An Economy in Motion Is Fueled by Transportation
Transportation is critical to the global economy. Commercial vehicles, buses, cars, planes, ships, and railways help us physically connect with each other and trade goods. Today, transportation systems are struggling to keep pace with the demands of our global, connected economy. The import and export of goods make up about three-quarters of the world gross domestic product.1 In addition, the demand for urban mobility—whether by personal or public transportation—is expected to grow 2.6 times by 2050.2
What Are Intelligent Transportation Systems (ITS)?
The Internet of Things (IoT) and artificial intelligence (AI) are enabling a new class of intelligent transportation systems (ITS) for road, air, rail, and sea. These solutions connect vehicles, traffic signals, toll booths, and other infrastructure to help ease congestion, prevent accidents, reduce emissions, and make transportation more efficient. Examples include fleet management, intelligent traffic management, V2X communication, electric vehicle charging, electronic toll collection, and a wide range of other mobility solutions.
Edge Computing Enables Near Real-Time AI and Analytics
Today, many transportation providers rely on disaggregated data platforms and independent point solutions. Intel is partnering with our partner ecosystem to support new models for intelligent, connected transportation. From the edge to the cloud, Intel helps transportation providers turn data into insights, achieving fast, efficient, and informed use of transportation systems.
At the edge, Intel® technologies enable AI and analytics in near-real time, helping support public safety or manage traffic flow. With edge computing and inference, you can benefit from fast response times, free up bandwidth, and help keep sensitive data private.
How Can Data Fuel Intelligent Transportation from Edge to Cloud?
The most valuable intelligent transportation systems work both at the edge, delivering actionable insights in near-real time, and in the cloud, revealing trends over the long term.
Placing compute at the edge is especially valuable when running AI on data from multiple sensors—for example, for smart traffic lights or e-tolling stations. Solutions based on Intel® platforms deliver high performance at the edge and make it possible to consolidate applications while leaving enough headroom for new functionalities. As a result, smart cities and transportation providers can reduce infrastructure costs, simplify integration and management, scale faster, and ensure their technology investments last longer.
Sharing data selectively with the cloud supports long-term analytics. For example, city planners can optimize traffic flow and parking to help reduce greenhouse gas emissions or identify problem areas where collisions or near-misses frequently occur. Intel provides a foundation of technologies to support cloud services, whether via public, private, or hybrid cloud.
Product and Performance Information
Trade (% of GDP), World Bank, https://data.worldbank.org/indicator/NE.TRD.GNFS.ZS.
“Future of Urban Mobility 2.0,” Arthur D. Little & UITP, January 2014, adlittle.com/futuremobilitylab/assets/file/131216_Arthur_D.Little_&_UITP_Future_of_Urban_Mobility_2_0_4-pagers.pdf.
GRIDSMART case study: Bangkok, Thailand, gridsmart.com/the-gridsmart-system-case-study-in-thailand/.