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 has become an essential component of automated vehicle technologies. With its built-in high performance NVIDIA® Jetson AGX Orin SOM, the ATC 3750-IP7-8M can deliver up to 200/275 TOPS workload on Artificial Intelligence (AI) processing and inference, supporting applications such as ADAS in Transportation/Construction, ANPR, AMR, Machine Learning (ML), ITS, railway safety assurance, and factory automation. Thanks to NEXCOM excellent thermal solutions, ATC 3750-IP7-8M can working through its defined TDP (15W~60W) at the harsh environments without fan kit to achieve 200/275 TOPS workload performance.  The ATC 3750-IP7-8M is a IP67 rated, rugged, compact-size in-vehicle/rail AI powered computer that features 9~36VDC/24VDC rail with IGN control, 8-ch MIPI/GMSL2 for accessing MIPI CAM/LiDAR sensors, and rich peripheral ports: GbE/2.5GbE, USB3.2, isolation CANBus, RS232, Console, DI/DO, OTG, and HDMI. With the installation of 5G NR, Wi-Fi 5/6 modules, the ATC 3750-IP7-8M can collaborate with CPS for AI model re-training, making it suitable for deployment in sophisticated applications such as ADAS/ANPR/AI aided ITS/Construction, etc. In harsh environments, the ATC 3750-IP7-8M can operate at a wide temperature range of -25~70°C and meet the MIL-STD-810H military standard for anti-vibration and shock. For regulation, the ATC 3750-IP7-8M is certified by CE/FCC Class A, UKCA, E-mark, and EN50155.

Intel®  Core™ Empowering Automation PC with Expandable Slots for AOI Robotics, Vision Recognition and Factory Intelligence Automation.  

Discover NEXCOM's advanced industrial computers, engineered for the challenges of outdoor deployment. With IP65/IP67 protection, these units withstand extreme temperatures and weather. NEXCOM's waterproofing techniques, including conformal coatings, waterproof foam and rubber seals, are validated by ISO 17025-certified lab testing. These solutions empower businesses with enhanced operational efficiency, reduced maintenance, and tailored configurations.

NEXCOM, a leading global provider of edge AI computing and intelligent automation solutions, will exhibit at the 2025 NVIDIA GTC conference. We will showcase our latest advancements in AI technology, including the world's first Dual EtherCAT Master AI Robot Controller developed on the NVIDIA® Jetson AGX Orin™ platform, which enables high-precision real-time motion control for enhanced robot performance. Additionally, NEXCOM will demonstrate its Backup Battery Unit (BBU) for power redundancy and intelligent Advanced Telematics Computer (ATC) for mobile edge AI computing.   Featured Highlights:   AI-powered Robot Safety NEXCOM's groundbreaking dual EtherCAT master AI robotic controller overcomes the reliability and performance challenges faced by typical single-master systems. Designed for advanced automation, the controller synchronizes complex robotic systems with ultra-low latency. Dual EtherCAT Master architecture supports multiple EhterCAT slave modules, facilitating seamless multi-axis motion control across humanoids, quadrupeds and robotic arms. Built for industrial automation, manufacturing and logistics, the controller delivers the precision and reliability required for factory automation, assembly lines and robotic material handling.   VTK-SCAP Backup Battery Unit (BBU): The VTK-SCAP is a supercapacitor-based BBU designed to provide uninterrupted power with a sophisticated power management system. Designed for vehicle/railway computers, it features higher charging and discharging efficiency with a maximum output of 200W. Through expansion mode (1 x VTK-SCAP-M + 3 x VTK-SCAP-S), the VTK-SCAP can support a 60W system for up to 6 minutes.   Intelligent Telematics Computers - ATC Series: Powered by the NVIDIA Jetson™ platform, the ATC series offers real-time AI inference capabilities and is suitable for public transportation, passenger infotainment system, and railway applications. With IP67-level protection and wide temperature adaptability, ensuring stable operation in harsh environments from -40°C to 70°C.   2025 NVIDIA GTC Details: Date: March 17-21, 2025 Venue: San Jose Convention Center, California, USA Booth: #1738     (Register now for an exclusive 20% discount on ticket )

