**Haibat Ali and Jae-ho Choi \***

Civil Engineering, Dong-A University, Busan, P4401-1, 550 Bungil 37, Nakdong-Dero, Saha-Gu 49315, Korea **\*** Correspondence: jaehochoi@dau.ac.kr; Tel.: +82-51-200-762

Received: 9 July 2019; Accepted: 21 July 2019; Published: 24 July 2019

**Abstract:** Major metropolitan cities worldwide have extensively invested to secure utilities and build state-of-the-art infrastructure related to underground fluid transportation. Sewer and water pipelines make our lives extremely convenient when they function appropriately. However, leakages in underground pipe mains causes sinkholes and drinking-water scarcity. Sinkholes are the complex problems stemming from the interaction of leaked water and ground. The aim of this work is to review the existing methods for monitoring leakage in underground pipelines, the sinkholes caused by these leakages, and the viability of wireless sensor networking (WSN) for monitoring leakages and sinkholes. Herein, the authors have discussed the methods based on different objectives and their applicability via various approaches—(1) patent analysis; (2) web-of-science analysis; (3) WSN-based pipeline leakage and sinkhole monitoring. The study shows that the research on sinkholes due to leakages in sewer and water pipelines by using WSN is still in a premature stage and needs extensive investigation and research contributions. Additionally, the authors have suggested prospects for future research by comparing, analyzing, and classifying the reviewed methods. This study advocates collocating WSN, Internet of things, and artificial intelligence with pipeline monitoring methods to resolve the issues of the sinkhole occurrence.

**Keywords:** WSN; pipeline leakage; human-induced sinkhole; leakage detection; sewer pipeline; sensors

### **1. Introduction**

Sewer and water leakages in underground pipelines have become a critical issue for water-management authorities in most countries—developed and developing alike—worldwide. Leakages in sewer and water pipelines may lead to several problems such as a shortage of drinking water, groundwater contamination, and ground subsidence [1]. Numerous countries are investing a considerable amount of their annual budget towards the prevention and control of the probable effects of sewer and water pipeline leakage. These issues further exacerbate infrastructure and environmental conditions that support human socioeconomic activities. In recent years, developed countries, such as the United Kingdom, Australia, France, Spain, and the United States of America, have experienced shortage in domestic water supply because of leaking pipe mains [2]. The after effects of these leakages in pipelines cause ground subsidence and sinkholes [3]. These sinkholes result in damage to infrastructure (roads, highways, railways, and underground fluid transportation networks).

A sinkhole refers to a cavity in the ground formed by underground erosion and the depression of the ground surface. In general, there exist two types of sinkholes—natural and human induced. Natural sinkholes are mainly observed in regions with large deposits of salt, limestone, and carbonate rocks. The accurate prediction of the location and time of the occurrence of these sinkholes is rather difficult [4]. Groundwater extraction, construction in adjoining areas, and leakage in underground

pipelines are the leading causes of human-induced sinkhole formation in urban areas [5]. Among them, the presence of leakages, bursts, or blockages in sewer, drain, and/or water pipelines are the most frequently reported causes of sinkholes. *Sustainability* **2019**, *11*, x FOR PEER REVIEW 2 of 25 Natural sinkholes are mainly observed in regions with large deposits of salt, limestone, and carbonate rocks. The accurate prediction of the location and time of the occurrence of these sinkholes is rather

