Underground Pipes Research Articles

Listen - Look up! Listen - Look down! Experiencing the counter-city through a sonic and augmented reality experience of urban undergrounds in southeast Melbourne

This paper is set in Nairm/Port Phillip Bay (Melbourne, Australia) – specifically in Boon Wurrung Country – across and below the watery landscapes that once characterised the south-eastern shore of Port Phillip Bay. Here, water springs and wetlands were gradually dredged, drained, filled, piped underground, or built over through processes of settler colonial urbanisation. Nevertheless, waters must always flow, and ecologies find remarkable ways to survive, especially underground. This paper discusses how an interactive sound and augmented reality (AR) experience can help us to reconnect histories of water, soils, and non-humans that inhabit the underground pipes and other water infrastructures in the urban. The paper uses as a case study The Rippon Lea Estate, a colonial house and pleasure gardens currently managed by the National Trust Australia, to explore the hidden and underground water narratives and materialities that underpin it. Through our collaborative project between the Trust, Universities and the Boon Wurrung Foundation, we have grappled with the question of how to invite visitors to Rippon Lea to engage ethically and care-fully with undergrounds, groundwaters and the histories they represent. This paper shares this counter-experience, inviting readers to immerse themselves in the layers of storytelling, materiality and the beings that traverse these realms.

Classification Size of Underground Object from Ground Penetrating Radar Image using Machine Learning Technique

Ground Penetrating Radar (GPR) is a useful tool in detecting subsurface object or hidden structure defects However, the time-consuming problems and high requirement of professional manpower is required to analyse the GPR data. Machine learning is a tool that endowed with the ability to learn, and it can reduce time taken for the GPR data analysing. To simplify the identification process, a framework is proposed to classify the size of underground metallic pipe by using Histogram of Oriented Gradient (HOG) as a feature extraction algorithm. Two machine learning algorithms namely Support Vector Machines (SVM) and Backpropagation Neural Network were proposed to classify the size of the underground metallic pipe. As a result, the accuracy from the identification is more than 98% for both classifier algorithm.

Study on the impact of ovality defect on structural stability of CIPP liner of drainage pipeline

Cured-in-Place Pipe (CIPP) is a trenchless pipeline rehabilitation technology commonly used for repairing underground municipal pipes. It effectively, safely, and environmentally friendly resolves drainage pipe leakage and dripping issues by curing a new resin-impregnated liner inside the original pipe. However, in practical applications, ovality defects may occur in CIPP liners due to insufficient inflation, deformation of the original pipe, joint misalignment, and other problems. These defects have the potential to reduce the structural bearing capacity of the liners. To investigate the buckling mechanism of oval liner structures under external water pressure, two sets of OD 600 mm CIPP liner buckling tests were conducted. The critical buckling stress state and buckling mode characteristics exhibited similarities across liners with different initial ovalities. With an increase in the ovality defect of the liners from 0% to 5%, the critical buckling pressure decreased by 10.62%, while the maximum radial deformation displacement decreased by 62%. Existing models have shown an inability to accurately predict the buckling pressure of oval liners with an initial annular gap. Consequently, this study proposes an improved analytical solution for calculating the critical buckling pressure of liners with ovality imperfections under the influence of an annular gap, which aligns well with the experimental data. The conclusions drawn from this study provide substantial data support for ensuring the accuracy and safety of CIPP liner rehabilitation design.

Aerial characterization of surface depressions in urban watersheds

Digital elevation models (DEM) are one of the most fundamental inputs for hydrological modeling. It has been a common practice to remove all surface depressions in a DEM as they are assumed to be data errors. The emerging technology of unmanned aircraft systems (UAS) provides an opportunity to re-examine this assumption at the hyperspatial resolution. This study was the first attempt to characterize small surface depressions in urban environments using UAS imagery. Using an urban area in south Texas as the study site, UAS flights were conducted to yield hybrid DEMs at the resolution of 8–14 cm, coupled with comprehensive ground truth collection. Surface depressions identified from the UAS DEMs were first corrected based on the vertical accuracy of DEMs and then validated through field surveys, with comparisons to two existing LiDAR DEMs (1-m and 10-m). The hydrological impacts of different DEM-derived estimates of catchment depression storage were examined using the Curve Number method across different design storms. Results show that the UAS DEMs outperformed the LiDAR DEMs in describing the microtopographic control of urban overland flow and associated hydrological connectivity across built and natural features. The 8-cm UAS DEM revealed 926% more depression storage than the 10-m LiDAR DEM. This demonstrates a compelling correlation between increasing DEM resolution and enhanced quantification of depression volume. Consequently, the increased depression storage reduced surface runoff by 41% under a two-year design storm and 13% under a 200-year design storm. The results suggest a strong relationship between the DEM resolution and the derived depression estimates, aligning with the fractal nature of watershed systems. Also, the results indicate that the centimeter-level UAS DEMs were not immune from problems. They could yield fake depressions caused by factors such as vegetation, temporary street objects, and underground sewer pipes. The findings of this study suggest the need to quantify the relationships between DEM resolution and associated hydrological attributes and develop new digital drainage analysis algorithms that could effectively incorporate UAS data into urban hydrological modeling.