The dairy farming industry faces significant challenges in managing livestock and optimizing farm operations. A major hurdle is accurate cow monitoring, complicating precise record-keeping of identification, health status, milk yield, and food biosecurity. Current data collection and analysis rely on manual methods, hindering timely tracking and data-driven decision making. Lack of real-time data and insights leads to potential wastage and negatively impacts cow welfare and productivity. Addressing these challenges demands an innovative solution, and IoT gateway represents a promising approach for such advancements in the industry. NEXCOM’s NDiS B560S, a slim, embedded fanless computer offers a comprehensive smart farming solution. It integrates with electronic and visual cow tags to enable accurate monitoring, automated data collection, nutrition analysis, and optimized resource allocation.   Powered by the Intel® Core™ i5-8500T processor, the NDiS B560S embedded fanless computer provides seamless connectivity, effectively enhancing cow health and performance through accurate identification and tracking of individual cows. The system facilitates real-time data access on breeding records, health metrics, and milk production, arming operators with vital information to make informed decisions on nutrition, reproduction strategies, and necessary veterinary interventions for smart farming.   The IoT gateway also accomodates temperature and humidity sensors via M.2 2230 Key E, enabling anticipatory monitoring of environmental conditions, thus mitigating risks associated with heat stress and other potential adverse effects on cow health. With integrating LAN and Wi-Fi capabilities, along with an intuitive touch HMI interface, it permits farm operators to remotely oversee and control various farm aspects. Operators can access real-time data from RFID tags, receive immediate alerts, and make informed decisions from anywhere, significantly boosting efficiency and flexibility.   Leveraging the innovative NDiS B560S embedded fanless computer and cow tags, dairy farms can revolutionize operations, authenticate livestock data, and eliminate human errors associated with traditional paper records. This advanced traceability solution improves food safety, regulatory efficiency, resource allocation, and more.   Diagram     Key Features for Application Needs   Support 8/9th Gen Intel® Core™ i3/i5/i7 LGA socket type embedded processor, up to 35W Intel® H310 Intel® integrated UHD 630 graphic engine Support 2 independent 4K2K 60Hz display output Compact and slim design (H: 39mm) Support 1 x 2.5” SATA HDD 2 x HDMI 2.0, 4 x USB 3.0, 2 x USB 2.0, 2 x GbE LAN, 4 x COM, 1 x Line-out, 1 x Mic-in Support M.2 Key B/E/M Fanless design

The Background The highway electronic toll collection (ETC) is an important part of modern transportation and can effectively improve vehicle traffic efficiency. The advanced ETC system, combined with real-time vehicle identification and blacklist monitoring functions, assists the police in tracking down vehicle theft and other illegal activities. The solution combines powerful edge computing, high-speed data processing and reliable device connectivity to ensure seamless operation under harsh highway conditions.   Solution Overview The ETC system was built using Neu-X302-Q as the main computing device and NDiS B561-PoE to control the ETC gate and also capture the images through PoE camera. These devices collaborated to deliver robust, real-time data analysis, enabling effective toll management and monitoring.   Neu-X302-Q The Neu-X302-Q served as the main computing platform for processing vehicle data, running blacklist comparisons, and triggering alerts for unauthorized vehicles. Its fanless design, Intel® 8th/9th Core™ processor, and high I/O expandability made it ideal for 24/7 operation in harsh roadside environments. The device handled large-scale data communication and ensured minimal latency, critical for real-time ETC operations.   NDiS B561-PoE The NDiS B561-PoE, powered by Intel® 12th Gen Intel® Core™ processor, not only to controls the ETC gate but also captures images of vehicles passing though ETC lane and immediately communicates with the Neu-X302-Q to process the data. Its advanced graphics support allowed seamless real-time visualization, and the PoE functionality significantly reduced wiring complexity by delivering both data and power through a single cable. Its rugged design ensured uninterrupted operations in extreme conditions.   Overall, the deployment of Neu-X302-Q and NDiS B561-PoE revolutionized the highway ETC system, enabling accurate, high-speed toll processing and offering better control over vehicles that attempt to evade tolls or engage in illegal activities. The Neu-X302-Q and NDiS B561-PoE industrial-grade computing devices can transform highway toll collection, paving the way for smarter and safer road infrastructures.   Application Diagram