Around the world, artificial intelligence (AI) technology is becoming increasingly prevalent in public sector activities. By expanding services, enhancing efficiency, and adopting cost-saving innovations, artificial intelligence (AI) technology can completely change how government operations are deployed.
AI can improve railway efficiency by identifying maintenance-required train segments in real-time online and minimising service interruptions, which is advantageous for both users and the subway system.
The Brazil Railway AI Market accounted for $XX Billion in 2021 and is anticipated to reach $XX Billion by 2030 registering a CAGR of XX% from 2024 to 2030.
The railway company of So Paulo, CPTM, wants to increase the productivity and efficiency of its operations by integrating big data, AI, and IoT into its ICT systems.
This is the major objective of an ICT call that a Brazilian company has opened and directed towards US businesses. The winner of the call will be in charge of conducting a feasibility study for the integration and upgrading of CPTM’s ICT systems.
The chosen company will create a roadmap including solutions, specifications for the architecture and infrastructure, standards, and a step-by-step process that outlines the steps required for CPTM to execute the suggestions as part of the requirements.
In addition to forecasting breakdowns and delays in transportation, studying traffic patterns, and improving passenger flow, among other things, the new technologies are considered as essential to lowering traffic congestion, power costs, and greenhouse gas emissions.
The largest health facility in Brazil and So Paulo’s subway system participated in a pilot programme run by the World Economic Forum (WEF) that resulted in a number of suggestions for the ethical use and procurement of artificial intelligence (AI) in the public sector.
The Metrô sought to acquire a predictive maintenance system driven by AI for online, real-time tracking of rail tracks throughout the subway system.
In order to support decisions made by Metrô’s engineering team to reduce delays, which are mostly caused by maintenance, it would integrate cameras on trains and sensors to enable deep learning and automated picture processing.
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