The issue of sinkhole creation has witnessed global escalation in recent years owing to ever-increasing urbanization and the continuous construction, development, and expansion of urban areas [6]. A cavity begins to develop as leaked water erodes the soil surrounding pipelines. This reduces the bearing capacity of the soil layer above the cavity, and hence, the ground collapses to form a sinkhole [7]. The size of sinkholes ranges from 2 m deep and 1.5 m wide [5] to a massive scale of up to 15 m deep and 30 m wide [8], as reported in Jeju, South Korea and Southwest Japan, respectively. Human-induced sinkholes have been reported in San Antonio, Texas [9]; Oakwood, Georgia; and Tracer, Colorado [10]. These incidences have reportedly caused considerable economic damage and loss of human lives. As reported in Fraser, USA [10], the abrupt collapse of a 44-year-old sewer pipeline destroyed 22 homes, and the reconstruction of the damaged road and sewer pipelines cost the city administration approximately \$70 million. More than 20 sinkholes have been observed in USA alone owing to the failure of underground pipe mains [11]. Figure 1 illustrates the effects of underground pipeline leakage. difficult [4]. Groundwater extraction, construction in adjoining areas, and leakage in underground pipelines are the leading causes of human-induced sinkhole formation in urban areas [5]. Among them, the presence of leakages, bursts, or blockages in sewer, drain, and/or water pipelines are the most frequently reported causes of sinkholes. The issue of sinkhole creation has witnessed global escalation in recent years owing to everincreasing urbanization and the continuous construction, development, and expansion of urban areas [6]. A cavity begins to develop as leaked water erodes the soil surrounding pipelines. This reduces the bearing capacity of the soil layer above the cavity, and hence, the ground collapses to form a sinkhole [7]. The size of sinkholes ranges from 2 m deep and 1.5 m wide [5] to a massive scale of up to 15 m deep and 30 m wide [8], as reported in Jeju, South Korea and Southwest Japan, respectively. Human-induced sinkholes have been reported in San Antonio, Texas [9]; Oakwood, Georgia; and Tracer, Colorado [10]. These incidences have reportedly caused considerable economic damage and loss of human lives. As reported in Fraser, USA [10], the abrupt collapse of a 44-year-old sewer pipeline destroyed 22 homes, and the reconstruction of the damaged road and sewer pipelines cost the city administration approximately \$70 million. More than 20 sinkholes have been observed in USA alone owing to the failure of underground pipe mains [11]. Figure 1 illustrates the effects of underground pipeline leakage.

**Figure 1.** Causes and effects of leakage in underground water systems and sewer pipeline systems. **Figure 1.** Causes and effects of leakage in underground water systems and sewer pipeline systems.

Various hardware, software, mathematical formulas, and algorithm-based methods have been proposed for monitoring, detecting, and preventing leakages in underground water pipelines and the occurrence of sinkholes. Conventional techniques, such as acoustic-based approaches, have been used for this purpose. These techniques require an expert who scans a suspected area by listening to leak sounds. However, such methods are extremely time consuming and their accuracy highly depends on the skills and experience of personnel [12]. Vibration analysis is another conventional technique utilized to locate leaks in pipelines [13]. However, in conventional vibration and acousticbased techniques, hydrophones must be placed on both sides of the pipeline section under consideration for leak detection. Such conventional techniques require the exact length of the pipeline to accurately locate a leak. In such cases, the length of the pipeline is measured either by walking with a measurement wheel or by utilizing the recorded data from maps [14]. The lengths obtained using these methods are inappropriate for locating or detecting a leak and result in errors of up to Various hardware, software, mathematical formulas, and algorithm-based methods have been proposed for monitoring, detecting, and preventing leakages in underground water pipelines and the occurrence of sinkholes. Conventional techniques, such as acoustic-based approaches, have been used for this purpose. These techniques require an expert who scans a suspected area by listening to leak sounds. However, such methods are extremely time consuming and their accuracy highly depends on the skills and experience of personnel [12]. Vibration analysis is another conventional technique utilized to locate leaks in pipelines [13]. However, in conventional vibration and acoustic-based techniques, hydrophones must be placed on both sides of the pipeline section under consideration for leak detection. Such conventional techniques require the exact length of the pipeline to accurately locate a leak. In such cases, the length of the pipeline is measured either by walking with a measurement wheel or by utilizing the recorded data from maps [14]. The lengths obtained using these methods are inappropriate for locating or detecting a leak and result in errors of up to 30% [15]. Various methods have been adopted to monitor and detect sinkholes. Over the years, wireless sensor networking (WSN) systems [16], Internet of things (IoT) [3], and image processing technology using artificial intelligence (AI) have been used for monitoring underground pipeline infrastructures [17]. WSN was first used for pipeline leakage monitoring and detection in 2004 [18]. However, most methods related to WSN, IoT, and image processing mainly focus on sewer and water pipeline monitoring to detect any defects

(including leakage) in a more efficient manner in the context of solving the drinking water shortage problem. The after effects (sinkholes) of leakages in sewer and water pipelines have not been discussed and must be examined.

