Connected Transportation: A Smarter Brain for Your Train with Intel
A modern locomotive, for example, has as many as 200 sensors generating more than a billion data points per second. Vibration sensors surround critical components, video cameras scan the track and cab, while other sensors monitor RPM, power, temperature, the fuel mix, exhaust characteristics, and more.
Most of today’s locomotives lack sufficient on-board processing power to make full use of all this data. To make matters worse, the data from different subsystems, such as the brakes, fuel system, and engine, remain separate, stored in isolated “boxes” that prevent unified analysis. The data is available, but the technology needed to process it in the most effective manner is not. As new sensors are added to the machine, the problem escalates.
IntelIntel designs, manufactures, and sells integrated digital technology platforms worldwide. The company's platforms are used in various computing applications comprising notebooks, desktops, servers, tablets, smartphones, wireless and wired connectivity products, wearables, transportation systems, and retail devices. It offers microprocessors that processes system data and controls other devices in the system; chipsets, which send data between the microprocessor and input, display, and storage devices, such as keyboard, mouse, monitor, hard drive or solid-state drive, and optical disc drives; system-on-chip products that integrate its central processing units with other system components onto a single chip; and wired network connectivity products.Featured Subsidiaries/ Business Units:- Intel Inside- Intel Data Center Manager (DCM)- Saffron Technology- Wind River
Logistics & Warehousing
- CONNECTIVITY PROTOCOLS
GE and Intel have come together to solve this challenge, and to lay the foundation for faster innovation across the full spectrum of industrial applications. GE GoLINC is a mobile data center that puts powerful data processing and flexible communications close to the data. GoLINC is purpose-built for rugged and remote industrial environments. It has proven its value on thousands of GE and non-GE locomotives run by nearly all of the tier one railroad operators in the United States.
GoLINC is a flexible system that holds multiple modules supporting a wide range of functions, such as wireless communications, networking, and the translation, processing, and storage of all sensor data. Individual sensor subnetworks no longer have to support all of these functions separately. For example, the proliferation of cellular antennas on a modern locomotive can be replaced by a single antenna—and a single module—that handles all communications. In addition, each high-performance GoLINC compute module can host multiple applications, including GE GoLINC Data Optimizer, third-party vendor applications, and home-grown customer applications. With this approach, hardware is consolidated, data is unified, and customers have full control over the applications that monitor and control their machines.
Unlike other on-board processing solutions, GoLINC is an open platform that can be integrated easily with diverse sensor networks, hardware modules, and software applications. Users can configure GoLINC to meet current needs, and then grow and adapt it as those needs change. Both hardware and software are built to support simple, non-disruptive upgrades.
- DATA COLLECTED
Fuel Consumption, Power Consumption, Temperature, RPM
- SOLUTION TYPE
- SOLUTION MATURITY
Emerging (technology has been on the market for > 2 years)
- OPERATIONAL IMPACT
Impact #1 [Data Management - Real Time Data Analysis]
Smarter, faster decision making.Sensor data is analyzed immediately, so time-sensitive decisions can be made without the delays associated with transferring high-volume data to a centralized data center (an inherently slow process that can be further disrupted in remote locations where cellular service is unavailable). Operators can detect and respond to issues instantly, before they escalate into more serious problems.
Impact #2 [Cost Reduction - Data Management]
Efficient, low-cost data transmission.Since sensor data is filtered and analyzed on-board, only critical alerts and other small messages need to be sent over costly cellular connections. High-volume data transfers are performed at stations to take advantage of fast, low-cost Wi-Fi connections. Given the size of the data sets, the savings can be substantial.
Impact #3 [Efficiency Improvement - Management]
Simpler and more efficient management.Intel processors are designed to enable efficient remote management of
the computing platform using proven tools and methods. GoLINC extends these advantages. As one example, hot-swap modules allow for simple, non-disruptive replacements and upgrades, so even a hardware failure can typically be resolved in seconds.
- QUANTITATIVE BENEFIT
- USE CASES
Autonomous Transport SystemsAutonomous transport systems provide unmanned, autonomous transfer of equipment, baggage, people, information or resources from point-to-point with minimal intervention. They can include the full range of transport vehicles, including trucks, buses, trains, metros, ships, and airplanes. They are most commonly deployed in controlled industries zones but are expected to soon be deployed in public areas with varying degrees of autonomy. We differentiate autonomous transport systems from autonomous vehicles. Whereas autonomous vehicles serve individual passengers (who may or may not own the vehicle), autonomous transport systems are interconnected fleets of vehicles owned by a business to service a particular need systematically. When discussing autonomous transport systems, the focus is on the interaction among vehicles in a sophisticated system that interfaces with ERP, MES, and other enterprise data management systems. The autonomy of the vehicle is one component of a larger interconnected system of autonomous and semi-autonomous activity with the objective of achieving business or organizational objectives, such as delivering the mail or moving soil from a mine to a processing facility.Asset Health Management (AHM)Asset Health Management refers to the process of analyzing the health of an asset as determined by operational requirements. The health of an asset in itself relates to the asset's utility, its need to be replaced, and its need for maintenance. It can be broken down into three key components: 1) Monitoring: Tracking the current operating status of the asset. 2) Diagnostic Analysis: Comparing real-time data to historical data in order to detect anomalies. 3) Prognostic Analysis: Identifying and prioritizing specific actions to maximize the remaining useful life of the asset based on analysis of real-time and historical data.