Preserving roads involves regularly evaluating government policy through advanced assessments using vehicles with specialized capabilities and high-resolution scanning technology. However, the cost is often not affordable due to a limited budget. Road surface surveys are highly expected to use low-cost tools and methods capable of being carried out comprehensively. This research aims to create a road damage detection application system by identifying and qualifying precisely the type of damage that occurs using a single CNN to detect objects in real time. Especially for the type of pothole, further analysis is to measure the volume or dimensions of the hole with a LiDAR smartphone. The study area is 38 province’s representative area in Indonesia. This research resulted in the iRodd (intelligent-road damage detection) for detection and classification per type of road damage in real-time object detection. Especially for the type of pothole damage, further analysis is carried out to obtain a damage volume calculation model and 3D visualization. The resulting iRodd model contributes in terms of completion (analyzing the parameters needed to be related to the road damage detection process), accuracy (precision), reliability (the level of reliability has high precision and is still within the limits of cost-effective), correct prediction (four-fifths of all positive objects that should be identified), efficient (object detection models strike a good balance between being able to recognize objects with high precision and being able to capture most objects that would otherwise be detected-high sensitivity), meanwhile, in the calculation of pothole volume, where the precision level is established according to the volume error value, comparing the derived data to the reference data with an average error of 5.35% with an RMSE value of 6.47 mm. The advanced iRodd model with LiDAR smartphone devices can present visualization and precision in efficiently calculating the volume of asphalt damage (potholes).

The effective allocation of resources within police patrol departments is crucial for maintaining public safety and operational efficiency. Traditional methods often fail to account for uncertainties and variabilities in police operations, such as fluctuating crime rates and dynamic response requirements. This study introduces a fuzzy multi-state network (FMSN) model to evaluate the reliability of resource allocation in police patrol departments. The model captures the complexities and uncertainties of patrol operations using fuzzy logic, providing a nuanced assessment of system reliability. Virtual data were generated to simulate various patrol scenarios. The model’s performance was analyzed under different configurations and parameter settings. Results show that resource sharing and redundancy significantly enhance system reliability. Sensitivity analysis highlights critical factors affecting reliability, offering valuable insights for optimizing resource management strategies in police organizations. This research provides a robust framework for improving the effectiveness and efficiency of police patrol operations under conditions of uncertainty.

The study sheds light on how service quality aspects affect customer satisfaction in the Saudi banking sector’s particular socio-cultural setting. Thus, the study examines the role of service quality dimensions on customer satisfaction in the banking industry of Saudi Arabia. The study examined how reliability, assurance, empathy, tangibility, and responsiveness affect customer satisfaction in the Saudi Arabian banking market using 250 bank clients. 250 Saudi bank customers completed a standardised questionnaire. These were normal bank customers with proper bank accounts. IBM SPSS correlational and multiple regression analysis investigated variable connections. The study found a significant favourable influence of reliability on customer satisfaction. However, assurance was not significant. Empathy had a significant impact on customer satisfaction. Tangibility shown a significant impact on customer satisfaction. Responsiveness was not significant. The study emphasises on reliability, empathy, and physical service delivery to boost banking customer happiness. The study found 3 of 5 service quality factors to be significant predictors. Service empathy, tangibility, and reliability greatly impacted customer satisfaction. Managers in Saudi banking should prioritize reliability, empathy, and tangibility to boost customer satisfaction. To keep customers happy, managers should monitor these service quality dimensions and adjust strategies based on feedback. Technology can improve service quality by streamlining processes and personalizing experiences.