Robots in E-Comm Logistics In e-commerce logistics, especially warehousing, robots, robotic arms, and AMRs play a promising role across the entire workflow, from unloading and storage to picking, packing, sorting, outbound, and even returns. With advances in AI and machine learning, robots are now being deployed in areas beyond imagination. Robots with machine vision can unload parcels from trucks. Vision-guided robotic arms with suction grippers or mechanical claws can pick parcels and polybags from an inbound conveyor, and sort them by size and shape, then place them into respective totes and bins. AMRs can carry parcels or containers between sorting zones, conveyors, or loading docks. Instead of relying on fixed conveyors, AMRs create modular routing, flexibly scaling with demand.   Robots are not just machines replacing humans, but now collaborative systems that extend human capacity, reduce labor strain, and enable warehouses to handle massive order volumes with speed, accuracy, and flexibility. With global e-commerce robot deployments projected to exceed 5 million units by 2030, even a single minute of downtime can cost a warehouse significant lost throughput. That’s why cybersecurity can no longer be an afterthought — it must be built into the robot’s brain itself.   With Greater Power in Robots Comes Greater Risk Despite their efficiency, robot-based warehouse automation systems face enormous risks once their networks are compromised. With hundreds of robots and AMRs working in sync, a single breach in the robotic control system can cascade through the entire warehouse, halting sorting lines, misrouting shipments, and creating chaos in scheduling and inventory tracking. The financial impact is immediate: delayed orders, lost revenue, and damaged brand reputation. In a high-throughput e-commerce warehouse, every minute of disruption translates directly into lost cash flow — not to mention the costly repairs and replacements of damaged assets.   The challenges: Robots being hijacked and authorized access being denied Robots being remotely controlled by hackers Hijacked robots spreading malware to other assets   Why Traditional IT/OT Security Tools Fail What makes it worse is that traditional IT and OT security tools often fall short in AI robotics environments. IT security tools such as firewalls, antivirus software, and IAM (Identity Access Management) systems, are based on authentication and authorization, not optimized for cyber-physical assets. In the context of robotics, where systems control motors, sensors, and actuators in real time, an IT-centric tool can’t handle the need for millisecond-level responsiveness or provide safe fallback mechanisms if access is denied.   Classic OT security tools for ICS/SCADA are designed for isolated networks where devices weren’t expected to authenticate and authorize users frequently. However, robots in modern warehouses are mobile, dynamic, and connected everywhere, requiring continuous protection when moving from one place to another, which traditional perimeter-focused OT security tools can’t provide.   Safeguard Robots from the Core NEXCOM eSAF Guardian, powered by NVIDIA® Jetson Orin™ / Jetson Thor™, provides embedded cybersecurity directly inside the "brain" of robot — its controller. It introduces multi-layered defense with: Realtime OT CybersecurityDetects and mitigates cyber threats instantly, ensuring minimal impact on industrial processes. Network MonitorAnalyzes network traffic for anomalies, policy violations, and intrusion attempts via deep packet analysis. System Call MonitorTracks low-level system interactions to detect abnormal or unauthorized activities that may indicate malware or system compromise. File Access MonitorMonitors file usage and access patterns to prevent unauthorized modifications, data theft, or tampering. IEC 62443 ComplianceEnsures global OT cybersecurity standards are met from the very beginning of the product development phase.   