Sinkholes are the most complex civil engineering problems stemming from the interaction of water and the ground. The sinkholes induced by leaking underground pipelines are an important problem that must be extensively investigated. The authors of this paper highlight the major technology-based approaches to obtain a better understanding of the current trends in leakages in underground water and sewer pipelines and their after effects (such as sinkholes). This work aims to find an opportunity for extending existing smart technologies, such as WSN, IoT, and AI, to monitor and detect any signs of sinkholes due to leakages in underground water or sewer pipelines.

The authors aim to demonstrate the exceptional performance of WSN and its application to the detection of sinkholes and to find a suitable solution to optimize the leakage process. Human-induced sinkholes due to leakages in underground pipelines are examined in detail, and the main challenges, issues, and future research areas are elucidated. Furthermore, the authors highlight the WSN-based approaches used to resolve the issue of sinkhole occurrence. The use of smart technology can ensure the future success of underground construction infrastructure industries and create new and clear business objectives. It is important to emphasize that the focus of this study is only on sewer and water pipeline leakages and their after effects.

### **2. Review Method**

#### *2.1. Scope and Objective*

This review article concentrated on leakages in sewer and water pipelines and their after effects. It focused on the status of the methods related to the use of WSN to address problems of leakage, burst, and/or blockage monitoring in underground sewer and water pipelines along with the monitoring of the sinkholes caused by these phenomena. The analysis of these methods can provide direction for future research in this area to reduce the occurrence of sinkholes due to leakages. The objective of this review was to provide a comprehensive overview of the state-of-the-art development in leakage and human-induced sinkhole detection and WSN-based monitoring methods.

#### *2.2. Review Execution*

This study applied two approaches to comprehensively review the damage caused by sinkholes and leakages in underground water and sewer pipe mains—patent analysis and extensive literature review.

Patent analysis—the patents filed by organizations in different regions worldwide were analyzed using relevant keywords to examine related trends concerning underground sewer and water pipeline leakages and sinkhole creation over the past 18 years. Relevant national and international bodies—Google Patent, United States Patent and Trademark Office, Korean Intellectual Property Rights Information Service (KIRIS), State Intellectual Property Office of the P.R.C, and so on—served as the sources for the patents mentioned in this section, as described in Table 1. Section 3 provides a detailed explanation of this approach.

Literature review—this includes journal articles and conference papers published in regard to the monitoring and detection of leakages in underground water and sewer pipelines and the sinkholes caused by these leakages using WSN systems. Different research article search databases, such as Science Direct, Web of Sciences, and Engineering Village, were used for finding relevant literature published over the past 18 years (2000 to 2018). The reason for reviewing the literature in between 2000 to 2018 was that WSN was first applied to leakage monitoring in 2004 [18]. Section 4 provides a detailed description of WSN-based and IoT-based sewer and water pipeline leakage and sinkhole monitoring and detection methods. Detailed web-of-science analysis was performed to provide statistical data on the reviewed literature. The aforementioned information was collected using keywords such as pipeline leakage, sinkhole, subsidence, sensors, and wireless sensor network.


**Table 1.** Results of patent search pertaining to sinkhole detection and underground pipeline leakage monitoring.

### **3. Patent Analysis**

Patent analysis is a unique management tool that deals with a company's technology and strategic management of a product development or service development process [19]. By converting patent data into competitive intelligence, companies can monitor current technological advancements, predict technology trends, and plan for potential competition based on new technologies. This section discusses the patents closely related to the development of leakage detection techniques in underground sewer and water pipelines to prevent potential adverse effects such as drinking water shortage and sinkhole formation.

In this regard, the authors first performed a preliminary search using several keywords related to sinkhole detection and its primary cause—water leakage in sewer pipelines—by utilizing Espacenet Patent Search, which is mainly used in European countries. The authors rapidly realized that different patent-search databases must be used because of the limited number of patents published in this domain. To select patents most relevant to the subject of concern in this study, 10 patent search engines, including official websites, were accessed, as described in Table 1. The database search yielded 431 patents. Approximately 10% (43) of these patents were related to underground pipeline monitoring and leakage detection using WSN, whereas only 4% (19) were related to sinkhole monitoring and detection using WSN.

