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2026.09.23
Giada IM1-993 SMARC Core Board Brings Low-Power Edge AI to Industrial and Embedded Applications
Giada has introduced the iM1-993 SMARC Core Board, a compact and low-power embedded computing platform designed for industrial control, EV charging stations, vending machines, drones, smart transportation, and other edge computing applications.
 
NXP i.MX 93 processor
Powered by the NXP i.MX 93 processor at up to 1.7 GHz, the iM1-993 combines computing, image acquisition, sensor data processing, and lightweight AI inference in a single compact module. Its low-power architecture enables fanless passive cooling and reliable 24/7 operation, making it suitable for space-constrained and thermally sensitive embedded systems.
 
Smooth Data Processing
The core board supports 1GB LPDDR4x memory, with 2GB available as an option, and optional 16GB, 32GB, or 64GB eMMC 5.1 storage. With Yocto 4.2 support, it provides a stable software foundation for embedded Linux development.
 
Rich I/O
Designed for industrial connectivity, the iM1-993 provides dual Gigabit Ethernet, three display outputs, one camera input, CAN-FD, UART, SPI, I2C, USB 2.0, GPIO, and SDIO 3.0 for Wi-Fi and Bluetooth expansion. These interfaces enable integration with PLCs, sensors, cameras, scanners, displays, payment devices, and industrial controllers.
 
Built around the 82 × 50 mm SMARC standard, the iM1-993 separates the computing module from the carrier board. Developers can customize I/O, enclosure, and power design while reusing the same core board across product generations, helping reduce development time and redesign costs. Giada also offers the iM1-9931 carrier board for faster system integration.
 
With industrial temperature options from -40°C to +85°C and commercial-grade operation from 0°C to +60°C, the iM1-993 is engineered for demanding environments. Its flexible architecture makes it suitable for drone control, EV charging infrastructure, vending machines, industrial HMI, CNC equipment, and smart transportation**, bringing efficient edge computing and AI capabilities closer to real-world devices.
 
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