Blocking threats from the outside helps, but protecting from within goes further, which enables more accurate detection of unidentified malware through its real actions, not just signatures.     AI in Action Utilizing OT time-series data, the LSTM (Long Short-Term Memory) model is a powerful tool for ML-based prediction, well-suited for scenarios with recurring behavioral patterns. For example, the model can be used to predict the number of device connections of sensors, scanners, or gateways every ten minutes, which helps detect operational deviations and potential cybersecurity incidents. In simple terms, the robot learns its own ‘normal’ behavior — and flags anything that looks off, before it causes downtime.   Through the NEXCOM eSAF Platform Manager, users can train models on at least one week of data for each device and define expected operational threshold ranges. When actual behavior deviates from the predicted range, alerts are automatically triggered. This approach enables intelligent anomaly detection and alerting without relying on traditional rule-based systems.   Benefits By integrating NEXCOM eSAF Gaurdian, robot manufacturers and system integrators gain: Comprehensive Asset Protection Coverage: Extends to Robots and AMRsBeyond common field assets, every embedded node now gains proactive defense. eSAF Guardian protects various robot configurations including humanoid, quadruped, and wheeled types from hijacking, covering the whole warehousing scenarios. Faster Incident Response: Days to HoursWith integrated monitoring of system calls, file access, and network traffic, anomalies are flagged instantly, reducing incident investigation time from days to hours. Reduced MTTR: Hours to MinutesReal-time detection of hijacking attempts and abnormal behaviors prevents unplanned production stoppages, cutting mean time to recovery (MTTR) from hours to minutes. Regulatory Compliance: IEC 62443Aligns with global industry standards at the component level, facilitating robot development and enabling system integrators to capture untapped market opportunities faster. Future-Proof Security with AIAnalyzes network traffic and device behavior to identify deviations from normal operating patterns, continuously evolving with new attack techniques.   As the world’s warehouses evolve into autonomous ecosystems, NEXCOM’s eSAF Guardian turns every robot into a self-defending asset, securing operations, protecting data, and ensuring no robot ever becomes a hacker’s target again.   NEXCOM can help you build safer, smarter robots — from the core to the cloud.

Background The chemical manufacturing sector is a cornerstone of the global economy. According to the International Council of Chemical Associations (ICCA), it contributes $5.7 trillion annually — approximately 7% of global GDP — and supports over 120 million jobs. As the fifth-largest manufacturing sector, it generates $1.1 trillion in direct output each year.   In Taiwan, the chemical industry holds similarly critical importance, ranking third in manufacturing output in 2022, behind only electronics and metal machinery. The sector — from petroleum refining to synthetic fibers — relies on continuous production lines where long, uninterrupted equipment runs are essential and process stability is crucial. Even minor deviations in key parameters can compromise product quality and pose safety risks. While historically reliable, traditional quality monitoring methods such as routine inspections, SPC charts, and operator experience are becoming less effective as product complexity increases and process variables multiply.   NEXCOM and Profet AI have surveyed the market and consulted with numerous companies across the pan-chemical industry to identify the lingering pain points on production lines. Discover how their joint solution tackles the challenge by bringing AI into physical world.   