Mapping soil corrosivity in an Australian arid environment and comparing corrosion rates of exclusion fence netting with different zinc coatings

Exclusion fencing and feral-free nature reserves are a key component of many threatened species recovery strategies in Australia. Soil corrosion damage (rust) sustained on exclusion fence netting can create entry points for feral animal incursions into areas of high conservation value. The use of soil physicochemical data to produce corrosivity risk maps is an approach used by project managers to identify the type of corrosion control measures (e.g. use of galvanised zinc coatings) needed to sufficiently limit the deterioration of buried metal infrastructure. This approach is commonly used in subsoil environments (e.g., underground piping), but very few studies have investigated the corrosivity potential of surfaces soils. This paper used surface soil pH, salinity and texture data collected from 69 field sites to map soil corrosivity potential (i.e., fence corrosion risk) at the Arid Recovery nature reserve in South Australia. The majority (72%) of soils in the reserve were predicted to be moderately corrosive and only 16% were predicted to be highly/very highly corrosive. Standard zinc-aluminium fence netting samples buried at six field sites for 18 months were used to validate map predictions. Zinc corrosion on netting samples at field sites were highly variable, particularly at the highly saline (ECe ≥ 5 dS/m) sites. Maximum predicted zinc corrosion rates were within 1.3 μm/year of measured maximum rates at four of the six sites. The fence corrosion risk mapping method used was able to reliably predict areas of low to moderate fence corrosion, but further research is needed to refine its ability to identify high risk areas. An accelerated corrosion experiment (9-month incubation at 65% WHC and elevated ambient temperatures) was used to assess the relative performance of standard zinc-aluminium (124 g/m2 zinc coating), heavy zinc-aluminium (410 g/m2) and heavy galvanised (650 g/m2) fence netting in different soil environments present on the nature reserve. The standard zinc-aluminium wire coating provided sufficient corrosion-resistance for use in the weakly saline (ECe < 5 dS/m) soils (Rhodic Arenosols, Calcic Chromic Solonetz and Chromic Cambisols). However, the increased corrosion-resistance of the heavy zinc-aluminium is needed in the highly saline (ECe ≥ 5 dS/m) Chromic Luvisol. None of the tested fence products were suitable for use in the highly saline Cambic Calcisols. A more corrosive-resistant alternative such as stainless-steel would be more suited for this very highly corrosive environment. Further research is recommended to confirm the long-term (>5 year) suitability of these products in these different soil types.

Cathodic Protection Online Monitoring Using a Low Power Wide Area Network Communication System

Cathodic protection is a corrosion control and prevention system that is applied to underground pipe structures by providing an electric charge to the structure to be protected. An online monitoring system for cathodic protection is urgently needed to save costs and ensure operator safety in the field in the care of the protected structure. This study aimed to evaluate cathodic protection online monitoring using a low power wide area network (LPWAN) communication system. Cathodic protection online monitoring in this study was applied using LPWAN with a radio frequency of 433 MHz. In this work, the type of communication with wireless technology has been chosen with low power consumption and can accommodate the distance between test stations in the distribution pipeline. From the results of testing the cathodic protection online monitoring system, it can be seen that measurement data that has been done manually can be replaced in real-time and monitored remotely. This system is highly recommended for areas that have so far not been covered by manual measurements, for example, remote areas prone to flooding, swamps, and interference areas that require denser data information to make handling easier to do early.

