Analytical Modeling for Underground Risk Assessment in Smart Cities

Abstract

Abstract:In the developed world, underground facilities are increasing day-by-day, as it is considered as an improved utilization of available space in smart cities. Typical facilities include underground railway lines, electricity lines, parking lots, water supply systems, sewerage network, etc. Besides its utility, these facilities also pose serious threats to citizens and property. To preempt accidental loss of precious human lives and properties, a real time monitoring system is highly desirable for conducting risk assessment on continuous basis and timely report any abnormality before its too late. In this paper, we present an analytical formulation to model system behavior for risk analysis and assessment based on various risk contributing factors. Based on proposed analytical model, we have evaluated three approximation techniques for computing final risk index: (a) simple linear approximation based on multiple linear regression analysis; (b) hierarchical fuzzy logic based technique in which related risk factors are combined in a tree like structure; and (c) hybrid approximation approach which is a combination of (a) and (b). Experimental results shows that simple linear approximation fails to accurately estimate final risk index as compared to hierarchical fuzzy logic based system which shows that the latter provides an efficient method for monitoring and forecasting critical issues in the underground facilities and may assist in maintenance efficiency as well. Estimation results based on hybrid approach fails to accurately estimate final risk index. However, hybrid scheme reveals some interesting and detailed information by performing automatic clustering based on location risk index.

An Optimized Fuzzy Logic Control Model Based on a Strategy for the Learning of Membership Functions in an Indoor Environment

“…The centroid of area method was used for defuzzification processes in this work, as shown in Equation (14). The structure diagram of the Mamdani fuzzy logic [30,31] is shown in Figure 5.…”

“…The centroid of area method was used for defuzzification processes in this work, as shown in Equation (14). The structure diagram of the Mamdani fuzzy logic [30,31] is shown in Figure 5. In this work, the tuning of the MFs was carried out in order to get better results when compared to the conventional Mamdani FLC method where the MFs are fixed.…”

A Water Supply Pipeline Risk Analysis Methodology Based on DIY and Hierarchical Fuzzy Inference

“…Hence, to overcome the rules explosion issue, HFIS methods have been used by different authors. Israr et al [34] designed two models to evaluate the underground risk index and rules reduction. Fayaz et al [35] developed a method named simplified HFIS for analyzing the underground risk index.…”

Underground Risk Index Assessment and Prediction Using a Simplified Hierarchical Fuzzy Logic Model and Kalman Filter

“…Hence, cities are becoming more congested and the installation of underground facilities is regularly growing. Consequently, enormous growth in underground facilities is expected in the future due to such relocation of the masses [1]. These facilities consist of underground metro buses, railway lines, parking lots, markets, power supply, water supply, sewerage lines, etc.…”