Where the Gaps Were When deviations in product quality occurred, such as shifts in purity or physical properties, teams often spent days searching for the root cause. This typically involved sifting through equipment logs, cross-checking historical parameters, and running trial batches to isolate the issue. But in an environment where time-to-correction matters, this kind of approach fell short:   Highly interdependent parameters made it difficult to pinpoint the root cause of quality issues Trial-and-error approaches prolonged process adjustment cycles Heavy reliance on tacit knowledge slowed response and hindered reproducibility Lack of reliable edge processing platform that provides both AI computing capabilities and legacy device compatibility   Physical AI: From Hardware, Software, to Physical World NEXCOM's industrial PC, combined with Profet AI’s AutoML platform, empowers process engineers to locate the root causes of quality fluctuations by AI training and inference.   NEXCOM TT 300-A3Q is a compact and high-performance system designed for factory automation and AI model training. Its PCIe x16 expansion slot can accommodate high-end GPU, providing the essential computing power for AI training and other advanced applications. The 4 x COM ports and 2 x GbE LAN ports offer ultimate connectivity to field devices, and the 2 x HDMI® & 2 x DP ports are perfect for quad 4K HDR displays, providing the elastic configurations of display matrix for intelligent operation center.   Via NEXCOM TT 300-A3Q, the AutoML platform receives process data from the production line, including temperature, pressure, liquid level, and flow rate. With the platform's no-code interface, engineers easily build predictive models on historical datasets, linking process variables to quality outcome. Key contributing factors are presented through inference by the models, allowing engineers to focus on the parameters that mattered most. Engineers can also explore how different operating conditions influence quality predictions using the models, which provides early visibility into potential outcomes, proactively guiding parameter adjustments even before the results are available.     Reframing the Approach: What You'll Discover A clearer picture of which variables are driving product variation Faster diagnosis of abnormal conditions: Trial-and-error cycles reduced by 57%~61% Precise guidance for parameter adjustments: Validation time drops from 3-5 days to less than 1 day Product stability improves by 28%   Importantly, none of these gains requires reorganizing teams or building an enormous analytics team. The breakthrough comes from equipping the people closest to the work with the right tools.   More Than a Fix, a Repeatable Process What once relied solely on experience becomes something visual, traceable, and reusable. Each model built is automatically documented — its structure, input, output, key variables, and how predictions perform is all well recorded. This transformation turns individual process knowledge into shared organizational intelligence.   It is not only a one-time success; it marked the beginning of a repeatable improvement system, where lessons learned on the field can be reproduced, scaled, and shared across teams and production lines anywhere.   About NEXCOM: https://www.nexcom.com/index.html

