Industrial Touch Panel PCs and Monitors
IP Rated Touchscreen Computers For HMI Integration
IP Rated Touchscreen Computers For HMI Integration
The digital transformation in the railway industry is steadily expanding with various innovative solutions available to modernize its traditional transit system. EN50155 Compliant in-vehicle fanless computers are a core building-block in enabling the latest railway technologies for:
EMC Conformity with EN50155 & EN50121-3-2
Wireless Connectivity
Railway-centric I/O with M12 Connectors
Computer Vision
Cableless & Fanless
The ACO-6000-CML in-vehicle computer is designed specifically for use in rolling stock applications. This computer is in line with the EN50155 standards and has the capability to connect up to 18 IoT devices at once, with support for Power over Ethernet (PoE) and M12 connection types.
The ECO-1000 Series EDGEBoost EnergyPack is an industrial-grade supercapacitor tailored to re-define power backup redundancy for mission-critical computing deployments, especially in railway infrastructure.
The integration of computer vision technologies has resulted in innovative transformations across various industries. Streamline computer vision technologies, crucial to modernizing the railway industry, with Premio’s in-vehicle computer. Applications like predictive rolling stock inspection and efficient railway traffic routing automate maintenance processes and introduce predictive analysis.
Transforming passive-feed into smart-feed. Smart surveillance significantly elevates productivity and efficiency by monitoring and analyzing various critical aspects of rail transportation. Onboard & trackside smart CCTV solutions enhance rail safety through early detection of potential issues to prevent escalations. As well as enable real-time data collection automation for timely decision-making and predictive pattern analysis.
In-cab:
Wayside:
Sensor Fusion is a critical concept that utilizes information collected from multiple types of sensors to build a more accurate model and real-time understanding of the environment. Diverse sensors including radar, lidar, and cameras are strategically deployed to monitor railway infrastructure. By synthesizing data from multiple sources, sensor fusion empowers railway systems to navigate complex and dynamic scenarios with precision, ultimately ensuring safer and more efficient transportation.
Digital train positioning plays a vital role in optimizing transit efficiencies and productivity, especially in GPS-denied environments. By utilizing real-time vehicle telematics with our in-vehicle computer, via SD-WAN, UWB, or Satacom, it enhances both operators and customers' experiences to be fully aware of the status of each locomotive.
The global railroad market size was valued at USD 281.24 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 5.6% from 2023 to 2030.
- Grand View Research
Rolling stock is subjected to a wide variety of demanding climates, including extreme weather conditions, fluctuating power irregularities, and consistent shock and vibration. When incorporating industrial computers onto rolling stock, adhering to EN50155 railway compliance is often considered necessary in most deployments. This strict standard involves rigorous testing for operational competence, ensuring equipment suitability, and longevity.
Rugged edge computers are built with enhanced durability and ruggedized features that are specifically engineered to withstand volatile environments to perform mission-critical workloads without failing. Premio’s industrial grade designs bring key technologies together with scalable and modular solutions to provide enhanced reliability and expandability that help enable rugged edge AI.
AI forms the foundation of rugged edge AI, allowing edge devices to analyze vast amounts of data in real-time and make intelligent, autonomous decisions. Combined with performance accelerators, AI algorithms can use inference to tackle complex tasks in predictive analytics and data processing, making it invaluable in rugged edge AI deployments.
Dense storage capacity allows for data storage, collection, and ease of transfer to the cloud. By leveraging cloud storage, edge devices can offload processing tasks, optimize storage capacity, and facilitate collaboration and integration with other systems
5G connectivity delivers high-speed wireless communication to reduce latency and bandwidth for data telemetry. 5G enables real-time transfer between the edge and the cloud and empowers applications where immediate responses and data transmission are critical.
Rich I/O interfaces with plug and play modularity for robust and reliable IoT sensor connectivity. Enabling the interconnectivity and communication between devices and systems, IoT devices gather and share data, allowing rugged edge AI to monitor, control, and optimize operations.
Railway applications typically surpass voltage input requirements of other industries. Our in-vehicle computer is purpose-built to accommodate 9-48VDC and 48-110VDC to adhere with EN50155 standards while providing optimal flexibility in varying railway deployments.
Stay connected while on the move with on-board dual-SIM slots and PCIe modules for seamless wide-broadband coverage (5G, 4G/LTE, Wifi, Bluetooth). Reliably exchange mission-critical data remotely for real-time insights and decision-making.
Premio is part of Intel’s Parner Alliance Program that provides special access to semiconductor silicon solutions and powerful processing technology. As Titanium members Premio designs and manufacture system level computing solutions from the edge to the cloud.
