Synaptics, an edge computing provider, has announced the development of KatanaConnect system-on-module. The solution uses AI-enabled computer vision and audio sensing, along with integrated wireless Wi-Fi and Bluetooth connectivity.
This system-on-module uses Synaptics‘ Katana low-power edge AI system-on-chip with the company’s Wi-Fi and Bluetooth module. It has been designed to serve various applications’ demands, including home automation, security, industrial automation and monitoring.
The Synaptics SYN430132 module provides wireless connectivity with a surface area of 33×32 mm and integrated IEEE802.11n Wi-Fi and Bluetooth 5.2 support. This module provides robust connectivity and reduces the system cost and space with built-in power and low-noise amplifiers.
“KatanaConnect enables the fastest, most future-proof path to feature-rich, connected AI vision and audio sensing systems in compact form factors,” said Ananda Roy, the senior product manager of low-power edge AI at Synaptics.
The Synaptics KatanaConnect solution merges vision, motion, and sound detection hardware and software with wired and wireless connectivity to create edge AI applications.
According to the company, KatanaConnect is a platform for developing innovative sensing methods, such as wireless sensing, and compliments Katana’s vision and audio edge AI features. Customers can customize and change AI models through a community of Katana AI software partners.
“In adopting the new Katana low-power AI solution from Synaptics, we are continuing a long and successful relationship between the two companies. We consider Synaptics one of our most trusted silicon partners,” said Vincent Fan, the VP of R&D at Ampak.
KatanaConnect makes autonomous decisions from collected vision and audio data, which means that it can be used for a variety of applications without being connected to the internet or needing a lot of power.
Synaptics recently announced the acquisition of Emza Visual Sense, which helped the company expand its edge IoT offerings, contributing to 63 percent of its fiscal 2022 revenue of $1.74 billion. For resource-constrained and low-power smart vision applications, Emza ML algorithms maximize AI inference per milliwatt.
chip | computer vision | edge AI | IoT | motion detection | sensor | SoC | Synaptics