Table 2 describes the scope of the patents listed in Table 1 in terms of academic and industrial relevance with regard to investigations concerning underground pipeline leakage monitoring and sinkhole formation during 2000 to 2018. Relevant patents have been classified based on the leakage monitoring/detection of underground sewer and water pipelines and sinkhole formation. Out of 43 patents, only 16 patents for pipeline leakage monitoring are cited in Table 2, which are the most relevant to the subject of concern in this study, and 19 patents relevant to sinkhole occurrence are cited. Table 2 further classifies the patents based on whether they belong to the class of safety equipment or method, robotic devices or sensors, or experimental setup or method. As shown in Table 2, until 2010, there were no patents on the implementation of WSN and IoT. However, the application of WSN and IoT has increased over the past two decades. There have been no significant technical advancements in the development of equipment or devices to ensure safety against pipe bursts and sinkhole formation.

Among the patents (16 leakage monitoring and 19 sinkhole detection or monitoring patents) shown in Table 2, the patents most relevant to the subject of concern (patents that used WSN) were selected for further study. Among these filtered patents, six were related to natural sinkhole and water pipeline monitoring and leakage detection methods, while only a single patent was related to human-induced sinkhole detection or monitoring using WSN [39]. The remaining patents mentioned in Table 2 are relevant to leakage monitoring and sinkhole monitoring. However, they do not use a WSN system. The authors created Figure 2 in order to illustrate the concept of different patented methods, which used a WSN system.

formation.

**Patent Subject** 

**Leakage monitoring**

**Sinkhole detection** 

**Table 2.** Patents published concerning underground water and sewer pipeline leakage and sinkhole formation.

**Years** 2000 2010 2013 2014 2015 2016 2017 2018

Among the patents (16 leakage monitoring and 19 sinkhole detection or monitoring patents)

*Sustainability* **2019**, *11*, x FOR PEER REVIEW 5 of 25

no patents on the implementation of WSN and IoT. However, the application of WSN and IoT has increased over the past two decades. There have been no significant technical advancements in the development of equipment or devices to ensure safety against pipe bursts and sinkhole formation.

**Table 2.** Patents published concerning underground water and sewer pipeline leakage and sinkhole

method - - [20] - - - - [21,22]

or methods - - - - [32] - [33] [34,35]

method - - - [36] [37] - - -

or methods - - - - [20,47,48] [49] [50,51] [52,53]

(robots/sensors) - - - - [38–40] [41] [42–45] [46]

(robots/sensors) - - - [23,24] [25,26] [27,28] [29–31] -

**Classification Subcategories References and Years of Patent Publication**

Safety equipment or

Devices

Experimental setup

Safety equipment or

Devices

Experimental setup

**Figure 2.** Visual representation of underground water pipeline leakage and sinkhole monitoring methods based on wireless sensor networking (WSN) systems; (**a**) sinkhole detector; (**b**) ultrasonic medium change detection; (**c**) remote pipeline inspection method and mobile-type monitoring device for pipelines; (**d**) pipeline safety and monitoring device; (**e**) sinkhole monitoring system based on pressure sensors; (**f**) simulated sinkhole to develop a neural network learning database for sinkhole detection. **Figure 2.** Visual representation of underground water pipeline leakage and sinkhole monitoring methods based on wireless sensor networking (WSN) systems; (**a**) sinkhole detector; (**b**) ultrasonic medium change detection; (**c**) remote pipeline inspection method and mobile-type monitoring device for pipelines; (**d**) pipeline safety and monitoring device; (**e**) sinkhole monitoring system based on pressure sensors; (**f**) simulated sinkhole to develop a neural network learning database for sinkhole detection.

just considered patents with applications of WSN. As reported in relevant patents, a device for detecting underground sinkhole formation is partially buried in the ground. A typical sinkhole detector comprises of a cable, a control circuit, and a weight, as depicted in Figure 2a. If a sinkhole is created in the vicinity of the device diameter or under the detector, the device releases the attached weight. This activates a circuit that sends a notification to an administration center [45]. The application of the said device is limited in the sense that it can only detect sinkholes created under the detector or those in the vicinity of its diameter. As the device is of limited size and does not include a WSN system, it cannot be installed for sinkhole detection throughout a pipeline network. Similarly, a sinkhole monitoring system based on pressure sensors has been developed for monitoring human-induced sinkholes. In this method, pressure sensors are placed close to underground utilities such as pipelines and subway tunnels. These pressure sensors comprise of four springs fixed on an axle [39]. When pressure changes in the vicinity of a pressure sensor, the sensor detects the change and wirelessly sends alarm signals to an end user, as depicted in Figure 2e. The signals transmitted underground by the pressure sensors are received by an unmanned aerial vehicle

