Implementation of an IoT Based Radar Sensor Network for Wastewater Management

Critical wastewater events such as sewer main blockages or overflows are often not detected until after the fact. These events can be costly, from both an environmental impact and monetary standpoint. A standalone, portable radar device allowing non-invasive benchmarking of sewer pumping station (SPS) pumps is presented. Further, by configuring and deploying a complete Low Power Wide Area Network (LPWAN), Shoalhaven Water (SW) now has the opportunity to create Internet of Things (IoT)-capable devices that offer freedom from the reliance on mobile network providers, whilst avoiding congestion on the existing Supervisory Control and Data Acquisition (SCADA) telemetry backbone. This network infrastructure allows for devices capable of real-time monitoring to alert of any system failures, providing an effective tool to proactively capture the current state of the sewer network between the much larger SPSs. This paper presents novel solutions to improve the current wastewater network management procedures employed by SW. This paper also offers a complete review of wastewater monitoring networks and is one of the first to offer robust testing of Long Range Wide Area Network (LoRaWAN) network capabilities in Australia. The paper also provides a comprehensive summary of the LoRa protocol and all its functions. It was found that a LPWAN, utilising the LoRaWAN protocol and deployed appropriately within a geographic area, can attain maximum transmission distances of 20 km within an urban environment and up to 35 km line of sight

Synchronous LoRa mesh network to monitor processes in underground infrastructure

Collecting precise real-time information on urban drainage system performance is essential to identify, predict, and manage critical loading situations, such as urban flash floods and sewer overflows. Although emerging low-power wireless communication techniques allow efficient data transfers with great above-ground performance, for underground or indoor applications in a large coverage range are difficult to achieve due to physical and topological limitations, particularly in dense urban areas. In this paper, we first discuss the range limitations of the LoRaWAN standard based on a systematic evaluation of a long-term operation of a sensor network monitoring in-sewer process dynamics. Analyses reveal an-on average-five-fold higher data packet loss for sub-surface nodes, which steadily grows with increasing distance to the gateway. Second, we present a novel LPWAN concept based on the LoRa technology that enhances transmission reliability, efficiency, and flexibility in range-critical situations through meshed multi-hop routing and ensures a precise time-synchronization through optional GPS or DCF77 long-wave time signaling. Third, we illustrate the usefulness of the newly developed concept by evaluating the radio transmission performance for two independent full-scale field tests. Test results show that the synchronous LoRa mesh network approach clearly outperforms the standard LoRaWAN technique with regard to the reliability of packet delivery when transmitting from range-critical locations. Hence, the approach is expected to generally ease data collection from difficult-to-access locations such as underground areas

Integration of a cellular Internet-of-Things transceiver into 6G test network and evaluation of its performance

Abstract. This thesis focuses on the integration and deployment of an aftermarket cellular IoT transceiver on a 6G/5G test network for the purpose of evaluating the feasibility of such device for monitoring the network performance. The cellular technology employed was NB-IoT paired with a Raspberry Pi device as the microprocessor that collects network telemetry and uses MQTT protocol to provide constant data feed. The system was first tested in a public cellular network through a local service provider and was successfully connected to the network, establishing TCP/IP connections, and allowing internet connectivity. To monitor network information and gathering basic telemetry data, a network monitoring utility was developed. It collected data such as network identifiers, module registration status, band/channel, signal strength and GPS position. This data was then published to a MQTT broker. The Adafruit IO platform served as the MQTT broker, providing an interface to visualize the collected data. Furthermore, the system was configured for and deployed on a 6G/5G test network successfully. The device functionality that was developed and tested in the public network remained intact, enabling continuous monitoring and analysis of network data. Through this study, valuable insights into the integration and deployment of cellular IoT transceivers into cellular networks that employ the latest IoT technology were gained. The findings highlight the feasibility of utilizing such a system for network monitoring and demonstrate the potential for IoT applications in cellular networks

Design and Implementation of a Pressure Monitoring System Based on IoT for Water Supply Networks

Increasing the efficiency of water supply networks is essential in arid and semi-arid regions to ensure the supply of drinking water to the inhabitants. The cost of renovating these systems is high. However, customized management models can facilitate the maintenance and rehabilitation of hydraulic infrastructures by optimizing the use of resources. The implementation of current Internet of Things (IoT) monitoring systems allows decisions to be based on objective data. In water supply systems, IoT helps to monitor the key elements to improve system efficiency. To implement IoT in a water distribution system requires sensors that are suitable for measuring the main hydraulic variables, a communication system that is adaptable to the water service companies and a friendly system for data analysis and visualization. A smart pressure monitoring and alert system was developed using low-cost hardware and open-source software. An Arduino family microcontroller transfers pressure gauge signals using Sigfox communication, a low-power wide-area network (LPWAN). The IoT ThingSpeak platform is used for data analysis and visualization. Additionally, the system can send alarms via SMS/email in real time using the If This, Then That (IFTTT) web service when anomalous pressure data are detected. The pressure monitoring system was successfully implemented in a real water distribution network in Spain. It was able to detect both breakdowns and leaks in real time

