Optimize road maintenance planning with AI

HAL24K’s Maintenance Planning Optimizer (MPO) is designed to provide continuous insight in the condition of your road network, and generate optimum short and long-term road treatment plans quickly and automatically. Using AI, the solution can take all relevant road-specific conditions, treatments, rules and constraints into account.

MPO helps clients to optimize planning and minimize the lifetime costs of their road works, while remaining compliant with regulations and contracts.

How does MPO work?

The MPO solution consists of two fully-integrated Dimension modules: Condition Calculator and Maintenance Planner.

Condition Calculator

The Condition Calculator is used to ingest road condition data recorded by automated and visual inspections, and uses this raw data to automatically calculate and visualize the condition of each road in your network.

The module provides secure, transparent and flexible data ingestion; data processing, validation and storage; metric calculations; geospatial enrichment; and associated auditable reporting in Dimension or third-party systems. It can be customized to your requirements, standards and processes, helping you to meet contractual commitments and understand how well your overall road network is performing, including under simulated conditions.

Maintenance Planner

The Maintenance Planner combines the road condition metrics generated by the Condition Calculator with other data sources, as input for an AI model to generate an optimized road treatment plan for your road network.

To find the optimum combination of treatment types and dates for each road, the model will consider relevant input, including:

• current road conditions

• available road treatments and their associated costs and estimated lifetime

• completed treatments

• minimum allowed conditions

• customer-specific rules and constraints to keep costs within a maximum budget and maintain the roads to set standards, over the life of the contract.

Its intuitive user interface allows users to set the relevant parameters and run the model. Progress of the Maintenance Planner can be monitored with a graph showing the reduction in lifetime costs, as the model continues to run. The input data can easily be updated at any stage and used to generate new plans.

All output of the Maintenance Planner is securely stored and made available for third-party business systems to query and analyze the results in further detail.

With MPO, organizations can now improve on their understanding and reporting of the condition of their road network, and determine the most cost and resource-efficient ways to keep it in check with contractual standards and commitments.