A patent describes the application of a neural network learning database for sinkhole detection. This patent is related to the development of a method for creating a small simulated sinkhole cavity characterized by the shape, texture, and complex background of an actual sinkhole. This method utilizes a drone fitted with a thermal imaging camera to detect sinkhole cavities at heights of the order of 10 m [49]. The images captured by the thermal drone camera can be used to construct an image database for the development of a neural network based sinkhole detection model. Figure 2f depicts the schematic of a simulated sinkhole with shapes similar to those of actual sinkholes. A similar device with abilities to detect changes in an underground medium has been developed. This

First, the patents relevant to sinkhole detection and monitoring are overviewed with their limitations. There are various patents with various operating and functioning techniques such as

*3.1. Patents Related to Sinkhole Detection or Monitoring*

(UAV) or a receiver mounted on a moving vehicle such as a train [39].

#### *3.1. Patents Related to Sinkhole Detection or Monitoring*

First, the patents relevant to sinkhole detection and monitoring are overviewed with their limitations. There are various patents with various operating and functioning techniques such as safety methods to overcome the sudden collapse or sinkhole occurrence [36,37]. Likewise, some patents were invented for sinkhole monitoring via developing experimental setups in laboratories, such methods and experimental setup have been cited in Table 2 [47–53]. However, herein authors just considered patents with applications of WSN. As reported in relevant patents, a device for detecting underground sinkhole formation is partially buried in the ground. A typical sinkhole detector comprises of a cable, a control circuit, and a weight, as depicted in Figure 2a. If a sinkhole is created in the vicinity of the device diameter or under the detector, the device releases the attached weight. This activates a circuit that sends a notification to an administration center [45]. The application of the said device is limited in the sense that it can only detect sinkholes created under the detector or those in the vicinity of its diameter. As the device is of limited size and does not include a WSN system, it cannot be installed for sinkhole detection throughout a pipeline network. Similarly, a sinkhole monitoring system based on pressure sensors has been developed for monitoring human-induced sinkholes. In this method, pressure sensors are placed close to underground utilities such as pipelines and subway tunnels. These pressure sensors comprise of four springs fixed on an axle [39]. When pressure changes in the vicinity of a pressure sensor, the sensor detects the change and wirelessly sends alarm signals to an end user, as depicted in Figure 2e. The signals transmitted underground by the pressure sensors are received by an unmanned aerial vehicle (UAV) or a receiver mounted on a moving vehicle such as a train [39].

A patent describes the application of a neural network learning database for sinkhole detection. This patent is related to the development of a method for creating a small simulated sinkhole cavity characterized by the shape, texture, and complex background of an actual sinkhole. This method utilizes a drone fitted with a thermal imaging camera to detect sinkhole cavities at heights of the order of 10 m [49]. The images captured by the thermal drone camera can be used to construct an image database for the development of a neural network based sinkhole detection model. Figure 2f depicts the schematic of a simulated sinkhole with shapes similar to those of actual sinkholes. A similar device with abilities to detect changes in an underground medium has been developed. This device is used to detect any leakage or deterioration in underground liquid pipelines carrying oil or water [38].

As depicted in Figure 2b, a transmitter device is buried in the middle layer of soil, and several signal receivers are placed above the ground to receive wireless ultrasonic signals emitted from the transmitter. The changes in the paths of these signals while propagating towards the receiver end can be detected by measuring their travel time between the transmitter and receiver. Any difference in travel time indicates a change in the underground medium. A limitation of this device is that ultrasonic signal propagation can be affected by the vibrations and sound effects generated by vehicular traffic on the ground or any other source during practical use.

#### *3.2. Patents Related to Leakage Monitoring*

Similar to the above-mentioned devices for sinkhole detection and monitoring, mobile-type monitoring devices for pipeline inspection have been developed to overcome the leakage issues in sewer pipelines [23–31]. Meanwhile, other experimental setups [32–35] and safety equipment [20–22] have been invented for pipeline leakage monitoring. However, these experimental setups and devices did not used the WSN system for pipeline monitoring. Leakage in sewer pipelines that transport wastewater and raw sewage to wastewater treatment plants leads to the contamination of surrounding soil and groundwater and the creation of sinkholes. As depicted in Figure 2c, this problem can be resolved by utilizing modern technology in the form of a remote pipeline-inspection device [28]. This robotic device comprises a camera to capture the images of pipeline interiors, and this data can be transmitted via a communication network for detailed visual inspection, as depicted in Figure 2c. A similar mobile device capable of moving forward and backward with cameras installed on its front and rear sides, as depicted in Figure 2c, can be used to inspect the existence of any leakage, crack, or damage [23] within a pipeline. The said device can be placed inside a pipeline, moved forward up to a fixed point, and made to automatically return to its starting point. The inspection of captured images helps conclude whether the sewer pipe mains has been damaged or not.

