Feasibility Evaluation of a Vibration-Based Leak Detection Technique for Sustainable Water Distribution Pipeline System Monitoring

Conventional water pipeline leak-detection surveys employ labor-intensive acoustic techniques, which are usually expensive and less useful for continuous monitoring of distribution pipelines. Based on a comprehensive review of literature and available commercial products, it has been recognized that despite previous studies and products attempting to address the limitations of the conventional surveys by proposing and evaluating a myriad of leak-detection techniques (LDTs), they lacked extensive validation on complex looped systems. Additionally, they offer limited compatibility with some pipe materials such as those made of plastic and may even fail to distinguish leaks from other system disturbances. A novel LDT that addresses some of these limitations is developed and evaluated in the current study using an experimental set-up that is representative of a real-world pipeline system and made of Polyvinyl Chloride (PVC) pipe. The studied LDT requires continuous monitoring of the change in the cross spectral density of surface vibration measured at discrete locations along the pipeline. This vibration-based LDT was hypothesized to be capable of not only detecting the onset of leakage, but also determining its relative severity in complex pipeline systems. Findings based on a two-phase, controlled experimental testing revealed that the proposed LDT is capable of detecting leakages and estimating their relative severities in a real-size, multi-looped pipeline system that is comprised of multiple joints, bends and pipes of multiple sizes. Furthermore, the sustainability merits of the proposed LDT for a representative application scenario are estimated. Specifically, life cycle costs and energy consumption for monitoring the large diameter pipelines in the water distribution system of the Charleston peninsula region in South Carolina are estimated by developing conceptual prototypes of the sensing, communication and computation schemes for practically employing the proposed LDT. The prototype designs are informed by the knowledge derived from the two-phase experimental testing campaign. Overall, the proposed study contributes to the body of knowledge on water pipeline leak detection, specifically to non-intrusive vibration-based monitoring, applications on plastic pipelines, and smart and sustainable network-wide continuous monitoring schemes

Natural and Technological Hazards in Urban Areas

Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events

The energy problem in resource constrained wireless networks

Today Wireless Sensor Networks are part of a wider scenario involving several wireless and wired communication technology: the Internet Of Things (IoT). The IoT envisions billions of tiny embedded devices, called Smart Objects, connected in a Internet-like structure. Even if the integration of WSNs into the IoT scenario is nowadays a reality, the main bottleneck of this technology is the energy consumption of sensor nodes, which quickly deplete the limited amount of energy of available in batteries. This drawback, referred to as the energy problem, was addressed in a number of research papers proposing various energy optimization approaches to extend sensor nodes lifetime. However, energy problem is still an open issue that prevents the full exploitation of WSN technology. This thesis investigates the energy problem in WSNs and introduces original solutions trying to mitigate drawbacks related to this phenomenon. Starting from solutions proposed by the research community in WSNs, we deeply investigate critical and challenging factors concerning the energy problem and we came out with cutting-edge low-power hardware platforms, original software energy-aware protocols and novel energy-neutral hardware/software solutions overcoming the state-of-art. Concerning low-power hardware, we introduce the MagoNode, a new WSN mote equipped with a radio frequency (RF) front-end which enhances radio performance. We show that in real applicative contexts, the advantages introduced by the RF front-end keep packet re-trasmissions and forwards low. Furthermore, we present the ultra low-power Wake-Up Radio (WUR) system we designed and the experimental activity to validate its performance. In particular, our Wake-up Radio Receiver (WRx) features a sensitivity of -50 dBm, has a current consumption of 579nA in idle-listening and features a maximum radio range of about 19 meters. What clearly resulted from the experimental activity is that performance of the WRx is strongly affected by noise. To mitigate the impact of noise on WUR communication we implemented a Forward Error Correction (FEC) mechanism based on Hamming code. We performed several test to determine the effectiveness of the proposed solution. The outcome show that our WUR system can be employed in environment where the Bit Error Rate (BER) induced by noise is up to 10^2, vice versa, when the BER induced by noise is in the order of 10´3 or below, it is not worth to use any Forward Error Correction (FEC) mechanism since it does not introduce any advantages compared to uncoded data. In the context of energy-aware solutions, we present two protocols: REACTIVE and ALBA-WUR. REACTIVE is a low-power over-the-air programming (OAP) protocol we implemented to improve the energy efficiency and lower the image dissemination time of Deluge T2, a well-known OAP protocol implemented in TinyOS. To prove the effectiveness of REACTIVE we compared it to Deluge exploiting a testbed made of MagoNode motes. Results of our experiments show that the image dissemination time is 7 times smaller than Deluge, while the energy consumption drops 2.6 times. ALBA-WUR redesigns ALBA-R protocol, extending it to exploit advantages of WUR technology. We compared ALBA-R and ALBA-WUR in terms of current consumption and latency via simulations. Results show that ALBA-WUR estimated network lifetime is decades longer than that achievable by ALBA-R. Furthermore, end-to-end packet latency features by ALBA-WUR is comparable to that of ALBA-R. While the main goal of energy optimization approaches is motes lifetime maximization, in recent years a new research branch in WSN emerged: Energy Neutrality. In contrast to lifetime maximization approach, energy neutrality foresees the perennial operation of the network. This can be achieve only making motes use the harvested energy at an appropriate rate that guarantees an everlasting lifetime. In this thesis we stress that maximizing energy efficiency of a hardware platform dedicated to WSNs is the key to reach energy neutral operation (ENO), still providing reasonable data rates and delays. To support this conjecture, we designed a new hardware platform equipped with our wake-up radio (WUR) system able to support ENO, the MagoNode++. The MagoNode++ features a energy harvester to gather energy from solar and thermoelectric sources, a ultra low power battery and power management module and our WUR system to improve the energy efficiency of wireless communications. To prove the goodness in terms of current consumption of the MagoNode++ we ran a series of experiments aimed to assess its performance. Results show that the MagoNode++ consumes only 2.8 µA in Low Power Mode with its WRx module in listening mode. While carrying on our research work on solutions trying to mitigate the energy problem, we also faced a challenging application context where the employment of WSNs is considered efficient and effective: structural health monitoring (SHM). SHM deals with the early detection of damages to civil and industrial structures and is emerging as a fundamental tool to improve the safety of these critical infrastructures. In this thesis we present two real world WSNs deployment dedicated to SHM. The first concerned the monitoring of the Rome B1 Underground construction site. The goal was to monitor the structural health of a tunnel connecting two stops. The second deployment concerned the monitoring of the structural health of buildings in earthquake-stricken areas. From the experience gained during these real world deployments, we designed the Modular Monitoring System (MMS). The MMS is a new low-power platform dedicated to SHM based on the MagoNode. We validated the effectiveness of the MMS low-power design performing energy measurements during data acquisition from actual transducers

