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Jetson Nano

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Jetson Nano
Manufacturer
NVIDIA
Alternatives
Raspberry PiAsus Tinker Board
Dimensions
70 x 45 mm
Number of Cores
4
Architecture
64-bit Arm
RAM
4 GB LPDDR4
Power Consumption
5–10 watts
Supported Languages
PythonC/C++

Jetson Nano is a compact and powerful AI computer developed by NVIDIA that enables modern artificial intelligence applications to run at the edge with low power consumption. It is capable of running multiple neural networks simultaneously in tasks such as image classification, object detection, segmentation, and speech processing. Despite its small size, this platform delivers high performance and is especially preferred for low-cost and energy-efficient solutions.

Jetson Nano and Camera Module (Generated by Artificial Intelligence)

History

Jetson Nano was developed with a focus on object detection, one of the fundamental problems in computer vision. Designed by the California-based NVIDIA Technology Company, Jetson Nano was first introduced at the GPU Technology Conference (GTC) in March 2019. The Jetson series is a line of integrated accelerator hardware created in response to the widespread use of machine learning. Jetson Nano was specifically designed as a low-cost, low-power, and compact AI platform for Internet of Things (IoT) manufacturers and developers.

Technical Specifications and Hardware Structure

Measuring only 70 x 45 mm, Jetson Nano is smaller than a credit card. The module is built on a 64-bit ARM architecture and features a 128-core Maxwell GPU, quad-core ARM Cortex-A57 CPU, 4 GB LPDDR4 memory, and 16 GB eMMC storage. It also includes components such as Gigabit Ethernet, PMIC, power regulators, and temperature sensors. The 260-pin SODIMM connector supports both high-speed and low-speed I/O components. Jetson Nano provides various interfaces including GPIO, I2C, SPI, UART, USB, and HDMI, along with a microSD card slot for storage.

Model Variants

There are three different developer kit models of Jetson Nano: Jetson Nano A02, Jetson Nano B01 (4GB), and Jetson Nano 2GB. The first A02 model was released in March 2019, while the enhanced B01 model was launched in January 2020. Some technical limitations found in the A02 model, such as the inability to boot with the Intel 8260 WiFi module, were resolved in the B01 model. Additionally, an extra camera slot was added to the B01 version. Most of the technical features and components are shared among the three models.

Performance and Power Efficiency

Jetson Nano delivers 472 GFLOPs of compute performance for modern AI algorithms. It can simultaneously process data from high-resolution sensors and run multiple neural networks in parallel. With a power requirement of only 5 to 10 watts, it offers excellent energy efficiency. This makes it ideal for intelligent IoT devices, robotic systems, and edge AI solutions.

Software Support and Development Environments

Jetson Nano runs on NVIDIA’s JetPack SDK and supports today’s most popular AI libraries and frameworks. Libraries such as Pandas, NumPy, TensorFlow, and Keras can be executed on this platform. It also supports OpenCV for image processing applications, including facial recognition via machine learning. Programming languages such as C/C++ and Python are supported. Thanks to its OS-based architecture, various compilers, applications, web apps, and databases can be installed and run on Jetson Nano.

Bibliographies

Ultralytics. April 2, 2024. Quick Start Guide: Ultralytics YOLOv8 with NVIDIA Jetson. Accessed May 12, 2025. https://docs.ultralytics.com/tr/guides/nvidia-jetson/#install-ultralytics-package_1.

NVIDIA. November 21, 2024. Jetson Nano | Modern AI for Millions of Devices | NVIDIA. Accessed May 12, 2025. https://www.nvidia.com/tr-tr/autonomous-machines/embedded-systems/jetson-nano/product-development/.

Kılıç, H. 2023. Object Detection from Ground Penetrating Radar Data Using Machine Learning on Embedded Systems. Master’s thesis, Selçuk University, Institute of Science, Konya.

Kocer, Sabri, Ozgur Dundar, and Resul Butuner, eds. Programmable Smart Microcontroller Cards. Istanbul: ISRES Publishing, 2021. ISBN 978-605-74825-6-3.

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Main AuthorKaan GülMay 13, 2025 at 9:19 AM
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