Bengaluru’s Namma Metro to make use of AI-driven drones to detect damages on pillars and viaducts: Report

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Bengaluru will quickly deploy drones to boost the security monitoring of concrete metro pillars and viaducts alongside metro tracks, in keeping with a report by Cash Management. These drones, outfitted with Synthetic Intelligence (AI) instruments, will seize visuals to detect cracks and structural damages.

The AI expertise won’t solely detect defects on tracks but in addition analyze their potential influence and inform BMRCL’s engineering staff. (X/@bykarthikreddy)

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Sumit Bhatnagar, Director of Operations and Upkeep at Bangalore Metro Rail Company Restricted (BMRCL) informed publication, “Namma Metro plans to invite bids for AI-drone inspections of Reach 1 (MG Road – Byappanahalli), the city’s first operational metro corridor launched in 2011. AI-driven systems will assess the extent of any structural damage and provide alerts, enabling engineers to implement timely maintenance measures.”

The way it works?

The AI expertise won’t solely detect defects but in addition analyze their potential influence and inform BMRCL’s engineering staff. “The AI-powered evaluations will determine whether the identified issues pose significant risks and suggest appropriate solutions, such as epoxy sealing or other necessary repairs,” he added additional.

This technological improve is anticipated to decrease operational prices and enhance the productiveness of BMRCL’s engineering division. Presently, structural inspections depend on handbook strategies involving binoculars, cameras, and hydraulic platforms. Introducing drones and AI will decrease handbook labor, improve precision, and expedite infrastructure assessments.

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Bengaluru’s visitors police have already built-in drone expertise to handle visitors circulate within the metropolis. Drones have been stationed at traffic-heavy areas like Hebbal, Central Silk Board, Ibballur, Marathahalli, KR Puram, Guruguntapalya, Sarakki, and Banshankari bus stand to watch congestion, notably throughout peak hours.