Intelligent cameras increase public safety
Community safety may be improved as Motorola Solutions and artificial intelligence company Neurala work together to develop intelligent cameras.
These cameras will allow police to more efficiently search for missing persons and suspects.
“We see powerful potential for artificial intelligence to improve safety and efficiency for our customers, which in turn helps create safer communities,” said Paul Steinberg, chief technology officer, Motorola Solutions.
“But applying AI in a public safety setting presents unique challenges. Neurala’s ‘edge learning’ capabilities will help us explore solutions for a variety of public safety workflows, such as finding a missing child or investigating an object of interest, such as a bicycle.”
The companies will work together to integrate Neurala’s AI capabilities with Motorola Solutions’ software and cameras, including its Si500 body-worn camera. The integration will create intelligent cameras that can learn ‘at the edge’ and automatically search for persons or objects of interest — significantly reducing the time and effort required to find a missing child or suspicious object in environments that are often crowded or chaotic.
These learning capabilities help solve some of the biggest challenges that come with real-time applications of AI. The intelligent camera learns to identify the person or object of interest. This feature, known as incremental learning, also reduces the risk of ‘catastrophic forgetting’, which occurs when a neural network forgets its previous training. Incremental learning also enables enhanced accuracy and latency for real-time public safety applications of AI.
“In the case of a missing child, imagine if the parent showed the child’s photo to a nearby police officer on patrol. The officer’s body-worn camera sees the photo, the AI engine ‘learns’ what the child looks like and deploys an engine to the body-worn cameras of nearby officers, quickly creating a team searching for the child,” said Steinberg.
Neurala will initially work with Motorola Solutions to build a prototype that allows for real-time learning for a person of interest search.
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