These devices [23,28] are currently under use. However, automated image processing and analysis techniques are necessary for replacing human visual inspection, which requires time and effort. With regard to real-time application, the said devices are expensive, time consuming, and require human intervention. Moreover, the devices can only be used to inspect a pipeline section by section, and they cannot inspect the entire pipeline network at once. However, AI-based automation methods are being investigated to facilitate more efficient maintenance compared to visual-inspection methods.

The risk of sinkhole creation has increased because of various ground subsidence phenomena. The method shown in Figure 2d is related to a safety monitoring system for a pipeline, wherein a sensing unit attached to a pipeline network generates position change and vibration signals at regular intervals in accordance with fluid flow inside the pipe to detect leakage and/or rupture in the pipeline. Using the pipe network information already stored in a management server, it is possible to track the position of the damaged parts of a pipeline via the interpretation of received position-change and vibration signals [24]. Sensing units are attached to pipelines using a magnetic outer-bottom portion comprising two subunits—(1) position change sensing unit including acceleration and gyro sensors to generate a position change signal; (2) vibration sensing unit that converts the vibration signals of the installed weight into electrical signals. The device provides the advantage of being able to detect changes in the vibration pattern and position due to the changes in flow velocity when a pipeline is distorted or broken. However, the reliability of the said system may deteriorate because of the transmission of an abnormal signal in the event of strong vibrations caused by construction work or rail and road traffic load.

#### **4. Literature Review**

#### *4.1. Web of Science Analysis*

A web of science analysis was performed to provide relevant articles and other information such as citations and article categories. From the standpoint of applying the WSN system to monitor and prevent pipeline leakage and sinkhole occurrence, the following different sets of keywords have been used according to trial and error—(1) leakage, pipeline, wireless sensor, and monitoring; (2) leakage, pipeline, and wireless sensor; (3) leakage, water pipeline, and underground; (4) sinkhole and underground; (5) leakage, pipeline, and sinkhole; (6) pipeline, sinkhole, and wireless sensor; and (7) human-induced sinkholes.

Research articles published between 2000 and 2018 with different sets of keywords are summarized in Table 3. It can be observed that a majority of extant studies focused on either leakage monitoring and detection of underground fluid pipelines (numbers marked in red under the water pipeline monitoring category in Table 3) or natural sinkhole monitoring and detection (numbers marked in red under the natural sinkhole category in Table 3). The numbers in orange under the others category in Table 3 indicate the results that are not relevant to the scope of this study (i.e., pipeline corrosion, gas pipelines, underwater pipelines, and aboveground pipeline leakage monitoring). In other instances, search results with different keyword combinations yielded identical results. Only one article was found to be related to sinkhole detection and monitoring due to leakage in underground sewer/water pipelines, as described in Table 3 (the number marked in green).

In accordance with Table 3, after filtering the duplicated articles, 47 articles published in different journals related to sewer/water pipeline and human-made sinkhole monitoring using WSN systems were observed.

Among those 47 articles, majority of the contributions (i.e., 35 articles) were published in journals related to technical domains such as computer science and information systems, telecommunication, electronics, and WSN systems. However, a relatively smaller number of articles (i.e., 12 articles) were

published in journals related to application domains such as civil engineering, water resources, soil mechanics, and environmental sciences.


**Table 3.** Web of science analysis of articles and contributions of different authors related to the field of interest (time span 2000–2018).

<sup>1</sup> not related to the intended field of study, <sup>2</sup> total sum of the column is "01" because both articles are duplicate.

The histogram in Figure 3 depicts the above-mentioned 47 articles with the number of publications per year between 2000 and 2018 pertaining to the use of WSN for underground water and sewer pipeline leakage and burst monitoring, and man-made sinkholes. *Sustainability* **2019**, *11*, x FOR PEER REVIEW 9 of 25