Taiwan's Semiconductor Edge Creates Unprecedented Pressure Taiwan’s leadership in semiconductors is the result of decades of investment and deep technical expertise. However, as the industry advances toward smaller nodes, complexity increases significantly. Parameter interactions become more sensitive, product launch cycles accelerate, and process windows narrow. The traditional reliance on experience-based optimization can no longer keep up with these demands.   When you factor in high measurement costs and delayed feedback from metrology tools, the pressure on frontline teams becomes immense. The urgency to improve is constant, yet improvement cycles remain slow and cumbersome. While some companies respond by expanding centralized data teams or investing in massive data lakes, these top-down solutions often overlook the most critical resource: the process knowledge of engineers.   See how NEXCOM and Profet AI's consulting services delivered a solution to empower process engineers, further expanding their expertise with AutoML software and AI computing systems.   Challenge In semiconductor manufacturing, the gap between identifying a problem and resolving it is often measured in weeks, not hours. The crucial process—virtual thickness measurement for CVD (chemical vapor deposition)—may not be the most glamorous application of AI, but it highlights a fundamental truth about the current state of smart manufacturing.   For years, the conversation around AI in factories has centered on technological feasibility. However, in practice, the real bottleneck isn’t the technology; it’s access. The process engineers who understand the problems best—like the subtle interactions between pressure, flow, and temperature—are often the least equipped to build the data models needed to solve them.   We witnessed this firsthand at a major semiconductor company. Despite having a dedicated team of data scientists, most process improvement ideas from the engineering team never made it to the top of an already long priority list. Engineers were eager to solve these problems themselves, but the tools were too fragmented, and the modeling process felt inaccessible. This isn't a data problem; it's a usability problem.   Virtual Metrology for CVD In this context, the company introduced Profet AI’s AutoML platform with a simple goal: to let process engineers build and deploy their own predictive models without waiting in line for data scientists.   CVD is a precision-heavy and time-consuming step where film thickness and uniformity are paramount. The traditional workflow involves running trial batches, relying on senior engineers to tune parameters, and waiting for offline inspections to validate results. This feedback loop is slow, and by the time a deviation is found, corrective actions often come too late.   Using the platform, engineers uploaded their historical process data including pressure, gas flow, temperature, timing, and more as the dataset. Within a few hours, they had built and validated models capable of accurately predicting film thickness and uniformity.   Integrated AI Computing System Profet AI’s AutoML platform is installed in the NEXCOM's TT 300-A3Q, a powerful industrial PC with a PCIe x16 expansion slot for advanced GPU support. Designed to support AI model training and inference, the system is powered by 12th/13th Gen Intel® Core™ processors and accelerates workloads with Intel® OpenVINO and Intel® Deep Learning Boost, making it a perfect companion for the AutoML software.   Comparing to other high-performance products, the NEXCOM TT 300-A3Q's compact size could seamlessly integrate into the limited space, demonstrating its remarkable performance even in the challenging conditions of high temperatures and humidity. The device operates efficiently within a wide temperature spectrum of -5°C to 55°C and a humidity range of 10% to 95%. With all I/Os at front, it is designed for easy maintenance and installation.   The system also supports AI deployments across the factory ecosystem, from edge DAQ (Data Acquisition) to MoM (Manufacturing Operations Management) system, and ultimately integrates with enterprise systems like ERP and MES. AI analyzes incoming operational data from field equipment/PLCs and powers insights in a centralized “Enterprise War Room,” enabling real-time monitoring and KPI-driven decision-making across many AI-enabled modules such as production line monitoring, energy management, and cybersecurity.   