diverse sensor inputs far more effective and accessible. This progress directly addresses the core computational challenges of this surveillance method.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedMulti-modal sensor integration, AI/ML software

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