# Analytical Modeling for Underground Risk Assessment in Smart Cities
## 2 Related Work  
Despite care and precautions, many severe and unfortunate incidents have happened in underground facilities around the globe. Investigation reveals that the major causes of incidents include natural disasters, technical faults, human mistakes and underground leakage and soil deformation. Improved structural design and strict adherence to standard operational procedures can help in building safer and disaster resilient communities. Designing for disaster is a platform for engineers, designers, planners, environmentalists and others to share their experiences by showcasing their innovative research findings [3]. Here, we try to address and design solutions for silent risk factors that pose constant and serious threats, e.g., continuous leakage of water and sewerage supply lines, structure fault and underground soil deformation. Contrary to natural disasters, in such cases, the damage does not happen at once, rather the hazard builds up slowly and gradually behind the seen as many underground facilities are invisible and least accessible. To avoid any accidental loss, a sensor based real time monitoring system is highly desirable to conduct automated and continuous risk assessment to report any abnormality before happening. Many research contributions are made to build a safe and risk free environment with particular emphasis on risk assessment of underground facilities. [PERSON] et al. [4] presents a generic risk assessment model for data acquisition and surveillance of underground facilities. Data collected from diverse sources/sensors are forwarded through gateways to main application server for detailed analysis. However, they did not evaluate the model with any simulated or real data. [PERSON] et al. proposed a four-step methodology for risk assessment in underground construction projects, i.e., identifying, analyzing, evaluating and managing the risk [5]. They developed a fuzzy inference based solution to perform risk assessment of a subway construction project in Korea. A similar system was deployed for underground risk assessment and analysis during expansion of Incheon Airport, South Korea [6]. The objective was to carry out intensive ground investigation to ensure safety while constructing a subway under an operational runway. Likewise, case studies are conducted highlighting the significance and utility of underground risk assessment [7; 8]. [PERSON] et al. developed a system for data collection in underground construction works to ensure safety while tunnel boring either through tunnel boring machine (TBM) or traditional methods [9]. During Warsaw (capital of Poland) Metro construction project, comprehensive risk assessment was done by collecting data from 7993 sites using 11 different devices to evaluate land and water conditions [10]. Continuous monitoring was performed by central station by receiving the data for analysis from selected sites and alerts were generated to control the process upon detecting of any abnormality. The key difference between these systems and approach is that they focus on ongoing construction projects, whereas our objective is monitoring of underground facilities. To perform automated and continuous monitoring on underground facilities, different types of sensors are required. With advancement in sensing technology, a variety of sensors is available to collect data about different kind of underground hazardous situation. Early detection following by necessary correction measures can avoid potential damage and save human lives. State of the art technologies for inspection of water pipes is presented in [11]. Assessment methods can be categorized into direct and indirect. Direct method includes visual inspection, e.g., cameras, CCTV, Laser scanning, electromagnetic radiation based devices, acoustic method, etc. SmartBall comprises several sensors including acoustic, accelerometer, GPS and temperature sensors [12]. It is shaped like a ball which makes it easy to travel through water pipes to detect, locate and estimate leakage in pipes while rolling.