In short, NEXCOM TT 300-A3Q transforms traditional factory operations into AI-powered smart manufacturing hubs, enhancing automation, responsiveness, and operational intelligence.   The Numbers: Less Waiting, More Engineering The impact wasn’t in adding more AI—it was in eliminating the wait. The results shifted the team’s entire workflow:   Pre-production parameter setup, which used to take 4 hours, was cut in half to 2. Quality predictions became available in near real-time, eliminating the delay from physical inspections. Physical measurement costs plummeted by an estimated 70%. Most importantly, the overall process yield improved by approximately 2%.   The change wasn’t just about gaining access to a new tool—it was about empowering engineers to act directly on their own process expertise.   From a One-Off Project to a Repeatable System This approach also addresses a common failure point for AI projects: successful models that remain "black boxes" and cannot be scaled because they weren't properly documented.   With the AutoML platform, every step from data selection to model tuning and performance validation, is automatically logged in the platform. This creates a structured, transparent record that allowed future teams to revisit, reuse, and build upon prior work. What starts as a one-off success could now become a repeatable and scalable process.   The True Shift: Empowering Engineers, Not Replacing Them The core challenge in smart manufacturing has never been a lack of data or a shortage of problems to solve. It has always been a bottleneck of usability.   When process engineers are empowered to test their own ideas and build models directly, companies can finally unlock the hidden value in the vast data they already collect. Profet AI's platform and NEXCOM's IPC didn't just provide a tool; it introduced a brand new, more intuitive way of working. When those closest to the problem are empowered to find the solution, AI moves beyond a buzzword on a presentation slide and becomes a practical part of the daily toolkit.   The future of industrial AI isn’t about making engineers into data scientists—it’s about making data science accessible to engineers.   About NEXCOM: https://www.nexcom.com/index.html

The AI landscape continues to shift rapidly, reshaping how we live, work, and engage with technology. At the forefront of this transformation is generative AI, which touches everything from entertainment and fashion to software development and customer service. Among its most transformative innovations are LLMs (Large Language Models), pre-trained on massive datasets to enable translation, summarization, and text generation. These technologies are already reshaping sectors such as smart retail – enhancing customer experiences and delivering deeper operational insights – and smart cities, where they are being used to improve public safety through advanced surveillance and data analysis.   Meet the AIEdge-X®310 To empower retailers and other AI-enthusiastic businesses in staying competitive and future-ready, NEXCOM proudly unveils its newest Edge AI computer: the AIEdge-X®310. This latest addition to our Edge AI computing family is engineered for flexibility, performance, and scalability. Users can configure their system with a powerful mix of Intel® Core™ CPUs and NVIDIA GPUs tailored to AI applications in retail, healthcare, public safety, and beyond. With versatile I/O connectivity and adaptable expansion options, this high-performance computing solution is ready to handle the considerable demands of LLM processing, real-time analytics, and AI inference at the edge.   Real-world applications galore The AIEdge-X®310 is purpose-built for Edge AI retail and Edge AI security. Its LLM capabilities enhance self-service kiosks, autonomous mobile robots (AMRs), and smart surveillance systems to create smarter, safer, and more responsive environments.   