Over the last few years, a plethora of public works have taken place, focusing towards urban renewal, in the greater Thessaloniki district. Municipality of Thessaloniki, provided data for twelve public projects of urban renewal. Mathematical models have been proposed for cost and time prediction based on regression analysis. Furthermore, the Fast Artificial Neural Network (FANN Tool) was applied, to predict the duration and the final cost of the project, using volume of earthwork, as input variable. Both approaches could facilitate project stakeholders, to forecast the projects' final delivery date and cost and provide early warnings for any deviation from the initial budget. The results indicate that neural networks perform better than regression analysis' models, in the case of urban renewal projects.

Over the last few years, a plethora of public works have taken place, focusing towards urban renewal, in the greater Thessaloniki district. Municipality of Thessaloniki, provided data for twelve public projects of urban renewal. Mathematical models have been proposed for cost and time prediction based on regression analysis. Furthermore, the Fast Artificial Neural Network (FANN Tool) was applied, to predict the duration and the final cost of the project, using volume of earthwork, as input variable. Both approaches could facilitate project stakeholders, to forecast the projects' final delivery date and cost and provide early warnings for any deviation from the initial budget. The results indicate that neural networks perform better than regression analysis' models, in the case of urban renewal projects.

Visual inspection is the most commonly employed way of condition inspection for road networks. The process is quite labor intensive, leading to a substantive cost of inspection per lane mile and causing long inspection cycles and substantive inspection outcomes variability. Automating the process can tackle these issues. The first step to achieve automation is to understand what the assets are, what their visible condition symptoms are, what they cause and what causes them, and how to fix both their outcomes and their causes. This is the objective of this paper. Inspired by the symptoms tracker of WebMD, we conducted exploratory research that combined several guidelines into a comprehensive definition of road assets, their defects and possible maintenance techniques from the road inspector's point of view. We propose a different classification system of the road assets according to their defects and maintenance techniques driven by the computer visual monitoring approach. The result is a large map containing all the aforementioned elements.