The ADI Intelligent Edge Laboratory (AIEL) builds embedded intelligent systems that bring AI directly to microcontrollers, single-board computers, sensors, actuators, and IoT networks. Guided by its mission of embedded intelligence for the physical world, the laboratory translates needs in health, environment, agriculture, industry, and education into validated, field-deployable Edge AI hardware. The laboratory was formally launched in February 2026 together with its adjacent ADI Software Innovation Hub, donated by Analog Devices Gen. Trias, Inc. in partnership with the EEE Institute.

Laboratory Head: Marc Rosales, PhD

The laboratory’s work is organized into eight technical pillars:

• Embedded Hardware and Platform Design — circuit design, sensor and actuator interfaces, PCB layout, and power budgets
• Embedded and Edge Systems Software — firmware, RTOS, and drivers for lab hardware
• TinyML and AI on Microcontrollers — on-device inference and quantization using ADI’s CNN accelerator pipeline
• Edge AI on SBCs and Gateways — inference on Raspberry Pi and Jetson, bridging microcontroller nodes to the network
• IoT Networks, Cloud, and UI — connectivity and dashboards linking lab devices to people
• Embodied AI and Physical Systems — robotics, actuators, and perception-action loops
• Hardware-Aware and Energy-Efficient AI — latency, memory, and energy benchmarking on real silicon
• Robust, Secure, and Field-Deployable AI — reliability and security practices for deployed systems

This work is applied across six Edge Intelligence application segments:

• Health, biomedical, and assistive Edge Intelligence
• Nature, agriculture, and environmental Edge Intelligence
• Industrial and predictive maintenance Edge Intelligence
• Smart spaces, buildings, and community Edge Intelligence
• Human activity, sport, and performance Edge Intelligence
• Robotics, smart instruments, and embodied Edge Intelligence