Kiosks integrated with LLMs can deliver personalized assistance, helping shoppers navigate stores more intuitively. AMRs can escort customers directly to products, streamlining the in-store journey and improving satisfaction.     Smart surveillance, powered by connected IP cameras, enables users to analyze the behavior of shoppers and large crowds, monitor foot traffic, and detect suspicious activity in real time. These insights help optimize merchandising, streamline operations, and enhance safety. Public safety professionals can also leverage these capabilities to identify unattended items or detect pedestrians in restricted zones. Beyond retail and security, LLM technology supports use cases such as data mining, 3D modeling, and healthcare management — the possibilities are virtually limitless.   Choose your ideal CPU/GPU combo High-performance AI tasks demand top-tier processing capabilities. That’s why the AIEdge-X®310 offers a customizable lineup of Intel® Core™ CPUs and NVIDIA GPUs. Choose from 14th, 13th, or 12th generation Intel® Core™ processors — including i9, i7, i5, and i3 — in either 65W or 35W configurations. For tasks requiring robust performance and multitasking, the Intel® Core™ i9-14900 (65W) stands out for its speed, availability, and long-term support.   On the GPU side, select from NVIDIA’s GeForce RTX, Quadro, or RTX series to meet your specific AI deployment goals. For use cases such as computer vision, smart surveillance, or AI inference, the GeForce RTX (including the RTX 50 series) offers a strong balance of performance and value. For more demanding workloads like AI model training and real-time analytics, where accuracy and long-term stability are critical, the Quadro and RTX lines deliver enterprise-grade reliability for your AI GPU computer.   Comprehensive I/O and expansion flexibility Designed with rich I/O capabilities, the AIEdge-X®310 seamlessly integrates into smart retail and industrial ecosystems. Dual LAN ports allow main/backup network configurations for higher reliability, segmentation of internal and external traffic to enhance information security, and simultaneous cloud platform access for secure, centralized management. To serve as an AI vision system, multiple USB 3.2 and 2.0 ports support IP camera integration for live monitoring and video analytics (e.g., people counting, behavior detection), along with environmental sensors for real-time temperature and air quality tracking. Serial ports provide connectivity for card readers used in access control, membership programs, and payment processing.   The system includes up to three full-size expansion slots to further extend its AI functionality. For example, users may install two GPU cards and either a PoE module for IP cameras or sensors – or a high-speed LAN card to enhance networking. A reinforced, adjustable GPU bracket protects installed graphics cards, maintaining stability even in harsh operating conditions.   Main Features Support 14th/13th/12th Gen Intel® Core™ i9/i7/i5/i3 processor Support optional M.2 module for storage Support 2 x SATA 2.5” SSD Support 2 x DP, 2 x LAN (1GbE/2.5GbE), 2 x COM, 4 x USB 3.2 Gen 1, 2 x USB 2.0 PCIe slot supports PCIe 5.0 x16 graphics card up to 350W Industrial AI system: stylish design with powerful computing Validated with the NVIDIA GeForce RTX 50 series and Quadro series graphics cards, up to the NVIDIA RTX 6000 Ada Generation   Ordering Information   AIEdge-X®310 (P/N:10W20X31000X0) Industrial AI computing system at the Edge, powered by 14th/13th/12th Gen Intel® Core™ processor

