Low power edge AI sensor for smart buildings
Cambridge startup InferSens has teamed up to combine its low power sensor with sophisticated deep learning for smart buildings.
InferSens’ sensor technology uses a third party processor with local AI models and innovative mechanical- and systems-engineering to create a smart sensors for the built environment.
The silicon is the NDP120 Neural Decision Processor from Syntiant in California which uses at memory compute and natively processing neural network instructions for enhanced data optimization. This enables InferSens to achieve on-device deep learning processing at only 1% of the power required by traditional processors.
The NDP120 can run multiple AI algorithms simultaneously at under 1mW, among other sensor and voice applications, and is designed to natively run multiple deep neural networks on a variety of architectures, such as CNNs, RNNs and fully connected networks.
The first version of the InferSens’ sensor technology is planned for Q1 2023. This is a low-cost, battery-powered, water flow and temperature sensor for monitoring and detecting Legionella risk in water systems. It can be quickly and easily attached to any pipe without any cutting or plumbing required.
It is initially aimed at the commercial and public sector property market where regulation demands that owners monitor the risks of Legionella, the cause of a potentially fatal form of pneumonia contracted via contaminated water.
“We are delighted to be working with InferSens to deploy cloud-free sensor solutions with our edge AI processor technology. The NDP120 delivers 25x the tensor throughput than our first-generation neural network, enabling highly accurate sensor processing with near-zero power consumption,” said Syntiant CEO, Kurt Busch.
InferSens CEO, Colin Payne said: “We have been developing our deep tech sensor technology since 2017, with the future of on-device deep learning in mind, which is why we’ve been able to achieve pole position with this revolutionary technology. Ahead of the formal product launch, we are engaging with customers for pilots, under commercial agreement, from a range of sectors including universities, hospitals, commercial offices, hotels and other property owners and operators.”
“The technology has very significant potential in multiple other practical uses such as multi-factor building occupancy, combined air quality and compound sensing for buildings and smart cities, and other applications where low power, rich data and smart sensing requirements converge. We are looking forward to bringing to market an exciting portfolio of products in due course.”
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