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SLN-VIZNAS-IOT

Name: NXP SLN-VIZNAS-IOT
Brand: NXP Semiconductors
SKU: 771-SLN-VIZNAS-IOT
Price: 23256.88 INR
Availability: InStock

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Mouser No:

771-SLN-VIZNAS-IOT

Mfr. No:

SLN-VIZNAS-IOT

Mfr.:

NXP Semiconductors

Description:

Development Boards & Kits - ARM SLN-VIZNAS-IOT

Datasheet:

SLN-VIZNAS-IOT Datasheet (PDF)

More Information

Learn more about NXP Semiconductors SLN-VIZNAS-IOT

In Stock: 83

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Factory Lead Time:: 13 Weeks Estimated factory production time for quantities greater than shown.

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	₹23,256.88	₹23,256.88

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Product Attribute	Attribute Value	Select Attribute
Manufacturer:	NXP
Product Category:	Development Boards & Kits - ARM
RoHS:	N
Series:	RT106F
Product:	Development Kits
Core:	ARM Cortex M7
Tool Is For Evaluation Of:	RT106F
Brand:	NXP Semiconductors
For Use With:	Smart Industrial Devices
Product Type:	Development Boards & Kits - ARM
Factory Pack Quantity:	1
Subcategory:	Development Tools
Part # Aliases:	935410533598

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Datasheet

SLN-VIZNAS-IOT Datasheet (PDF)

USHTS:: 8471500150
ECCN:: 5A992.C

MCU-Based Turnkey IoT Solutions

NXP Semiconductors MCU-Based Turnkey IoT Solutions leverage specialised i.MX RT Crossover Processors that enable developers to quickly and easily implement facial recognition and voice control into their applications. These turnkey IoT solutions come with fully integrated software running on FreeRTOS, for quick out-of-the-box evaluation and proof of concept development.

SLN-VIZNAS-IOT Solution for Face Recognition

NXP Semiconductors SLN-VIZNAS-IOT Solution for Face Recognition is an EdgeReady development kit for secure face recognition based on the i.MX RT106F Crossover Processor. The SLN-VIZNAS-IOT is designed to enable developers to quickly and easily add face recognition with liveness detection to their products. Liveness detection prevents spoofing with a photograph and is implemented with cost-effective IR and RGB cameras, without the need for expensive 3D cameras. The SLN-VIZNAS-IOT comes with fully integrated turnkey software for quick out-of-the-box operation, minimizing time to market, risk, and development effort. Face recognition is done entirely at the network edge, addressing the privacy concerns of many consumers.