AI 已成为铁路自动化的重要技术。ATC 3750-IP7-8M 搭载高性能 NVIDIA® Jetson AGX Orin™ SOM，在 AI 处理和推论可提供高达 200/275 TOPS 的工作负载，支持先进驾驶辅助系统 (ADAS)、车牌自动识别 (ANPR)、自动移动机器人 (AMR)、机器学习 (ML)、智能交通系统 (ITS)、铁道安全和工厂自动化等 Edge AI 车载应用。  受益于 NEXCOM 卓越的散热解决方案，ATC 3750-IP7-8M 无需风扇套件可在恶劣环境中运作，透过散热设计功耗 (TDP)15W~60W 实现 200/275 TOPS 的工作负载性能。 ATC 3750-IP7-8M 是符合 IP67 防护等级的坚固轻巧型铁路 Edge AI 车载平台， 具有以下特点：支持 9~36VDC/24VDC 和 点火控制，8 个 MIPI/GMSL2 用于连接 MIPI CAM/LiDAR 传感器，以及丰富的 I/O 接口，包括 GbE/2.5GbE、USB3.2、隔离型 CANBus、RS232、Console、DI/DO、OTG 和 HDMI。透过安装 5G NR 和 Wi-Fi 5/6 模块，ATC 3750-IP7-8M 可以与 CPS 协作进行 AI 模型重新训练，使其适用于部署在先进驾驶辅助系统(ADAS)、车牌自动识别 (ANPR)、智能交通系统 (ITS)、建设等相关应用中。 在恶劣环境下，ATC 3750-IP7-8M 可以在 -25~70°C 的宽温范围内运作，并符合 MIL-STD-810H 军用标准的抗震动和抗冲击要求。在法规方面，ATC 3750-IP7-8M 通过了 CE/FCC A 类、UKCA、EN50155 和 EN45545-2 认证。  

这款强大的自动化工业计算机，核心搭载高效能的 Intel® Core™ 处理器，为您的工业应用提供坚实的运算基础。更重要的是，它配备了丰富的扩展槽，赋予系统高度的弹性，能够轻松整合 AOI (自动光学检测) 机器人控制、先进的视觉辨识系统，以及各式工厂智能自动化所需的模块。

深入了解 NEXCOM 先进的强固型工业计算机系列，专为应对户外部署的严峻考验而精心打造。全系列产品具备高达 IP65/IP67 的防护等级，能够有效抵御恶劣天气、粉尘与液体的侵袭，确保在极端温度环境下依然稳定可靠地运作。

全球边缘 AI 运算与智能自动化解决方案领导厂商 NEXCOM 新汉集团将参展 2025 NVIDIA GTC 大会。NEXCOM 新汉将于现场展出创新的 AI 技术，发表全球首款搭载 NVIDIA® Jetson AGX Orin™ 模块的 Dual EtherCAT AI 机器人控制器，内建 NEXCOM 新汉自主开发的实时操作系统，支持双重 EtherCAT 主站架构，实现高精准度实时运动控制，提升机器人应用效能。此外，新汉也将展示应用于交通运输系统的备援电池模块 BBU（Backup Battery Unit）及用于行动边缘 AI 运算的智能车载计算机 ATC（Advanced Telematics Computer）。 展出重点：   双重 EtherCAT 主站 AI 机器人控制器（Dual EtherCAT Master AI Robot Controller）： NEXCOM 新汉最新的双 EtherCAT 控制架构可解决单一 EtherCAT 控制架构所面对的稳定性、效能不佳及运作延迟等难题。此款控制器专为高阶自动化应用设计，具备超低延迟同步功能，可支持多个 EtherCAT 从站模块，实现多轴协同运动控制，适用于各种构型机器人，如人型机器人、四足机器人及机械手臂。搭载 NVIDIA JetPack™ SDK，以 AI 运算能力提升机器人视觉辨识与动作效率，使机器人能因应环境状态动态调整运作决策。此解决方案可应用于工业自动化、制造业与物流业的智能工厂、装配线与机器人物料搬运等场域。   VTK-SCAP 备援电池模块（BBU, Backup battery unit）： VTK-SCAP 专为车辆/铁路计算机设计，是一款先进的超级电容电池备援电力模块（BBU)，其复杂的电源管理系统可提供不间断的电源稳定性。VTK-SCAP 具有更高的充放电效率，可维持最大输出功率 200W。透过扩充模式（1 x VTK-SCAP-M + 3 x VTK-SCAP-S），VTK-SCAP 可支持 60W 系统运作长达 6 分钟。   智能车载计算机 ATC 系列产品： ATC 系列产品搭载 NVIDIA® Jetson™ 平台，提供实时 AI 推论能力，适用于大众运输、客用车载系统与轨道应用。ATC 系列强固型产品具备高度耐用性，包括 IP67 等级防护能力以及宽温等特色，能在摄氏 -40°C 至高温70°C 的严苛环境中长时间稳定运作，应对行驶中所遇到的各种状况。   2025 NVIDIA GTC AI 大会 活动详情: 活动日期: 2025 年 3 月 17 日至 21 日 活动地点: 美国加州圣荷西会议中心 (San Jose Convention Center) 活动摊位: 编号 1738 展位     (透过此连结进行活动注册，可享门票八折优惠)

畜牧业正面临着管理牲畜和优化农场运营的重大挑战。其中一个主要障碍是准确的乳牛生产数据监控，包括身分识别、健康状况、产奶量和食品生物安全等…。目前的数据收集和分析依赖于人工方法，导致及时的追踪和数据驱动的决策变得更加困难。缺乏实时数据和洞察力可能导致浪费，并对乳牛健康和生产力产生负面影响。为了应对这些挑战，物联网Gateway提供了一种创新的解决方案。NEXCOM 的 NDiS B561S 是一款轻巧的嵌入式无风扇计算机，作为一个全面的智慧农业解决方案，它能与乳牛电子卷标无缝整合，实现精准监控、自动化数据收集、营养分析，并优化资源分配。   NDiS B561S 嵌入式无风扇计算机搭载 Intel® Core™ i5-8500T 处理器，提供无缝连接，通过准确识别和追踪个别乳牛，有效提升乳牛健康和性能。该系统可便捷串联繁殖记录、健康指针和牛奶产量…等实时数据，为操作员提供重要讯息，以便就营养、繁殖策略和必要的医疗行为做出明智的决策，实现智慧农业。   物联网Gateway还可透过 M.2 2230 Key E 串接温度和湿度传感器，以进行周遭环境监控，减少热伤害和其他潜在的对乳牛健康不利条件的风险。透过整合 LAN 和 Wi-Fi 功能，以及直觉的触控式 HMI 接口，农场操作员可远程监控农场运营状态。操作员随时取得 RFID 卷标的实时数据，接收实时警报，并从任何地方做出明智的决策，显著提高效率和灵活性。   透过创新的 NDiS B561S 嵌入式无风扇计算机和乳牛卷标，畜牧业可以彻底改变营运方式，验证牲畜数据，并减少传统纸笔记录造成的人为错误。这种先进且可回溯的解决方案大幅改善了食品安全、监管效率、资源分配。   应用架构图     产品特点   支持第 12代 Intel® Core™ i3/i5/i7 LGA 插槽型嵌入式处理器，最高达35W Intel® PCH H610芯片 Intel® UHD 770 系列图形运算引擎 支持 2 个独立的 4K2K 60Hz 显示输出 轻巧且纤薄的设计 (H: 39mm) 支援宽温0~50°C 2 个 HDMI 2.0，2 个 USB 3.2，4 个 USB 2.0，1 个 GbE LAN，2 个 2.5 GbE LAN 3个 M.2 Key B/E/M 无风扇计算机    

應用背景 高速公路电子收费系统（ETC）是现代交通组成重要的一环，能够有效提升车辆通行效率。先进的ETC系统结合「实时车辆识别」与「黑名单监控」两种功能，可协助警方追踪车辆失窃等违法行为。该解决方案结合强大的边缘运算、高速数据处理和多元设备连接性，确保机器能在各种严苛的环境下持续运作。   解決方案 本次案例中的 ETC 系统以 Neu-X302-Q 作为主要运算设备，同时透过 NDiS B561-PoE 控制 ETC 闸门，同时透过 PoE 摄影机进行影像捕捉。在这样协同运作的架构下，实现了强大的实时数据分析，实现了有效的过路费管理和影像监控。   Neu-X302-Q： ETC 系统的强大「大脑」 Neu-X302-Q 作为主要运算设备，负责处理车辆数据、进行黑名单比对，如发现在黑名单中的车辆便会发出警报。Neu-X302-Q 的无风扇设计且搭载Intel® 第九代/第八代 Core™ 处理器和高 I/O 扩充性，使Neu-X302-Q非常适合放置于恶劣环境下，并全年无休的运作。该设备能处理大规模数据传输并及其低延迟的特性，结合以上特色，使其成为 ETC 系统的首选   NDiS B561-PoE：ETC 系统的「千里眼」 NDiS B561-PoE 搭载第十二代 Intel® Core™ 处理器，不仅能有效控制 ETC 闸门，更具备先进的影像辨识能力。透过实时影像分析，其 能迅速将车辆信息传输至 Neu-X302-Q，实现高效的数据处理。NDiS B561-PoE 搭载先进图像处理技术，能以无缝方式呈现可视化影像，PoE 功能让数据传输与电源供应合而为一，仅需单一线路，，大幅简化布线工程。其坚固耐用的设计，使其能够在各种恶劣环境下持续工作。   ETC 系统在导入Neu-X302-Q 和 NDiS B561-PoE 后，发生了革命性的变化。透过以上两项产品的导入，使得通行费的收费更加准确、高效，同时也加强了对拒缴过路费的车辆和违法行为的监控。Neu-X302-Q 与 NDiS B561-PoE 为智能交通系统开辟了新的道路，使用路人更加安全可靠。   应用架构图