Calculating Pavement Maintenance Priority Index (PI) Utilizing Artificial Intelligence (Fuzzy Logic) through Mobile Application - Jad Wael AbdulQader Obeid; Eyad Nheed “Mohammad Zahi” Abu Saleh; Samed Azmi Khaled Odeh; Abdulrahman Yaser Abdullatef Hussain; Shima Osamah Fawzi Haj Mohammad (computer); Areej Mohammad Imair (computer) (My University, 2021)
Currently, the Palestinian Municipalities are using the Operation Maintenance Manual (OMM) for prioritizing their pavement maintenance and identifying the sections with the highest priority. The municipality are using the PI equation, which is composed from four indicators: Pavement Condition, Importance of the Road, Peoples Complains, and Functional Classification of the road. The OMM gain the following weights for the above-mentioned indicators 0.75, 0.10, 0.08 and 0.07, respectively. However, through consulting different experts, they declared that these weights could be modified. Moreover, they stated that the 0.75 weight for the PCI is too high. The team decided to take the average between the large acceptable ranges to be set to 50% also as stated in Accordingly, the project team proposed to identify a membership function using Artificial Intelligence and Fuzzy Logic at specific to deal with this issue. The team with the help of Dr. Anas Toma from Computer Engineering Department utilizing MATLAB program to build the membership function to identify the weights of the 4 indicators and developing of rules. The project aims to introduce a better and more accurate way to calculate Pavement Priority Index (PCI) using Artificial Intelligence (AI) with the help of MATLAB program in order to compare model results with the procedure adopted in the OMM. The results indicated that there is a tangible difference between the two values of the PI. However, when comparing the PI resulted from Fuzzy logic and PI from expert’s opinion, the results are close and strong correlation achieved. Based on the results, the team recommend adding more rules to the system in order to improve the results. Moreover, in new indicators in the PI equation will be considered such as Average Daily Traffic, Safety, Maintenance Cost, etc., and re-distribute weights accordingly. Additionally, new ratings to the membership functions such as Extremely High and Extremely Low are added. Finally, the project team will increase the sample size in order to get more confidence results. Image Processing took this project to another level by adding it to a mobile application that is portable and easy to use for the municipality technicians. The mobile application combined imagine processing and the ASTM standards (rules, tables and equation) also including new weights of the PI equation into one application that can be easily used by Nablus Municipality technicians. The app will save time and cost.