Superlattice-shelled nanocrystalline core structural design for highly sensitive GMI sensors

Giant magnetic impendence (GMI) sensors are known as a significant pillar of modern technology, and has many applications in smart society such as automation, navigation and bioengineering. Developing high-sensitive GMI sensors operating under extremely weak magnetic fields is highly desirable yet challenging. Here, we proposed superlattice-shelled nanocrystalline core structural design in the cobalt-based amorphous sensor-core microwires for the highly sensitive GMI sensors. Continuous Co-based amorphous microwires with a length up to thousands of meters and uniform diameter is first fabricated by a scalable modified Taylor–Ulitovsky method and then processed by the picosecond lasering heat treatment. As a result, the microwire exhibits a unique nanostructure consisting of ultrafine nanocrystalline cores surround by the thermal-stable Cr-rich superlattice shell, and hence circumferential magnetic domains of the higher density and intensity. The GMI sensors made from nanostructured Co-based microwires show a sensitivity up to 1743 mV/Oe, the maximum GMI ratio up to 78%, increasing the performance by up to twice and nine times respectively over the GMI sensor made from the amorphous counterpart, and a wide linear range of ± 70000 nT. The correlation between the microstructure, magnetic domain structure and GMI performance is also established and discussed in the nanostructured Co-based microwires. Furthermore, we demonstrate the successful application of the highly sensitive GMI sensor in geomagnetic communication to detect underground energy transmission metal pipes with a detection resolution down to pT-level weak magnetic fields.

Visualizing of the below-ground water network infrastructure

Abstract. This research addresses the design and the utilization of vertical reference features in Augmented Reality (AR) to aid in providing perspective from underground pipes to the ground surface. The study utilizes 3D GIS data and assigns Z coordinates to the Underground Utility Networks (UUNs) using the AHN4 digital elevation data of the Netherlands (and either use standard depth or surveyed depth). However, registering Z coordinates and related data at the vertex level presents data registration issues that Esri's current Utility Network Model (UNM) cannot accommodate. A supplementary data model is required to address this, which can be achieved through vertical reference features. These multifunctional features emphasize the height difference between the pipe and the ground surface and can be used in AR applications to provide better depth clues. Additionally, polygons signatures and flow direction are utilized to enhance visualization.

Entrepreneurship and alignment work in the Swedish water and sanitation sector

Water and sewage (WS) systems are, like most grid based infrastructural systems, often centralised and hierarchical and the end user has almost no possibility to influence the technical standards, business models or system architecture. The preferred method for connecting new areas to the grid are underground water pipes and gravity flow for sewage. Thus, the WS system is “tightly coupled”. It is hard to change and conservative in its system culture, exhibiting a strong “momentum” or “path dependence”.In this article we investigate an unusual case in the development of WS-systems. As a rule, WS-systems, as most infrastructural systems, develop gradually through incremental innovations, and system owners/utilities traditionally build their systems “from the inside out”. In our case, we investigate a situation where the end users took the initiative to connect a residential area, Aspvik, part of the municipality of Värmdö, outside Stockholm, Sweden, to the municipal grid and thus expand the WS-system, not from the inside out, but from the outside in.Furthermore, we highlight another unusual feature: the role of a resident that acted as the “entrepreneur” in this process of WS-system expansion. The entrepreneur had unique trust building abilities in the local community, which the regime actor (the WS utility), could not match. Historically, inventor-entrepreneurs have been common, acting as “system builders” in the establishment phase of new infrastructural systems. However, entrepreneurs outside the regime are not common in the WS sector.Although atypical in mature WS systems in developed countries, these types of local initiatives or hybrid solutions are common in developing countries. In this article, we argue that there are lessons to be learnt from our case, when dealing with system expansion processes both inside and outside the Global North.

Analysis of the Importance of the Filling Material Characteristics Injected Around the Precast Concrete Lining in the Microtunnelling Technology

Microtunnelling is an excavation technique capable of positioning underground pipes with considerable advantages from the point of view of the environment, safety, construction times and also total costs, when the lengths are significant. The technology used is now reliable and is suitable for use in different types of soils and rocks without particular problems. The installation of the concrete lining of the micro-tunnel takes place behind the excavation machine starting from a thrust shaft. A filling material must be injected between the outer surface of the lining and the tunnel wall. This filling material plays a very important role, because it conditions the overall stiffness of the support system and, therefore, influences the radial load applied by the ground to the support system. Therefore, it is necessary to take into account the presence of the filling material in order to correctly size the support system of the micro-tunnel. This paper illustrates a new procedure for analyzing the behavior of the micro-tunnel support system, based on widely used and tested analytical calculation methods. This procedure was applied to a real case, underway in Northern Italy. The results obtained were then compared with those of numerical modeling, which made it possible to simulate the micro-tunnel in detail. From the comparison it was possible to note how the analytical calculation procedure leads to stress states similar (slightly higher) to those of numerical modeling; the first, therefore, can be effectively used in the preliminary stages of the design of micro-tunnels to obtain useful information on the characteristics of the support systems to be adopted to ensure the stability.