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of “volunteer mappers”. Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protection

Water leakage mapping in concrete railway tunnels using LiDAR generated point clouds

Dissertation (MEng (Transportation Engineering)) University of Pretoria, 2021.Light detection and ranging (LiDAR) is a key non-destructive testing (NDT) method used in modern civil engineering inspections and commonly known for its ability to generate high-density coordinated point clouds of scanned environments. In addition to the coordinates of each point an intensity value, highly dependent on the backscattered energy of the laser beam, is recorded. This value has proven to vary largely for different material properties and surfaces. In this study properties such as surface colour, roughness and state of saturation are reviewed. Different coloured and concrete planar targets were scanned using a mobile LiDAR scanning system to investigate the effect distance, incidence angle and ambient lighting have on targets of differing properties. The study comprised controlled laboratory scans and field surveying of operational concrete railway tunnels. The aim of field tests was to automatically extract water leakage areas, visible on tunnel walls, based on the intensity information of points. Laboratory results showed that darker coloured targets resulted in a lower recorded intensity value and larger standard deviation of range. Black targets recorded the lowest intensities (0 - 4 units) with 50% higher standard deviations of range, on average, compared to all other coloured targets which recorded standard deviations of around 12 mm. The roughness of each coloured target showed to largely influence the recorded intensity, with smooth surfaces recording higher standard deviations of measurements. Concrete targets proved that a difference in roughness and saturation was detectable from intensity data. The biggest change was seen with saturated targets where a 70 to 80 % lower intensity value was recorded, on average, when compared to the same targets in their dry state. The difference in target roughness showed to have no effect on intensity when saturated. The laboratory data provided an important reference for the interpretation and filtering of field point clouds. Ambient lighting had no significant effect on all measurements for both the coloured and concrete targets. Field tests conducted on an operational concrete railway tunnel confirmed and demonstrated the ability to rapidly identify, extract and record areas of water leakage based on the intensity and spatial information of point cloud data. This is particularly useful as water ingress is known to degrade concrete, resulting in the earlier onset of corrosion, spalling and loss of strength. The mobile LiDAR scanning system used here proved capable of reducing survey time, which would allow for shorter interval revisits, while providing more quantitative information of the leakage areas. Long-term continuous monitoring of the internal structure of a tunnel will reduce the life cycle costs by removing the need for personnel to enter the tunnels for visual assessments and enable remedial work to be better planned by analysing a virtual 3D point cloud of the tunnel before stepping foot onto site.Transnet Freight RailChair in Railway EngineeringCivil EngineeringMEng (Transportation Engineering)Unrestricte

