Skip to Content

AI at the Display Edge

Building the roadmap for intelligent displays

Bringing Intelligence to the Screen

Hardware is getting smarter, and displays are no exception. They need to sense, interpret and react in real time.  Cloud‑hosted AI can do this, but sending every frame or sensor reading upstream is costly, introduces latency and raises privacy concerns.  Digital View’s new ALC‑4096‑AIH LCD controller is our first AI-enabled answer to this challenge.


Why AI at the display edge?

Edge inference moves processing directly into the device.  Rather than shipping data to a remote server, the sensor feeds a local accelerator and the output is immediately available at the display.  This approach reduces latency, keeps private information on site and cuts bandwidth costs.  Processing on the board offers lower latency, enhanced privacy, reduced bandwidth consumption and greater reliability.  A dedicated AI accelerator means the user experience is driven by on‑device intelligence rather than round‑trips to the cloud.

Edge processing is especially important for interactive kiosks, industrial control panels and medical instrumentation where response times matter and network access can be intermittent. Equally, for digital signage where privacy concerns impose functional restrictions that an edge processor unlocks. Positioning the AI accelerator with the LCD panel, the ALC‑4096‑AIH eliminates the need for an external mini‑PC or GPU, simplifying system design and thermal management .


What’s inside the ALC‑4096‑AIH?

The ALC‑4096‑AIH is Digital View’s first LCD controller with a built‑in AI accelerator and compute module.  It combines three functional sections on a single 127 × 101.6 mm PCB:

  • LCD controller – drives panels up to 4096 × 2160 or 3840 × 2160 with 10‑bit colour depth via V‑by‑One or eDP connectivity.  It accepts HDMI 2.0, DisplayPort 1.2 and USB‑C video inputs , provides on‑screen display controls and exposes RS‑232/IR interfaces for external buttons and remote control .
  • Compute module – a Raspberry Pi CM5 provides a Linux‑based environment with high‑performance Arm CPU, dual CSI camera inputs, PCIe 3.0 for peripherals and its own HDMI output .  This gives engineers a familiar development platform for application logic, networking and storage while keeping power consumption low.
  • AI accelerator – a Hailo AI accelerator on a PCIe M.2 connector (max power 13 W) delivers up to 26 TOPS with the Hailo‑8 module or 40 TOPS with the Hailo‑10H; a lower‑power 13 TOPS Hailo‑8L is also supported. These processors handle inference workloads such as object detection or generative AI without loading the CPU/GPU .

The board also exposes IO pins for sensors and two CIS ports for cameras, making it straightforward to integrate depth sensors, thermal cameras or other peripherals .  Gigabit Ethernet, USB 3.0 ports and SD‑card storage complete the connectivity , while an MTBF of over 500 000 hours and a three‑year warranty reflect Digital View’s industrial focus .


Accelerators beyond Hailo

Although the ALC‑4096‑AIH typically ships with Hailo acceleration, it is designed to be flexible.  Our Display Edge AI blog details support for DeepX DX‑M1, a 25 TOPS accelerator known for its power efficiency.  DeepX supports frameworks like TensorFlow, PyTorch and ONNX and runs state‑of‑the‑art networks such as YOLOv5, EfficientDet and CLIP.  

The ALC-4096-AIH can also support the Akida accelerator from Brainchip. 

This modularity allows you to choose the right balance of compute, power consumption and model support for your application.


Why a dedicated accelerator?

A specialised AI accelerator offers advantages over general‑purpose processors.  A comparison of Hailo‑8, CPUs and GPUs shows that Hailo delivers tens of TOPS of INT8 inference performance at a few watts, whereas embedded CPUs offer only a fraction of a TOP at higher power draw and GPUs deliver high performance but require large power budgets and cooling.  Inference on the Hailo‑8 is therefore fast, efficient and ideal for devices mounted behind displays.  By keeping models local, sensitive data never leaves the device and response times remain in the millisecond range .


Building smarter displays

The combination of display control, compute and AI opens opportunities across industries:

  • Smart retail signage and kiosks – tailor content based on demographics or engagement, measure dwell time or detect gestures without sending video to the cloud .  Data stays local for GDPR compliance and minimal bandwidth.
  • Industrial automation – run computer‑vision models to detect defects or abnormal conditions on production lines.  Our AI opportunities guide explains how to identify high‑ROI use cases by focusing on pain points, available data and potential impacts.
  • Medical imaging and diagnostics – assist clinicians by highlighting areas of interest on high‑resolution displays, with all processing performed in the device .  Embedded AI reduces latency and network dependence, important for mobile medical carts.
  • Security and surveillance – perform real‑time analysis of video feeds from multiple cameras connected to the board’s dual CSI ports .  Edge processing provides immediate alerts while respecting privacy requirements.
  • Multi‑modal vision – fuse RGB video with depth, thermal or infrared data.  Our article on multi‑modal vision explains how combining two cameras widens perceptual bandwidth, improves robustness and enables privacy‑preserving analytics .  Example pairings include RGB+ToF for foot‑traffic analytics, RGB+Thermal for environment monitoring and stereo RGB for depth sensing.


Sensors and data: feeding the AI engine

Edge AI depends on quality inputs.  Our Sensors & Data overview describes why sensors are crucial for real‑time AI: they collect data continuously, provide contextual awareness and let the AI respond instantly.  The ALC‑4096‑AIH supports a wide range of sensor types—cameras, microphones, environmental sensors, motion detectors, LiDAR, accelerometers and many more.  By fusing these inputs, the board can implement applications such as predictive maintenance, biometric authentication or environmental monitoring.


Learning and resources at DisplayEdge.ai

Alongside the hardware, Digital View is investing in knowledge and tools.  Our Display Edge AI website is a hub for engineers exploring edge intelligence.  Recent posts include:

  • Identifying AI opportunities – a practical framework for selecting use cases by identifying pain points, assessing data availability, matching AI capabilities and estimating ROI .
  • Data modalities – a deep dive into what types of data (images, sensor streams, audio, multi‑modal, text) are best suited to Hailo and DeepX accelerators .
  • Inference basics – an accessible explanation of inference versus training and why accelerators like Hailo‑8 excel at running trained models locally .
  • Comparison of Hailo‑8, CPU and GPU – a quick guide to the performance, power and cost trade‑offs between processing options .
  • Hailo‑8 resources – links to model zoos, SDKs and community forums .

The site is regularly updated with example applications, sensor integrations and demonstrations of our boards in action.  Engineers can sign up for updates, order evaluation kits or contact our team for guidance on selecting the right controller board.


A roadmap for intelligent displays

The ALC‑4096‑AIH is just the start.  We are working on additional boards to complement our display controllers with different compute modules and AI accelerators, giving customers the flexibility to choose their preferred ecosystem.  Support for generative AI models, large language models and multi‑modal vision is already underway .  As these technologies mature, we will provide firmware updates and application notes through DisplayEdge.ai.


Next Steps

Display Security