A research on data integration and application technology of urban comprehensive pipe gallery based on three‐dimensional geographic information system platform

AbstractThree‐dimensional Geographic Information System (3D GIS) technology is often used in geology, mining, hydrology and other fields. It is also used in intelligent management of urban comprehensive pipe gallery projects, because the real environment with the sky, ground, and underground can be intuitively simulated in the virtual reality environment by 3D GIS platform. Through the research on data integration and application technology of urban comprehensive pipe gallery, the 3D model of comprehensive pipe gallery project data can be created based on Building Information Modelling and GIS technologies, and a comprehensive underground pipelines network management information system has been developed to realise the integration of various data, including 3D data of comprehensive pipe gallery model and underground pipe network model, 2D or 3D GIS data of the ground and underground etc. On this basis, the functions of intelligent planning and approval management, the safety analysis and disaster prevention planning and decision‐making of urban comprehensive pipe gallery projects can be further realised. The research results have been applied to the planning and construction process management of the comprehensive pipe gallery project in the sub‐centre of Beijing.

Age-dependent failure probabilities of corroding concrete sewer pipes under traffic loads

Concrete pipes are frequently used in the wastewater infrastructure. These buried structures are prone to ageing and deterioration, as well as damage under excessive stresses from traffic. This study presents the first set of temporal fragility models for underground concrete sewer pipes under the compounding effects of corrosion and truck loads. To address the high computational costs of fragility modeling, Bayesian Additive Regression Trees (BART) – a machine-learning based meta-model – are trained using a high-fidelity computational model of buried concrete pipes. The BART models are subsequently applied to develop age-dependent fragility models for serviceability and collapse of pipes conditional on truck loads. Considered uncertainties include statistically significant concrete and soil properties, truck load, and environmental factors that affect the corrosion of concrete sewer pipes. Results indicate that the direction of traffic stream, the degree of loss of wall thickness due to corrosion, and the maximum allowed truck load are critical factors that must be considered when planning inspection, rehabilitation, and retrofit of this underground infrastructure. According to the results, concrete sewer pipes buried in perpendicular to the direction of traffic flow are more vulnerable than those that are parallel to the direction of traffic flow. The results highlight that the probability of collapse is insignificant when it comes to vehicles weighing less than the design truck weight; however, the probability of collapse significantly increases for the moderate and severe corroded sewer pipes when it comes to the overweight vehicles. The age-dependent fragility models indicate that for sewer pipes buried perpendicular to the direction of traffic stream with service life of less than 25 years, the probability of the first major structural defect is less than 5%. This is also true for sewer pipes that have been in service for less than 45 years if the traffic stream is parallel to the buried pipe. The developed fragility models also constitute a key component of quantitative risk assessment of underground wastewater collection systems.

Multi-Sensor Fusion SLAM Method for Underground Power Pipe Gallery

The satellite signal in the underground power pipe gallery is missing and the light is dim, so simultaneous localization and mapping (SLAM) is facing many challenges. Aiming at this special scene, a new SLAM method based on multi-sensor fusion is proposed by using a new type of area array laser radar and a monocular camera to build a 3D scanner. The geometric structure of the global map is obtained by fusing the pre-integrated IMU data and the lidar data. The texture and color information of the global map are supplemented by visual information rendering. A data connection bridge is built between the equipment and the local server in the form of remote networking to achieve data synchronization. The experimental results of an underground power pipe gallery in Zhejiang Province show that the method significantly improves the accuracy of 3D reconstruction in complex environments, and provides a useful reference for the development of localization and mapping of underground inspection robots.