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Premio is part of NVIDIA Partner Network that provides in-depth knowledge into the latest technologies powering machine learning and artificial intelligence. Our rugged edge computing solutions are validated to support enterprise performance acceleration cards (GPUs) from NVIDIA’s portfolio of compute, virtualization, and visualization products.
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Premio’s edge computers are certified to run AWS IoT Greengrass for developers requiring a less centralized processing platform for their IoT network. AWS IoT Greengrass empowers edge computers to act locally on the data they collect and generate.
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Premio is part of Hailo’s hardware partner ecosystem that enables technology leaders to bring advanced deep learning capabilities to a variety of edge computers with domain-specific performance acceleration.
Computer vision is an imagery-based technology that detects and identifies objects from IoT cameras. When applied to railway applications, computer vision streamlines and automates defect inspection, predictive maintenance, and many other key technologies. Read more about computer vision here.
Railways use computer vision for predictive maintenance, defect inspection, rolling stock management, hazard detection, and more. These applications utilize computer vision to amplify efficiency, safety, and accuracy of the railway infrastructure.
A smart railway system is a modernized railway framework that utilizes AI technologies to significantly improve various processes of railway from predictive maintenance to safety monitoring.
As of 2023, the latest technology in railway is AI driven to improve numerous processes in the ever-growing railway industry. Computer vision has been a primary technology to detect defects and hazards in real-time.
Premio’s IoT and IIoT solutions tailored specifically for railway are: the ACO-6000 Series In-Vehicle Computer and the ECO-1000 EDGEBoost EnergyPack. The ACO-6000-CML enables and streamlines edge AI applications and provides connectivity up to 16x supported IoT devices. The ECO-1000 EDGEBoost EnergyPack utilizes supercapacitor technology for enhanced power reliability and redundancy.
A smart railway system is an AI-enhanced railway system that modernizes and optimizes various processes for improved convenience, communications, safety, and longevity. Computer vision, sensor fusion, and digital train positioning/signaling are key applications that are currently being implemented to transition traditional railway systems into a smart infrastructure.
There are two key categories where AI is utilized in railway deployments: On-board and Train-to-Ground.
On-board the rolling stock: AI computer vision is incorporated to automate inspection protocols and detect/identify objects on the track for enhanced safety and effective maintenance. Additionally, there are in-cab and wayside surveillance with on-board smart CCTV to improve both passenger safety and traffic analysis.
Train-to-Ground: Applications such as sensor fusion, railway signaling, and digital train positioning to provide real-time data telematics and accurate traffic analysis. These technologies significantly enhance railway efficiencies and management/decision-making processes.
Digital train positioning is the use of various technologies (GNSS, IMU, wayside wireless communication networks, etc.) to accurately determine a train’s location and telematics even in GPS-denied environments. Digital train signaling involves digitalizing traditional train communication systems with real-time rolling stock monitoring and communications
The digitization of railway is the adoption of advanced digital technologies, such as AI computer vision, to improve various efficiencies in the railway industry. These modernized technologies improve upon the existing railway infrastructure by introducing precise vehicle telematics for real-time data analytics and intelligent AI-driven algorithms to detect anomalies wayside and/or on-board rolling stock.
EN50155 compliant industrial computers are typically deployed into rolling stock. The standard, EN50155, is specific to deploying electronic equipment to railway applications and is to ensure that electronic equipment has been tested for functional competence under extreme rolling stock conditions. Learn more about the importance of EN50155 in this blog article here.
Industrial computers are utilized for real-time edge AI computing and as a centralized connection host to power/process all IoT devices. An industrial computer could be referred to as the brain and heart of intelligent railway systems as it seamlessly drives power to all connected IoT devices and enable AI technologies with the collected IoT data.
Intelligent railway surveillance systems or CCTV systems operate with the pairing of IoT cameras and an industrial computer. IoT cameras are incorporated on-board rolling stock or wayside. Then they are connected to an industrial computer to power the camera itself and process the incoming data the camera is gathering. AI algorithms are installed onto the industrial computer to detect and identify objects from the cameras. When an anomaly or event occurs, the computer uploads the data to dispatch for further analysis. Read more in detail in our railway surveillance case study here.
Passenger Information Systems (PIS) are transportation-specific systems that display real-time information and updates on the public transit. Interactive route maps, platform/gate assignment, delays and ETAs, and similar informative displays all utilize a PIS to help passengers get valuable information regarding their travel quickly. Read more about PIS and more here.
Railway Infrastructure Monitoring Systems (RIMS) is a culmination of technologies and tools, such as predictive maintenance, that filter critical information to dispatch for further analysis and decision-making. Due to the sheer amount of information fed to railway control centers, RIMS intakes and aggregates information to its respective categories for specialists to look further into.
Sensor fusion is the combination of data gathered from multiple IoT devices to develop a more accurate and reliable model. Learn more about sensor fusion in our latest blog article here.
