Planting the Seeds for a Sustainable Future Explore Solutions

Empowering Smart Sustainability Table of Contents1 AAEON Introduction Company overview and expertise in loT and Al edge computing How AAEON solutions support environmental initiatives Real-world implementations of sustainable technology solutions Partnership opportunities for a sustainable future

Our expert team provides end-to-end customized services, from concept development to mass production and after-sales support. Founded in 1992, AAEON Technology Inc. is a leading provider of IoT and AI edge computing solutions. Our comprehensive product portfolio includes: • Embedded Boards: Industrial-grade tablets & HMI panel PCs SBCs, Computer-on-Modules, Industrial Motherboard Computing Systems: AI Solutions: NVIDIA/Intel-powered Edge AI systems & modules Network & IoT: Network appliances, gateway systems, server boards Fanless & in-vehicle Box PCs, Industrial Chassis Rugged Devices: UP Series...

AAEON has a long history of facilitating the development of applications that pair advanced computing with initiatives aimed at improving the world around us to help create a brighter, more sustainable future. Systems that monitor, control, and optimize energy usage using embedded technology. Embedded systems enable data collection for the processing and communication of environmental parameters. Embedded systems handle everything from user interaction to power control, metering, communication, and safety monitoring.

Sustainable Innovation Proven Solutions for a Greener Future Smart Energy Consumption Meter Electric Vehicle Charging Station Al-Assisted Forest Fire Detection

Develop an automated system to monitor and control electricity consumption across multiple premises including campuses, offices, and factories.

Real-time monitoring of energy consumption Automated control of non-essential systems Threshold-based operation adjustment Support for multiple communication protocols

The SRG-AM62 collects real-time energy consumption data from devices like boilers, lighting systems, and heat pumps via Modbus RTU/TCP, analyzes it, and issues commands to automatically reduce the operation of non-essential functions when consumption exceeds predefined thresholds, using both wired and wireless communication.

Efficient Communication Versatile I/O connectors (RS-232 /422/485, CANBus). Supports Modbus RTU/TCP for multidevice integration. ARM-based TI Sitara™ Processor (1.2W per core, 5.76W full load). Wireless module control for energysaving and scalability. Wide 9V-36V power input, -40°C to 85°C tolerance. Compact, fanless, and durable design for diverse environments

Client Challenge: A global EV charging equipment provider needed to deploy user-friendly, energy-efficient charging stations across multiple locations.

Android™-based touchscreen interfaces Robust outdoor performance Seamless cloud connectivity

The integration of the PICO-IMX8PL allowed the customer to roll out a scalable, user-centric EV charging station platform aligned with their sustainability goals. By addressing the project’s key technical and environmental demands, AAEON’s PICO-IMX8PL became the reliable core of an EV charging solution built for smart, scalable, and sustainable infrastructure worldwide

Energy Efficient Despite its powerful NXP i.MX 8M Plus platform featuring quad-core Arm® Cortex®-A53 processing, the board averages just 14.8W even under full load. The platform supported Android™ 13, allowing them to tailor application display panel functions and adjust the UI for different screen sizes. With a 2.5" Pico-ITX form factor, the board was easy to integrate into the space-constrained environment of charging stations. Designed for harsh conditions, the PICO-IMX8PL supports a -40°C to 80°C temperature range and 9V to 36V power input.

-Assisted Forest Fire Detection fire 0.27 A company specializing in intelligent environmental monitoring needed to upgrade its forest fire detection system to enable faster response times and reduce environmental

Edge AI processing for early fire detection Real-time monitoring in remote areas Minimal latency for critical alerts Scalable network with low maintenance requirements

The system uses the live video feed from an IP camera and runs advanced deep learning models locally using the BOXER-8651AI’s NVIDIA® Jetson Orin™ NX module to identify early signs of fire such as smoke or flickering. In the event a fire is detected, the device transmits real-time alerts via the installed cellular or Wi-Fi modules to a central server, enabling rapid response with minimal manpower across a scalable, low-maintenance network. NVIDIA Jetson Orin NX Central Server Mounted Camera

(Jp1 Wireless Expansion M.2 slots and SIM support for 4G/5G and Wi-Fi modules, it ensures low-latency wireless alerts and data transmission NVIDIA Jetson Orin NX Up to 70 TOPS of AI performance, enabling accurate, real-time forest fire detection without reliance on cloud processing Fanless enclosure and wide -15°C to 55°C operating range make it ideal for remote outdoor deployment Compact & Lightweight 105mm x 90mm x 52mm form factor weighing just 1.1kg makes it easy to install on observation towers or in forested areas

Contact your AAEON representative to explore how to leverage embedded technology for a more livable, sustainable future