AI road condition monitoring on the 2-lane approach road to the Munger rail-cum-road bridge inspection in Bihar, built in EPC mode

This is a project-level account from RoadVision AI's road survey programme for NHAI, covering the Construction of Approach Road to the Rail-cum-Road Bridge inspection across the River Ganga at Munger Ghat (NH-333B) in Bihar. It sets out what the survey of 24 July 2026 found, and why the approach road to a major bridge is exactly where an independent condition record earns its keep.

1. A Highway Approach to a Landmark Bridge

NH-333B in Bihar carries the approach road to the rail-cum-road bridge across the River Ganga at Munger Ghat. As publicly described, the project provides 14.52 km of road approaches, built to 2-lane national highway standard under Regular Civil Works in EPC mode. The survey record carries 18.02 km of road, divided into 181 segments at a 100 m chainage interval.

In the survey programme the road is tracked under project code, as the single road in Weekly-Cycle-5, and was surveyed in its third survey cycle. Because every finding is tied to a chainage, the road can be read stretch by stretch rather than as a single average.

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2. Why a Large Project Needs an Independent Record

As publicly reported, the work was awarded at ₹239.16 crore, within a project whose original capital cost of ₹538 crore has been revised to ₹634 crore, with about ₹574 crore spent to date. On a project of this size and visibility, the approach road decides how the bridge works for the people using it every day. That makes it hard to tell, from a desk or an occasional visit, whether what has been built is holding up. A consistent, chainage-tied record answers that: it shows what is wrong, how urgent it is, and whether it has been put right by the next survey.

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3. The Highway on the Map

Every finding sits on a live GIS map, with each inspection point opening to its exact location, the defect flagged, and the frame behind it in both original and AI-annotated form. Figure 1 shows the route on the map around Munger and the Ganga for the survey of 24 July 2026, with an inspection point captured at midday, at about 12:47 pm, flagging shoulder vegetation growth, faded pavement marking and a pothole in a single frame, with a guard rail beside the carriageway. A frame like this is a reminder that the survey records conditions as road users meet them.

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4. What the Survey Found

The Survey 3 record for 24 July 2026 covered 18.02 km across 181 segments. RoadVision AI logged 214 defects across 9 defect types. Shoulder vegetation growth accounts for 64 (29.9%), faded pavement marking for 63 (29.4%), potholes for 51 (23.8%), damaged metal beam crash barrier (MBCB) for 11 (5.1%) and faded painting on concrete crash barriers for 10 (4.7%), with cracking, unauthorized hoardings, damaged kerb and rutting making up the remaining 15 (7.0%). By severity, 128 are High (59.8%), 22 Medium (10.3%) and 64 Low (29.9%).

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5. From Findings to Action

Each survey gives the responsible Regional Office and PIU a defect ID, chainage and survey reference for every finding, independent of the agency doing the work. A later survey of the same chainage then shows whether the finding has been closed out, so that verification does not rest on the contractor's own account.

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Our Commitment

RoadVision AI is committed to continuous AI road condition monitoring along the NH-333B approach road to the Munger rail-cum-road bridge, giving NHAI a consistent, chainage-level record of the road that connects people to a landmark crossing of the Ganga. Keeping that record current, survey after survey, is how a large project can be shown to be holding up.

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