Towards self-powered wireless sensor networks

Ubiquitous computing aims at creating smart environments in which computational and communication capabilities permeate the word at all scales, improving the human experience and quality of life in a totally unobtrusive yet completely reliable manner. According to this vision, an huge variety of smart devices and products (e.g., wireless sensor nodes, mobile phones, cameras, sensors, home appliances and industrial machines) are interconnected to realize a network of distributed agents that continuously collect, process, share and transport information. The impact of such technologies in our everyday life is expected to be massive, as it will enable innovative applications that will profoundly change the world around us. Remotely monitoring the conditions of patients and elderly people inside hospitals and at home, preventing catastrophic failures of buildings and critical structures, realizing smart cities with sustainable management of traffic and automatic monitoring of pollution levels, early detecting earthquake and forest fires, monitoring water quality and detecting water leakages, preventing landslides and avalanches are just some examples of life-enhancing applications made possible by smart ubiquitous computing systems. To turn this vision into a reality, however, new raising challenges have to be addressed, overcoming the limits that currently prevent the pervasive deployment of smart devices that are long lasting, trusted, and fully autonomous. In particular, the most critical factor currently limiting the realization of ubiquitous computing is energy provisioning. In fact, embedded devices are typically powered by short-lived batteries that severely affect their lifespan and reliability, often requiring expensive and invasive maintenance. In this PhD thesis, we investigate the use of energy-harvesting techniques to overcome the energy bottleneck problem suffered by embedded devices, particularly focusing on Wireless Sensor Networks (WSNs), which are one of the key enablers of pervasive computing systems. Energy harvesting allows to use energy readily available from the environment (e.g., from solar light, wind, body movements, etc.) to significantly extend the typical lifetime of low-power devices, enabling ubiquitous computing systems that can last virtually forever. However, the design challenges posed both at the hardware and at the software levels by the design of energy-autonomous devices are many. This thesis addresses some of the most challenging problems of this emerging research area, such as devising mechanisms for energy prediction and management, improving the efficiency of the energy scavenging process, developing protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support. %, including the design of mechanisms for energy prediction and management, improving the efficiency of the energy harvesting process, the develop of protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support

Building the Hyperconnected Society- Internet of Things Research and Innovation Value Chains, Ecosystems and Markets

This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade

Autonomous Sensing Nodes for IoT Applications

The present doctoral thesis fits into the energy harvesting framework, presenting the development of low-power nodes compliant with the energy autonomy requirement, and sharing common technologies and architectures, but based on different energy sources and sensing mechanisms. The adopted approach is aimed at evaluating multiple aspects of the system in its entirety (i.e., the energy harvesting mechanism, the choice of the harvester, the study of the sensing process, the selection of the electronic devices for processing, acquisition and measurement, the electronic design, the microcontroller unit (MCU) programming techniques), accounting for very challenging constraints as the low amounts of harvested power (i.e., [μW, mW] range), the careful management of the available energy, the coexistence of sensing and radio transmitting features with ultra-low power requirements. Commercial sensors are mainly used to meet the cost-effectiveness and the large-scale reproducibility requirements, however also customized sensors for a specific application (soil moisture measurement), together with appropriate characterization and reading circuits, are also presented. Two different strategies have been pursued which led to the development of two types of sensor nodes, which are referred to as 'sensor tags' and 'self-sufficient sensor nodes'. The first term refers to completely passive sensor nodes without an on-board battery as storage element and which operate only in the presence of the energy source, provisioning energy from it. In this thesis, an RFID (Radio Frequency Identification) sensor tag for soil moisture monitoring powered by the impinging electromagnetic field is presented. The second term identifies sensor nodes equipped with a battery rechargeable through energy scavenging and working as a secondary reserve in case of absence of the primary energy source. In this thesis, quasi-real-time multi-purpose monitoring LoRaWAN nodes harvesting energy from thermoelectricity, diffused solar light, indoor white light, and artificial colored light are presented

Building the Hyperconnected Society- Internet of Things Research and Innovation Value Chains, Ecosystems and Markets

This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade