TFT vs OLED in Budget Tablets: A 2025 Technical Overview

As tablet adoption continues to rise across both mature and developing markets, the quality of display technology has become one of the most noticeable factors influencing user satisfaction. In the budget segment—typically tablets priced below $300—the choice between TFT LCD and OLED panels plays a major role in balancing cost, reliability, power consumption, and overall visual performance.

This article reviews how these two display technologies are used in budget tablets in 2025, examining their technical characteristics, market trends, engineering considerations, and suitability for different user scenarios.

1. Why Displays Matter in Budget Tablets

In low-cost devices, internal components such as mid-range processors, RAM, and storage have become relatively standardized. As a result, the display often becomes the feature that defines the quality of the tablet experience. Brightness, viewing angle stability, color accuracy, and power efficiency all shape how a device feels during day-to-day use.

Budget tablets must strike a balance between affordability and usability, and the selected display technology is one of the few components that directly influences both.

2. Technical Overview of TFT LCD

TFT LCD displays rely on an LED backlight that shines through liquid crystal cells. These cells act as shutters, controlling light flow through red, green, and blue color filters. The structure is relatively simple and has been refined over decades.

Strengths of TFT LCD

• Lower production cost due to mature manufacturing processes


• Consistent brightness and better readability outdoors


• Minimal risk of burn-in, even with static UI elements


• Wide availability across multiple suppliers

Weaknesses of TFT LCD

• Reduced contrast ratio compared with OLED


• Limited color depth on lower-end panels


• Viewing angles that vary depending on panel type (TN, IPS, VA)


• Thicker structures due to the backlight layer

In today’s budget tablets, IPS-type TFT panels are common because they offer acceptable color reproduction and significantly improved viewing angles compared with older TN panels.

3. Technical Overview of OLED

OLED panels work very differently. Each pixel emits its own light, removing the need for a backlight. This gives OLED its well-known deep blacks and high contrast ratios. Recent improvements have made OLED more available in mid-range tablets, and the cost gap has narrowed compared with previous years.

Strengths of OLED

• True blacks and excellent contrast


• Highly vibrant colors and superior viewing angles


• Thinner and lighter construction


• Flexible and curved designs possible

Weaknesses of OLED

• Susceptibility to burn-in when static elements remain on screen


• Higher cost than mainstream TFT options


• Lower peak brightness in lower-cost OLED panels


• Performance degradation over long operating lifetimes

Despite these limitations, OLED has become increasingly common in tablets positioned as “premium budget” devices.

4. Market Trends in 2025

Growing Use of OLED in Mid-Range Tablets

Since 2022, large-scale manufacturing has reduced the cost of OLED modules by an estimated 20–25%. This allows manufacturers to offer OLED-equipped tablets around the $200–$300 range without significantly compromising other specifications.

Brands including Xiaomi, Realme, and Honor now offer budget tablets with OLED displays, mainly targeting consumers who prioritize media consumption.

Continued Dominance of TFT in Lower Price Brackets

Under $200, TFT LCD remains the default choice. Manufacturers such as Lenovo, Samsung, and Amazon continue to rely on high-quality IPS TFT panels because they provide:

• Reliable performance in classrooms and industrial environments


• Higher outdoor visibility


• Longer operational lifespan


• Stable supply chains

5. Visual Performance Comparison

Color and Contrast

OLED delivers unmatched contrast because pixels turn off completely to represent black. TFT panels, even IPS variants, still show some glow in dark scenes due to the active backlight.

Brightness and Outdoor Use

Budget-oriented OLED panels often cannot reach the peak brightness levels of TFT LCDs. As a result, TFT tends to perform better in sunlight or brightly lit spaces.

Viewing Angles

OLED maintains accurate colors across almost all viewing angles.
IPS TFT is acceptable, while cheaper VA and TN panels introduce noticeable shifts.

Battery Consumption

OLED power usage varies widely. It is efficient with dark interfaces but becomes less efficient with bright or white backgrounds. TFT power consumption is more predictable, making it easier to manage battery life in general-use tablets.

6. Durability and Longevity

Durability is where TFT still holds a clear advantage. OLED burn-in remains a concern for devices that display static UI layouts or icons for long periods. Educational tablets, kiosk-style commercial tablets, and business devices typically avoid OLED for this reason.

TFT panels do not suffer from permanent image retention and typically maintain stable performance over long operating lifetimes.

7. Engineering and Manufacturing Considerations

Thermal Behavior

OLED lacks a backlight, reducing overall heat generation. However, bright content can lead to localized heat spots.
TFT distributes heat more evenly due to the backlight structure.

Form Factor Flexibility

OLED enables thinner and curved designs. While not yet mainstream in sub-$300 tablets, early models with flexible OLED panels are beginning to appear.

Supply Chain Reliability

TFT LCD manufacturing capacity is widespread and diversified across many suppliers.
OLED production remains concentrated among a smaller number of panel manufacturers, leading to occasional supply constraints.

8. Practical Use Cases

9. Strategic Outlook

Looking ahead, the budget tablet market will likely continue following a dual-track approach:

• TFT LCD for durable, cost-oriented, and educational devices


• OLED for visually immersive and media-centric devices

Meanwhile, emerging technologies such as mini-LED backlit TFT panels are beginning to bridge the gap between traditional LCD and OLED, offering improved contrast while maintaining durability.

10. Conclusion

In 2025, both TFT LCD and OLED play important roles in budget tablets. OLED continues to push visual quality forward, while TFT remains the dependable option for long-term use, outdoor visibility, and lower price points.

For manufacturers, the challenge lies in matching display technology to user expectations. For consumers, understanding the strengths and trade-offs of each panel type makes it easier to choose a tablet that fits real-world needs.

As display innovation accelerates, the distinction between budget and premium tablets is becoming less about raw performance and more about the kind of experience users want—and the role the display plays in delivering it.

Android SBC vs Linux SBC: Choosing the Right Platform for Embedded Projects

Single Board Computers (SBCs) have become a standard building block for modern embedded systems. Instead of designing a
processor, memory, and I/O subsystem from scratch, engineers can start with an SBC and focus on application logic, UI,
and system integration.

When selecting an SBC, one of the first architectural decisions is the software platform. In many projects that need a
graphical user interface or connected features, the choice often narrows down to two options:

• Android SBC – an SBC that ships with Android as the primary operating system


• Linux SBC – an SBC that runs a more traditional GNU/Linux distribution

Both options can run on similar ARM or x86 processors, and both support rich applications, networking, and hardware
acceleration. However, their design philosophy, development workflow, and best-fit applications are different.
This article compares Android SBCs and Linux SBCs from a practical engineering perspective to help you decide which
platform is the better match for your next embedded project.

1. What Is an Android SBC?

An Android SBC is a single board computer whose primary operating system is Android, usually based on
AOSP (Android Open Source Project) plus vendor-specific modifications. These boards are often derived from mobile or TV
box platforms and reuse SoCs originally designed for smartphones, tablets, or media players.

Android SBCs typically provide:

• A touch-friendly, app-centric user interface


• Support for Android applications written in Java/Kotlin (and sometimes Flutter, React Native, etc.)


• Access to common Android APIs: multimedia, sensors, notifications, permissions, and more


• Hardware acceleration for graphics and video playback


• Optional access to Google Mobile Services (GMS) depending on licensing and certification

From the user’s perspective, an Android SBC can feel like a large-screen Android tablet without a battery. From the
developer’s point of view, it behaves like an embedded Android device that can be customized, branded, and integrated
into a product.

2. What Is a Linux SBC?

A Linux SBC runs a more traditional Linux distribution such as Debian, Ubuntu, Yocto-based custom
images, or other embedded Linux variants. The board may still use the same family of ARM or x86 processors, but the
software stack resembles a desktop or server Linux environment.

Linux SBCs usually provide:

• Standard GNU/Linux user space (shell, systemd or other init system, common utilities)


• Wide language support: C/C++, Python, Go, Rust, Node.js, and more


• Access to package managers (apt, opkg, rpm, etc.), enabling the installation of existing software


• Multiple graphical frameworks: Qt, GTK, LVGL, Chromium-based front-ends, or fully custom UIs


• Flexible networking and security tools comparable to server Linux systems

Developers can treat a Linux SBC like a small server, a desktop replacement, or a headless controller, depending on the
application. It is especially strong where openness, customization, and long-term maintainability are priorities.

3. User Interface and HMI Capabilities

3.1 Android SBCs

Android was designed from the ground up for touch-first devices, so UI development is one of its strongest advantages:

• Rich, mature UI toolkit with animations, transitions, and standardized widgets


• Well-defined design language (Material Design) that helps maintain a consistent look and feel


• Built-in support for virtual keyboards, text input, notifications, and multi-touch gestures


• Good ecosystem of high-level frameworks and libraries for charts, media, and connectivity

For devices that resemble a smartphone or tablet in behavior—for example, interactive kiosks, digital signage,
consumer touch panels, or infotainment terminals—Android can significantly reduce HMI development time.

3.2 Linux SBCs

Linux SBCs offer more freedom but also demand more architectural decisions on the UI side:

• Choice between Qt, GTK, LVGL, web-based UIs (Electron, Chromium, WebView), or custom OpenGL solutions


• Greater flexibility for non-touch or mixed input (mouse, keyboard, industrial keypads, barcode scanners)


• Better suited to multi-window desktop-style applications or combined GUI + headless services

For industrial HMIs, configuration tools, or engineering interfaces that require precise control and integration with
existing Linux software, a Linux SBC can be a better match.

4. Headless Operation and Background Services

Many embedded systems do not need a graphical UI at all, or only require a simple status page while most work runs in the
background.

• 
  Android SBC: Optimized for app-centric workflows with Activity and Service lifecycles.
  Headless or daemon-style services are possible but less natural, and the platform assumes a foreground UI most of the time.
  


• 
  Linux SBC: Naturally suited for headless operation. System services can run under systemd or other
  init systems, just like on a server or router. Ideal for gateways, data loggers, or control units that rarely show a UI.
  

If your project is primarily about data acquisition, control, or networking with minimal direct interaction,
a Linux SBC is usually the simpler and cleaner option.

5. Development Workflow and Tooling

5.1 Android SBC Development

Android development typically uses:

• Android Studio as the main IDE


• Java or Kotlin as primary languages


• Android SDK and NDK (for native C/C++ code)


• Emulators and ADB for debugging and deployment

Engineers with mobile app experience can quickly adapt to building applications for Android SBCs. However, modifying
system components, device drivers, or low-level behavior may require working with the Android build system and BSP
(Board Support Package), which is more complex than standard Linux distributions.

5.2 Linux SBC Development

Linux SBC development looks more like server or desktop development:

• Compilers like GCC/Clang and cross-compilation toolchains


• Shell access (SSH), standard build systems (CMake, Meson, Make)


• Popular languages such as C/C++, Python, Go, Rust


• Standard debugging tools: gdb, strace, perf, Valgrind

For teams already familiar with Linux development, moving to a Linux SBC is straightforward. Kernel modification,
driver integration, and custom filesystems are also easier to manage in a typical embedded Linux workflow (Yocto, Buildroot,
Debian-based images, and so on).

6. Connectivity, Networking, and Security

Both Android and Linux provide mature networking stacks, but their emphasis differs.

• 
  Android SBC: Offers convenient APIs for Wi-Fi, Bluetooth, mobile networks, and cloud connectivity
  from the application layer. Good for devices that are mostly client-like, such as consumer IoT products, kiosks, and
  connected displays.
  


• 
  Linux SBC: Provides a full range of networking tools more typical for servers and routers:
  iptables/nftables, VPNs, SSH, advanced routing, industrial protocols, and more. Better suited to gateways, edge
  nodes, or devices that must integrate deeply into existing IT/OT networks.
  

In terms of security, both platforms can be hardened, but Linux gives more granular control at the system level
(SELinux, AppArmor, custom firewalls, containerization, etc.), while Android emphasizes sandboxing at the application
level and a permissions-based model.

7. Real-Time Behavior and Determinism

Most Android and Linux SBCs are not hard real-time systems out of the box. However, embedded Linux has a more established
path toward real-time enhancements:

• PREEMPT_RT patches for the Linux kernel


• Combining Linux with a separate real-time MCU for critical control loops


• Use of real-time frameworks such as Xenomai in some projects

Android can be tuned, but it is generally not the first choice for applications that require deterministic response times
(such as motor control or safety-critical functions). In such cases, Linux SBCs paired with dedicated MCUs or real-time
modules are more common.

8. Software Ecosystem and Package Availability

The available software ecosystem is another major difference.

• 
  Android: Access to Android libraries, mobile frameworks, and app-centric tooling. Many cloud SDKs and
  third-party services offer Android clients. However, traditional Linux command-line tools, daemons, and packages are
  either absent or must be ported specifically.
  


• 
  Linux: Access to huge repositories of open-source software (servers, databases, message brokers,
  monitoring tools, scientific libraries, etc.). Ideal when the device must run existing Linux components or integrate
  with standard tooling.
  

If your product is primarily a touch device that behaves like a dedicated app, Android has the edge. If the device needs
to behave more like a small server or gateway, Linux offers far more ready-made building blocks.

9. Updates, Maintenance, and Lifecycle

Embedded products often remain in the field for many years, so long-term maintenance is critical.

• 
  Android SBC: Android versions are tightly coupled to SoC vendors and BSP releases.
  Upgrading from one major Android version to another can be complex and may depend on vendor support.
  OTA (over-the-air) updates are well supported at the application level, but long-term OS support varies.
  


• 
  Linux SBC: Many distributions provide long-term support (LTS) kernels and security updates.
  Yocto or Buildroot-based systems allow complete control over the software stack, enabling long-term maintenance
  even after a SoC is considered mature or end-of-life, as long as kernel support remains.
  

If your product has a long lifecycle and needs predictable maintenance strategies, Linux often offers more control and
transparency, whereas Android support depends more heavily on the BSP vendor.

10. Typical Use Cases for Android SBCs

Android SBCs tend to work best when:

• The device is highly UI-centric and touch-focused


• The user experience is similar to a consumer app


• Media playback, animations, or app-like workflows are important


• Developers have strong Android/Java/Kotlin expertise

Examples include:

• Interactive kiosks and self-service terminals


• Smart home control panels and wall-mounted touch screens


• Digital signage players with animated content


• Point-of-sale terminals or check-in systems

11. Typical Use Cases for Linux SBCs

Linux SBCs are usually preferred when:

• The system must run multiple services or daemons alongside the UI


• Industrial protocols, gateways, or edge computing workloads are involved


• Headless or semi-headless operation is required


• Long-term maintenance, root-level access, and customizations are critical

Examples include:

• Industrial HMIs with complex back-end logic


• Data acquisition units and edge gateways


• Factory automation controllers that interact with PLCs and fieldbuses


• Robotics platforms and autonomous machines

12. Decision Checklist: Android SBC vs Linux SBC

When choosing between an Android SBC and a Linux SBC, consider the following questions:

1. Is the device primarily a touch-based, app-like interface or a control/gateway node?


2. Does the team have more experience with Android development or Linux development?


3. Will the device run mostly one foreground application or multiple background services?


4. Are long-term OS updates and deep system customization required?


5. How important are real-time behavior and deterministic response?


6. Does the project depend heavily on existing Linux tools and packages?

There is no universally “better” platform—only a more suitable one for a specific problem. In some projects, a
hybrid approach is also possible: using a Linux SBC as the core controller and an Android device as a secondary display, or
combining a Linux SBC with a separate microcontroller for real-time tasks.

Conclusion

Android SBCs and Linux SBCs share much of the same hardware DNA, yet they target different design philosophies.
Android focuses on delivering polished, touch-first user experiences with a strong app ecosystem, while Linux emphasizes
flexibility, openness, and long-term maintainability.

If your device is essentially a dedicated interactive application with rich graphics and animations, an Android SBC may
offer a faster path to market. If your project resembles a small server, gateway, or industrial controller with multiple
services and heavy integration requirements, a Linux SBC is likely the better choice.

By aligning the choice of SBC platform with the actual role of the device—UI terminal, gateway, controller, or
mixed system—you can reduce development effort, improve reliability, and extend the useful life of your embedded
product.

Display Interfaces: LVDS vs MIPI DSI vs eDP vs HDMI

Choosing the right display interface is a critical decision in embedded and industrial system design.
The interface you select affects image quality, refresh rate, power consumption, cable length, EMI performance,
and the overall BOM cost of your product. This article provides a clear comparison of the four most commonly
used display interfaces—LVDS, MIPI DSI, eDP, and HDMI—based on real engineering considerations.

For readers who want a broader overview of different TFT interface standards, you can also explore
this detailed collection of TFT display interface guides.

1. LVDS (Low-Voltage Differential Signaling)

Overview

LVDS is one of the longest-standing display interfaces in industrial applications. It transfers data using
differential signaling, which greatly reduces EMI and supports long cable distances compared with more
modern serialized display protocols.

Strengths

• Mature, stable, and widely supported in industrial SBCs and HMI devices.


• Excellent reliability over long cable lengths (up to 10 meters with proper cabling).


• Well suited for electrically noisy environments.

Limitations

• Fixed mapping makes it less flexible for evolving display resolutions.


• Requires more pins compared with serial interfaces like MIPI.


• Dual- or quad-channel LVDS is required for resolutions above 1080p.

Best For: Factory automation panels, medical displays, outdoor kiosks.

2. MIPI DSI (Mobile Industry Processor Interface – Display Serial Interface)

Overview

MIPI DSI was originally developed for smartphones and tablets, but it is now widely adopted in compact
embedded systems. It uses high-speed serial lanes with a low pin count.

Strengths

• Extremely low power consumption.


• High bandwidth supporting resolutions up to 4K with four lanes.


• Allows slim, flexible cable designs commonly used in handheld devices.

Limitations

• Short cable length limitations (typically less than 30 cm).


• Sensitive to EMI; requires proper shielding in industrial environments.


• Driver support varies across industrial SBC platforms.

Best For: Portable devices, compact HMIs, low-power IoT products.

3. eDP (Embedded DisplayPort)

Overview

eDP is a version of DisplayPort designed for internal display connections. It supports high-resolution
and high-refresh-rate displays, making it a strong choice for performance-oriented systems.

Strengths

• Supports extremely high resolutions, including 4K and 8K.


• Lower EMI and improved efficiency compared with HDMI.


• Can transmit audio and auxiliary data.

Limitations

• Cable length is shorter than LVDS (typically under 3 meters).


• Less common in older industrial embedded platforms.

Best For: AI vision systems, high-performance industrial PCs, medical workstations.

4. HDMI (High-Definition Multimedia Interface)

Overview

HDMI is the world’s most widely used consumer display interface. It supports both video and audio through
a single cable and is compatible with virtually all TVs and monitors.

Strengths

• Universal compatibility with retail displays.


• Supports hot-plugging and modern content protection (HDCP).


• Capable of resolutions up to 8K with HDMI 2.1.

Limitations

• Higher power consumption than LVDS or MIPI.


• Not optimized for internal displays due to connector size.


• Requires strong EMI shielding for industrial applications.

Best For: Digital signage, prototyping, external monitors.

5. Comparison Table

Before comparing the interfaces directly, understanding resolution and aspect ratio is helpful because
different interface technologies scale differently with pixel density.

For a deeper explanation, you can explore this guide on resolution and aspect ratio in TFT displays.

6. Application Recommendations

Use LVDS when:

• You need long cable runs.


• The environment has high EMI.


• You require long-term stable industrial supply.

Use MIPI DSI when:

• Low power and compact cabling are priorities.


• Cable length can be kept short.


• Your device is battery powered.

Use eDP when:

• You need very high resolutions or fast refresh rates.


• The system design allows short internal cables.


• Your platform supports DisplayPort signaling.

Use HDMI when:

• The display is external or user-replaceable.


• You need compatibility with consumer monitors.


• You are prototyping or developing concept designs.

Additional Resource

For readers who want a broader overview of how these interfaces are used in embedded systems,
you can also check this Google page on display interfaces.

Final Thoughts

There is no single display interface that fits every embedded project. LVDS remains the preferred choice
for long-distance industrial applications, while MIPI DSI excels in portable and ultra-compact devices.
eDP is ideal for performance-oriented systems with high resolution requirements, and HDMI continues to
dominate applications involving external screens and general consumer displays.

Selecting the right interface early in your design process can prevent costly redesigns later and ensures that
the overall system performs efficiently throughout its lifecycle.

Introduction to ARM Architecture: A Modern Computing Foundation

ARM architecture has become one of the most influential computing platforms in the modern era.
From smartphones and tablets to automotive systems, industrial controllers, routers, smart home devices,
and even cloud servers, ARM-based processors are everywhere. Unlike traditional x86 processors,
ARM follows a reduced instruction set computing (RISC) philosophy, focusing on efficiency,
scalability, and flexibility — qualities that make it ideal for embedded and power-sensitive applications.

1. The Origins and Evolution of ARM

ARM traces its roots back to the 1980s at Acorn Computers in the United Kingdom.
Originally designed to power personal computers, ARM quickly evolved into a licensing-based business model.
Instead of manufacturing chips, ARM develops processor architectures and CPU IP cores, which semiconductor
companies can license and integrate into their own system-on-chips (SoCs).

• ARM designs the ISA and CPU cores.


• Chip vendors (Qualcomm, Apple, Rockchip, NXP, MediaTek, Samsung, etc.) integrate these cores with GPUs, NPUs, memory controllers, and I/O blocks.


• Final products appear in mobile devices, SBCs, automotive ECUs, wearables, and cloud servers.

This licensing ecosystem allows ARM technology to scale from microwatt IoT sensors all the way
to multi-core server processors.

2. RISC Philosophy: The Foundation of ARM

ARM belongs to the RISC (Reduced Instruction Set Computer) family. Compared to CISC architectures like x86,
RISC focuses on simplicity and efficiency. Key principles include:

• Simple, fixed-length instructions for predictable execution and easier pipeline design.


• A large general-purpose register set to minimize memory access.


• Load/store architecture, where only specific instructions access memory.


• High efficiency per watt, making ARM ideal for mobile and embedded devices.

Over time, ARM has added advanced features — such as NEON SIMD, TrustZone security, and vector extensions —
while preserving its RISC fundamentals.

3. Major ARM ISA Generations: ARMv7, ARMv8, and ARMv9

3.1 ARMv7: The 32-bit Era

ARMv7 powered early smartphones and embedded Linux systems. Features include:

• ARM Thumb/Thumb-2 instruction sets for better code density.


• NEON acceleration for multimedia processing.


• TrustZone secure execution mode.

Popular cores such as Cortex-A8 and Cortex-A9 belong to this generation.

3.2 ARMv8: The 64-bit Transition

ARMv8-A introduced the 64-bit AArch64 architecture while retaining backward compatibility with 32-bit AArch32.
Its improvements include:

• 64-bit registers and larger virtual address space.


• A modernized exception and privilege model.


• Improved floating-point and SIMD performance.

ARMv8 enabled ARM’s shift from mobile devices to servers and high-performance computing.

3.3 ARMv9: Security and Vector Computing

Launched as the next major evolution, ARMv9 strengthens security and accelerates AI workloads.
It includes:

• ARM CCA (Confidential Compute Architecture) for secure execution environments.


• SVE2 (Scalable Vector Extension 2) for AI, DSP, and HPC tasks.


• Enhanced debugging and memory safety improvements.

4. ARM Processor Families

ARM divides its CPU IP into specialized series, each targeting different market needs.

4.1 Cortex-A: Application Processors

Designed for rich operating systems such as Android, Linux, and Windows on ARM. Features include:

• MMU and virtual memory support.


• Multi-level caches, out-of-order execution, and advanced pipelines.


• Used in smartphones, SBCs, automotive IVI, and industrial HMI systems.

4.2 Cortex-R: Real-Time Processors

Targeting mission-critical applications requiring deterministic responses:

• Low-latency interrupt handling.


• Lockstep and ECC features for safety.


• Used in automotive control units, HDD controllers, and communication modems.

4.3 Cortex-M: Microcontrollers

Cortex-M processors dominate the MCU market:

• Low power consumption.


• Integrated peripherals such as NVIC, timers, and GPIO.


• Common in IoT nodes, appliances, and small industrial devices.

4.4 Neoverse: Data Center and Network Infrastructure

Neoverse cores power cloud servers and networking equipment:

• High core counts and server-class performance.


• Excellent virtualization support.


• Used in ARM-based cloud instances from AWS, Google, Azure, and Alibaba Cloud.

5. Advantages of ARM Architecture

5.1 Exceptional Energy Efficiency

ARM processors deliver excellent performance per watt, making them ideal for:

• Battery-powered consumer devices.


• Industrial systems requiring 24/7 uptime.


• Edge computing and micro-servers with thermal constraints.

5.2 Highly Customizable SoCs

Because ARM provides IP rather than complete chips, vendors can tailor SoCs for their exact needs.
This allows integration of:

• GPUs, NPUs, VPU modules.


• Custom I/O interfaces (MIPI, LVDS, PCIe, Ethernet, CAN, etc.).


• Automotive-grade safety mechanisms and industrial-grade reliability.

5.3 Mature Software Ecosystem

ARM enjoys broad software support:

• Mobile systems: Android and iOS.


• Embedded Linux: Buildroot, Yocto, Debian, Ubuntu.


• Cloud computing: full support for ARM64 in major distributions, container platforms, and databases.

This ecosystem lowers development cost and accelerates time-to-market.

6. Challenges and Design Considerations

• Fragmented BSP quality across different SoC vendors.


• Long-term supply concerns for industrial and automotive projects.


• Debug and tooling differences compared to x86 environments.


• Performance evaluation must be workload-specific, especially for memory- and vector-heavy tasks.

7. ARM’s Role in Modern Computing

Today’s computing landscape demands both high performance and high efficiency.
ARM fits naturally into this trend:

• Dominant in mobile and embedded markets.


• Rapidly expanding in cloud and HPC workloads.


• Providing end-to-end silicon solutions for IoT, industrial systems, and automotive platforms.

As the industry continues shifting toward heterogeneous computing and energy-optimized architectures,
ARM’s combination of performance, efficiency, and ecosystem maturity ensures it will remain
one of the most important processor architectures for years to come.

Deploying YOLOv8 on Rockchip NPU Using RKNN

Rockchip’s NPU platform introduces a complete toolchain built around the RKNN model format.
RKNN files, typically ending in .rknn, are optimized models designed specifically for
Rockchip NPU hardware. To support developers, Rockchip provides a full suite of model conversion
tools, including Python APIs for RKNN-Toolkit2 along with C/C++ and Python runtime interfaces on
device. Together, these components streamline the deployment of deep-learning algorithms from desktop
development environments to embedded edge devices powered by Rockchip SoCs.

Overview of the Rockchip NPU Software Stack

The Rockchip NPU SDK is divided into two major parts: the desktop-side tools and the device-side runtime.
On a PC, developers use RKNN-Toolkit2 to convert mainstream deep-learning models—
including Caffe, TensorFlow, TensorFlow Lite, ONNX, DarkNet, and PyTorch—into the RKNN format.
The toolkit also enables simulation-based inference, performance analysis, and memory usage evaluation
directly on the desktop, making it easy to estimate deployment results before transferring models to hardware.

On the target board, Rockchip provides a runtime environment consisting of a set of C APIs, Python
bindings, communication drivers, and essential executables. This runtime environment ensures that RKNN
models generated by RKNN-Toolkit2 can execute efficiently on the NPU. The entire RKNN software stack
is designed to help developers rapidly deploy AI workloads onto Rockchip-based systems.

The following components form the core of the ecosystem:

• RKNN-Toolkit2: A software development kit for converting, simulating, and evaluating AI models on PC or Rockchip NPU platforms.


• RKNN-Toolkit-Lite2: A lightweight Python deployment interface intended for direct use on Rockchip NPU devices, simplifying inference workflows.


• RKNN Runtime: A C/C++ runtime for executing RKNN models directly on Rockchip NPU hardware.


• RKNPU Kernel Driver: The low-level driver responsible for interacting with the NPU hardware. It is open-source and available within Rockchip’s kernel repositories.

Capabilities of RKNN-Toolkit2

RKNN-Toolkit2 provides a convenient Python interface for model conversion and inference on a PC.
With this toolkit, developers can:

• Convert Deep-Learning Models: Convert Caffe, TensorFlow, TensorFlow Lite, ONNX, DarkNet, and PyTorch models into RKNN format. The converted RKNN files can be exported, imported, and deployed on Rockchip NPU devices.


• Quantize Models: Convert floating-point models into fixed-point models using asymmetric quantization (asymmetric_quantized-8). Hybrid quantization is also supported.


• Simulate Inference: Run inference using the RKNN model on a PC to simulate NPU execution, enabling developers to validate outputs before deployment.


• Evaluate Performance: Send the model to an NPU-equipped device to measure execution speed and memory consumption.


• Analyze Quantization Accuracy: Compare layer-by-layer outputs between floating-point and quantized models using cosine similarity, helping identify quantization-sensitive operations.


• Encrypt Models: Encrypt RKNN models using specified security levels. Encryption occurs within the driver, meaning encrypted models load and run identically to normal models.

RKNN SDK supports mainstream Rockchip chips such as RK3566, RK3568, RK3576, and RK3588.
A typical development environment requires Ubuntu 20.04 (64-bit), Python 3.8, and at least 16GB RAM.

YOLOv8: A SOTA Vision Model Meets Edge Deployment

In January 2023, Ultralytics released YOLOv8, the newest generation of the popular YOLO model
family. Presented as a state-of-the-art, cutting-edge vision framework, YOLOv8 is designed to support
an extensive range of visual AI tasks—including image classification, object detection, instance segmentation,
pose estimation, and even multi-object tracking.

One of YOLOv8’s strengths lies in its diversified model lineup. Ultralytics provides five pretrained
variants: YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x. These range from lightweight models suitable
for edge devices to high-accuracy variants ideal for demanding applications. Compared with YOLOv5 of
similar size, YOLOv8 achieves significantly higher accuracy on the COCO dataset, thanks to improvements
in architecture, training methods, loss functions, and anchor-free designs.

Where YOLOv8 Shines

• It offers strong accuracy improvements while still running efficiently on lightweight platforms.


• The command-line interface allows easy training, inference, and model export.


• Its built-in integration with tracking algorithms such as BoT-SORT and ByteTrack enables robust tracking applications.


• The FastSAM segmentation approach uses YOLOv8’s backbone for generalizable mask-generation tasks.

Because of these advantages, YOLOv8 has become a strong candidate for edge-based vision systems such as
robots, surveillance devices, autonomous machines, and embedded smart cameras.

Understanding the Model Deployment Process

Deploying a machine-learning model means placing it in a real operating environment where it can perform
tasks for an actual product or service. During deployment, models often undergo optimization steps such as
operator fusion, graph restructuring, post-training quantization, and knowledge distillation. This ensures
that the model runs efficiently on specialized hardware while meeting power and latency constraints.

From Training Framework to Inference Engine

Most models are initially developed using flexible frameworks like PyTorch or TensorFlow. However,
deployment platforms frequently rely on specialized inference engines such as TensorRT, ONNX Runtime,
or Rockchip’s RKNN Runtime to achieve real-time performance.

To bridge these environments, Facebook and Microsoft introduced ONNX in 2017—a universal model
representation format that allows conversion between training and inference frameworks. As a result,
the deployment process typically follows the workflow:

Training Framework ’ ONNX Representation ’ Hardware-Specific Inference Engine

Instead of manually rewriting models layer by layer, today’s conversion tools rely on graph tracing.
Given a sample input, the tool traces intermediate operations and reconstructs the computational graph,
which becomes the converted model. In RKNN conversion, sample inputs also help determine quantization
parameters.

Deploying Models on Rockchip NPU Using RKNN

RKNN is the official inference framework for Rockchip NPUs. It enables optimized execution of
deep-learning models on NPU hardware, ensuring high throughput and low power consumption.
The rknn-toolkit ecosystem provides Python APIs for:

• model conversion


• post-training quantization


• simulation inference


• validity checking and debugging

A typical RKNN deployment pipeline consists of:

1. RKNN Model Configuration
   Specify preprocessing parameters, mean values, quantization type, platform, and other settings.



2. Model Loading
   Import the source model (ONNX, PyTorch, TensorFlow, Caffe, etc.). Developers can also designate output nodes, which affects how the model is sliced during conversion.



3. RKNN Model Building
   Perform quantization if needed and supply calibration datasets.



4. Model Export
   Save the final .rknn file for deployment on Rockchip hardware.

Rockchip RK3576/RK3588 NPU Highlights

Rockchip’s high-performance AIoT platforms—particularly RK3576 and RK3588—feature powerful NPUs
built on advanced 8nm processes. Delivering up to 6 TOPS, these NPUs handle compute-intensive
tasks such as:

• image classification


• object detection and recognition


• face recognition


• speech processing


• natural language understanding

Rockchip NPUs support mainstream deep-learning frameworks including TensorFlow, PyTorch, Caffe, and MXNet,
allowing developers to train models in familiar environments while benefiting from accelerated inference
on embedded devices. Their strong ecosystem makes them well suited for large-scale computer vision
applications such as surveillance, autonomous driving, industrial robotics, and medical imaging.

Conclusion

By combining the flexibility of YOLOv8 with the high-performance capabilities of Rockchip’s NPU ecosystem,
developers can build powerful edge-AI applications that operate efficiently even under strict resource
constraints. The RKNN toolchain—spanning RKNN-Toolkit2, RKNN-Toolkit-Lite2, and RKNN Runtime—provides a
comprehensive workflow from model conversion to deployment. As edge AI continues to evolve, Rockchip’s
platform offers a scalable and practical solution for embedding advanced vision algorithms directly
into next-generation devices.

Small Moments, Everyday Screens, and a Little Journey Into Round TFT LCDs

Life recently has been moving a little faster than usual. I’ve been splitting my time between work,
walking around the city, exploring cafés, and reading random articles that somehow pull me into
deep technical rabbit holes. I don’t know whether it’s the colder weather or simply the rhythm of
this part of the year, but I’ve been paying more attention to small details around me — especially
the screens that quietly exist everywhere.

Screens are in places we barely notice: the ticket machine I use for the bus, a tiny display on a coffee
grinder in a local shop, the circular interface on a portable speaker, the smart thermostat on my wall,
and even the interface at the laundromat. It feels almost funny that we all interact with displays
hundreds of times per day, yet most people never think about what type of display technology they are using.

A few days ago, while waiting for my coffee, I noticed the café had installed a new grinder with a
small round display. It was stylish and clean, and somehow it made the entire device feel more
modern. That little display pulled me into reading more about why round TFT LCDs have become so
common in 2024–2025. It reminded me of the projects I worked on not long ago, where industrial
designers strongly preferred “non-rectangle displays” because modern products need a distinctive,
friendly look.

This small moment made me revisit an article I saved earlier, which explains the topic much better
than I can summarize here. It helped me organize my thoughts about how these displays are used in
different devices, especially in industrial and consumer applications. Here is the article I found
useful:

Round TFT LCD Displays: Technology, Use Cases, and Practical Guide 2025

What I found interesting while re-reading it is how many real-world devices now rely on round or
custom-shaped TFT displays. Smart home devices, vending interfaces, medical instruments, wearables,
and even modern car dashboard meters use them. They are no longer just “cute design choices.”
They have become functional components that enable simpler UI layouts, clearer interaction design,
and better use of limited surface area.

I also started thinking about all the little design decisions that product teams make. For example,
a circular UI forces the developer to rethink information hierarchy. You can’t simply copy a rectangular UI
and paste it into a circle. It requires clarity and simplicity. Maybe that is why these screens feel
more modern — they push designers to remove clutter.

Beyond aesthetics, the technology behind them has improved dramatically. Contrast, viewing angles,
brightness, and touch responsiveness are so much better compared to older modules. The price gap
between rectangular TFT modules and round versions has also become much smaller, which is probably
why cafés, gyms, beauty salons, and smart-home brands started adopting them rapidly.

On my way home that day, I looked around more intentionally. I saw a round interface on a public
bicycle rental station, a circular display on a smart lock, and another one on an interactive signboard.
It felt like I was discovering a pattern hidden in plain sight — everyday screens becoming better and
more diverse as display technology evolves.

Maybe this is why I enjoy writing these casual notes. They help me connect everyday life with the
technology behind the scenes. And sometimes, a small circular screen on a coffee machine is all it
takes to open an unexpectedly deep technical curiosity.

If you are also curious about this trend, I recommend checking the article linked earlier. It explains
the engineering side clearly without being overly technical. As someone who enjoys both technology
and small everyday observations, it was surprisingly enjoyable to read.

A Slow Afternoon Walk Through the Old Town

It’s funny how certain afternoons unfold without any plan, yet end up being the most memorable ones.
Yesterday, after finishing my usual daily tasks, I felt an urge to leave the apartment for no particular reason.
There was nothing I needed to buy and nowhere specific I wanted to go — I simply wanted to step outside and let my feet decide the direction.

I walked toward the old part of the town, a place I don’t visit often even though it’s only a short bus ride away.
The moment I arrived, I remembered why I used to enjoy it so much.
The narrow streets, uneven old stones, small balconies full of plants, and the smell of bakeries hidden in alleys all mixed together into a strangely comforting atmosphere.

One small detail caught my attention: an elderly man repairing an antique wooden chair right outside his workshop.
His hands moved slowly but confidently, as if he had done this thousands of times.
I stood there for a moment longer than I expected, just watching the rhythm of the sandpaper brushing against the wood.
He looked up, smiled politely, and continued working without saying anything — a tiny interaction, yet it felt sincere and warm.

Farther down the street, I passed a café that I hadn’t noticed before.
It had only three tables outside, each with mismatched chairs and slightly crooked umbrellas.
But the place had character — the kind you can’t design intentionally.
I sat there for a while with a simple cup of coffee, listening to a group of students discussing something enthusiastically, switching between laughter and serious debate.
Their energy somehow lifted my mood, even though I couldn’t hear every word clearly.

As the sun started to set, the town changed its tone.
Shadows stretched across the walls, the warm yellow lights flickered on, and more people appeared on the streets — couples holding hands, parents carrying children, and tourists trying to capture everything with their phones.
It felt like the town was waking up for its evening shift.

When I finally decided to head back home, I felt strangely refreshed.
Nothing extraordinary happened, yet the combination of small observations created a sense of calm I hadn’t felt in a while.
Maybe the real purpose of wandering without a plan is simply to be reminded that the world is alive even when we’re too busy to notice.

Next time, I might explore another part of the town — or maybe I’ll return here again. Some places deserve more than just one visit.