A Review on Manhole Monitoring System

Abstract: Smart city is a concept which every country look forward to seed in their lands. To make that seed a big tree, a lot of aspects need to be addressed. Among them an important element is that, the drainage system. Even a small area with the proper drainage system will contribute a lot to the society. Manholes act as the access point to a sewer system. If there are any blockages in the drainage pipelines, manholes are the way to get into the underground pipes. If the blockages are not addressed, the sewage water overflow through the manholes which rises the temper of the pedestrians as well as vehicle drivers. Even tilted manhole covers are dangerous since they lead to accidents. Also the life of the scavengers who enters the manhole is not safe because of unawareness of the toxic level of the drainage or sewage water.

A Comparison of the Performance of Four Acoustic Modulation Techniques for Robot Communication in Pipes

Autonomous robotics is an emerging technology for the inspection of a vast network of underground pipes. Communication between autonomous robots is essential to optimise their efficiency and network coverage. However, sending a message acoustically is not a well-researched topic because most of the existing literature is devoted to the study of the acoustic properties of the pipe for the purpose of sensing rather than communication. In particular, the influence of multi-modal propagation and background noise on the quality of acoustic communication in pipes has not been well understood. This paper studies the performance of four standard acoustic communication techniques in a dry drainage pipe to fill this knowledge gap. The noise resistance, communication range and data rate of these techniques are estimated through numerical simulations and laboratory experiments. It has been found that the techniques based on shift keying requires at least 5--10 dB signal to noise ratio (SNR) to function properly while the chirp linear frequency modulation technique can operate reliably with SNR = 0 dB or event lower SNR. The results also suggest that the multi-modal propagation in the pipe has significant effects on the package error rate. The frequency dependent sound attenuation in the pipe also affects the communication range and data rate. In particular, for a 150 mm diameter dry pipe the maximum robot operation distance is likely to be limited to 50--100 m with the highest carrier frequency of around 10 kHz and data rates below 6300 bps. The results of this work pave the way to the development of acoustic communication modules to be deployed on tetheless robots designed to inspect a buried pipe network autonomously and collaboratively.

Size estimation of underground targets from GPR frequency spectra: A deep learning approach

GPR (Ground Penetrating Radar) is a robust and effective device for identifying underground artefacts. Construction companies and civil engineers should be aware of the sizes of rebars and pipelines before and during construction work for various reasons. Most research efforts have typically concentrated on GPR signal analysis in the time domain, however recent studies have increasingly focused on analysis in the frequency domain. This paper proposes an artificial neural network (ANN) model for estimating the diameter of underground rods (solid) and pipes (hollow). GPR data captured in the time domain domain is transformed to the frequency domain using FFT, after which feature extraction is performed using ANN. An FPGA-based prototype GPR system is used to collect GPR A-Scan data for a variety of targets made of aluminium, stainless steel, rebar, and PVC. A mean absolute percentage error of 1.89% is achieved using the proposed model. The experimental results confirm the effectiveness of the proposed approach in extracting size-related information from GPR data.

Propagation of stress waves in layered rock mass under the impact of high-pressure gas

High-pressure gas (HPG) blasting is safe and environmentally friendly, and has replaced traditional explosive blasting in some applications. The characteristics of HPG impact load and the propagation law of the stress wave in layered rock mass (LRM) under HPG blasting were investigated experimentally and numerically. Through experimental tests of hole wall pressure, a segmented exponential model of the hole wall pressure under the impact of HPG was developed; it accurately accounted for the time history characteristics of the hole wall load. Experimental tests of stress wave propagation were conducted; the soft rock–hard rock interface was found to have a significant effect on stress wave propagation in the LRM. Based on the experimental results, a specific strain model for 10 MPa HPG impact was fitted for a single-hole LRM. A polynomial exponential model and a specific strain model (20 MPa HPG impact) were found for the double-hole LRM. The stress wave attenuation laws for single-hole and double-hole LRM were characterised well. The propagation characteristics of stress waves in LRM under the impact of HPG were analysed and a numerical model of stress wave propagation was established. The numerical model adopted the Riedel–Hiermater–Thoma (RHT) material model for the test parameters. The proposed segmented exponential models of hole wall pressure were applied to the lower, middle and upper parts of the blasthole. With the feasibility of the numerical model analysed, the stress wave propagation characteristics were studied by numerical simulation of an underground pipe gallery. This study provides theoretical guidance and practical value for improving rock-breaking theory and optimising HPG blasting in LRM.

Mobile augmented reality-based visualization framework for lifecycle O&M support of urban underground pipe networks

The structural deterioration of urban underground pipe networks is the accumulated combined effects of physical, environmental and operational factors during the whole lifecycle. Accurate on-site locating and mapping of pipes and their conditions has been a great challenge for construction, maintenance and emergency response in a dynamic manner. Existing approaches, mostly based on design-centric and static visualization, are unsuitable for implementation within the operation and maintenance (O&M) phase because they are performed in a completely virtual environment and are unable to interact with buried assets on site. An integrated hyperrealistic visualization framework based on mobile augmented reality (MAR) is developed to support various real-life project tasks for O&M support of urban underground pipe networks. The proposed approach consists of three parts: a cloud-based data management platform, a 3D visualization development platform, and a location-based registration method for MAR. A cloud–edge–mobile layer is proposed to manage, analyze, process and visualize multisource data, especially for dynamic data. Field experiments on a real-life urban gas pipe network were carried out to investigate the feasibility of the proposed framework to achieve informed O&M support. The results demonstrate that (1) a smartphone linked to a Lite RTK device allows for both accurate locating and easy operation; (2) both the 3D virtual digital model and the multisource data visually superimpose onto the realistic environment, enabling on-site human–machine interaction in a hyperrealistic manner; and (3) MAR-based immersive visualization contributes to avoiding excavation damage, improving O&M efficiency and assisting emergency responders to make timely and better–informed decisions based on multisource information fusion.

Analysis of the Effect of Capillary Water Absorption on the Resistivity of Cementitious Materials

In a humid environment, the stray current generated by subway operation will corrode the underground pipe network and the internal steel structure of the track plate, which will seriously affect the service life of the subway track plate and increase the maintenance cost later. Groundwater in subway projects mainly enters the concrete interior through capillary action and affects the concrete resistivity, and there is a lack of research on the mechanism of groundwater effect on concrete resistance. In this study, the variation of cement mortar resistivity with capillary water absorption time for cement mortar with different amounts of mineral admixtures (fly ash, ground-granulated blast furnace slag, and silica fume) was measured by the four-electrode method, and the mechanism of the influence of the electrical properties of cementitious materials under the effect of capillary water absorption was analyzed based on the mercury-pressure method (MIP) and thermogravimetric method (TG-DTG). The results show that with the increase in capillary water absorption time, the change curve of cement mortar resistivity can be divided into two stages; in the first stage, capillary water absorption leads to gel pores and transition pores quickly connecting to capillary pores and other large pores to form a water-saturated conductive pathway, resulting in a rapid decrease in resistivity, when the gel pores and excessive pores have a greater impact on resistivity. The second stage is that of capillary water absorption, to a certain extent, after the specimen’s internal water upward development rate slows down; at this time, the formation speed of the conductive pathway decreases, resulting in the rate of change in resistivity decreasing and gradually stabilizing. The incorporation of silica fume can effectively improve the resistivity of cementitious materials under the action of capillary water absorption, in which the resistivity of specimens incorporated with 15% silica fume after 36 days of capillary water absorption is 10.39 times that of the reference group, which is mainly due to its lower porosity and a higher percentage of gel pores.

S-BIRD: A Novel Critical Multi-Class Imagery Dataset for Sewer Monitoring and Maintenance Systems

Computer vision in consideration of automated and robotic systems has come up as a steady and robust platform in sewer maintenance and cleaning tasks. The AI revolution has enhanced the ability of computer vision and is being used to detect problems with underground sewer pipes, such as blockages and damages. A large amount of appropriate, validated, and labeled imagery data is always a key requirement for learning AI-based detection models to generate the desired outcomes. In this paper, a new imagery dataset S-BIRD (Sewer-Blockages Imagery Recognition Dataset) is presented to draw attention to the predominant sewers' blockages issue caused by grease, plastic and tree roots. The need for the S-BIRD dataset and various parameters such as its strength, performance, consistency and feasibility have been considered and analyzed for real-time detection tasks. The YOLOX object detection model has been trained to prove the consistency and viability of the S-BIRD dataset. It also specified how the presented dataset will be used in an embedded vision-based robotic system to detect and remove sewer blockages in real-time. The outcomes of an individual survey conducted at a typical mid-size city in a developing country, Pune, India, give ground for the necessity of the presented work.