DbM4SBM - Drive-by Monitoring for Sustainable Bridge Management

Bridges are vital to how cities function, yet many are ageing while maintenance resources remain limited. In the DbM-Luleå project, a new approach is being tested where sensors mounted on buses and service vehicles collect data during everyday traffic to monitor bridge conditions more continuously. Using Luleå as a real-world testbed, the project aims to enable earlier detection of damage and support smarter, more sustainable bridge management.

Background

Bridges are essential to how cities function, but many bridge stocks are ageing while maintenance resources remain limited. Current bridge management still relies heavily on inspections carried out at long intervals, which means deterioration can develop between inspection cycles. DbM-Luleå addresses this gap by testing a more continuous approach in which sensors mounted on buses and service vehicles record bridge-response data during normal operation. The project uses Luleå as a real-world demonstration environment, where repeated vehicle routes and demanding seasonal conditions provide a relevant testbed.

Aim & Objectives

The aim of DbM-Luleå is to develop and demonstrate a scalable system for continuous bridge condition monitoring using data collected from public buses and service vehicles in normal operation. The project will test the method in a real municipal setting in Luleå and evaluate how drive-by monitoring can support more continuous and data-driven bridge management.

The objectives are to equip selected vehicles with sensors, validate the measurements against reference-instrumented bridges, develop a processing pipeline that converts raw vibration data into bridge-condition indicators, and present the results through a municipal dashboard that supports interpretation and maintenance planning.

Scientific approach

Selected buses and service vehicles will be equipped with accelerometers and GPS units, while selected bridges will also receive reference sensors for validation. The recorded data will be processed through a structured analysis pipeline that includes cleaning, synchronization, feature extraction, comparison with bridge-mounted sensors, and interpretation of bridge-condition indicators. The project is organised around system deployment, data analysis, dashboard development, evaluation, and scaling.

Societal relevance & open science

The project aims to support earlier detection of structural change, better maintenance planning, and more efficient use of public resources. By improving maintenance timing, it may help extend service life, reduce unnecessary interventions, and lower environmental impact. Although the pilot is based in Luleå, the intention is to develop methods, workflows, and tools that can be transferred to other municipalities in Sweden and beyond.