Optimizing DOT Asset Management: From Field Data to Actionable Insights

Abstract

Departments of Transportation (DOTs) and Municipalities are under growing pressure to manage large, aging, and complex transportation networks. From drainage systems to guardrails, signs, lane markings, and roadway conditions, effective asset management requires a data-driven, fieldinformed approach. This paper will outline a comprehensive methodology that supports the full asset lifecycle, from initial inspections to rehabilitation project execution, using advanced data collection, geospatial analytics, AI, and interactive dashboards. The process begins with data collection/field inspections using tablets and GIS software to geolocate and assess drainage infrastructure. For other roadway-visible assets, car-mounted cameras paired with AI-driven image recognition enable automated, scalable identification and condition assessment of signs, guardrails, lane markings, and pavement condition, greatly improving coverage and efficiency. Collected data is processed through proprietary and ESRI-based software to generate prioritized recommendations for follow-up inspections, maintenance, and rehabilitation. Where detailed evaluations are needed, advanced technologies such as inSight Lite™ and inSight BCT™ are deployed. Recommendations are then delivered through interactive, client-specific dashboards that help DOTs visualize asset conditions, develop capital expenditure plans, and monitor execution progress. Beyond reporting, these dashboards provide actionable planning tools, KPI tracking, and transparency for construction and maintenance activities. Deep involvement in inspection and project delivery ensures recommendations are grounded in real-world conditions and constraints. Through case studies and practical examples, this paper will demonstrate how integrated technology, analytics, and field expertise can help DOTs and Municipalities enhance asset reliability, streamline operations, and reduce lifecycle costs.