Long-range Radio for Underground Sensors in Geothermal Energy Systems

The paper presents the design of a temperature monitoring system in a very harsh environment, such as Shallow Geothermal Systems (SGS), where the information of underground temperature is necessary to assess the thermal potential of the soil, for maximizing the efficiency of the SGS. The challenge is to get information at different depths (sometimes up to - 100m), to transmit data wirelessly in rural areas where conventional wireless connections (e.g. WiFi, GSM) are not guaranteed and energy availability poses severe limits. Our design exploits a recent new modulation protocol developed for long-range transmission, at the minimum energy cost, and a two-tier hardware architecture for measuring underground temperature. Aggressive duty cycling permits to achieve lifetime of several years. Experimental results demonstrate the utility of such a system during the design and the operational activity of a SGS

A field-measurements-based LoRa network planning tool

Long range (LoRa) transmission technology enables energy-constrained devices such as the tiny sensor systems used in internet-of-things applications that are distributed over wide areas while still being able to establish appropriate connectivity. This has resulted in the development of an exponentially increasing number of different solutions and services based on LoRa, be they dedicated to the long-term monitoring of distributed plants and infrastructures or to human-centred applications such as safety-oriented sensor systems for use in the workplace. In dense LoRa networks, predicting the number of supported nodes in relation to their position and the propagation environment is essential for ensuring reliable and stable communication and minimising costs. In this paper, after comparing different path loss models based on a field measurement campaign for LoRa received signal strength indicator values within a university campus, two main modifications of the LoRa simulator tool were implemented. These were aimed at improving the accuracy of the prediction of the number of sustainable nodes in relation to the target data extraction rate set. The simulations based on field measurements demonstrated that through an improved path loss evaluation and the use of three gateways, the number of nodes could be increased theoretically from around 100 to around 6,000

Gestión inteligente de sistemas de distribución de agua

The United Nations predicts that the world's population in 2050 will reach 9.7 billion people. This exponential growth will mean an increase in the global demand for water available for human consumption. In addition, the advance of climate change is causing the occurrence of more frequent droughts, especially in arid and semi-arid areas. Indirectly, this means an increase in the costs associated with water transport and purification, as water must be drawn from sources that are increasingly distant from the points of consumption and the quality is getting worse. The traditional management of urban water supply is changing towards a more sustainable model aimed at an efficient use of resources (water, energy, labour) that not only reduces management costs but is also more environmentally friendly. This transformation is taking place due to the development of other transversal disciplines (cloud computing, communication systems, Big Data, electronics, etc.) applied to many fields of science, which applied to water management, can bring considerable benefits. Furthermore, to achieve intelligent management of a water supply network, it is necessary to rely on current tools that provide objective knowledge of the system. For example, geographic information systems (GIS) together with hydraulic models serve as a georeferenced database where the behaviour of any hydraulic network in different scenarios can be simulated. The Internet of Things (IoT) allows the connection of a network of sensors to know the main hydraulic variables at any time, providing key information for hydraulic models to faithfully reproduce the behaviour of modelled systems in real time. Digitalisation itself favours the use of information and communication technologies (ICT) to convert traditional management into smart management. For these reasons, new studies are needed to assess the potential and applicability of these new tools. This thesis is organised in 6 chapters focused on the development and application of a decision support system that allow the manager of a water supply network to make decisions based on data recorded on real-time. All the tools developed throughout this thesis have been tested in a real water supply network located in the south of Spain, managed by the Provincial Water Company of Cordoba (EMPROACSA). Chapter 1 shows the trajectory of urban supply management: explaining the starting point and where it is expected to achieve. Then, Chapter 2 describes the main objective and the specific objectives of this thesis, as well as the structure of this document. Chapter 3 presents a methodology that serves as a basis for starting the digitisation process in water supply networks. The system developed is based on three pillars: the geographic information system, the hydraulic model, and the application for mobile devices. The geographic information system provides a georeferenced database of the infrastructures that compose the hydraulic network; the hydraulic model simulates the response of the network to different operation scenarios; and finally, the mobile application facilitates the feedback of the system to keep it always up to date with changes in the systems. One of the distinguishing features of this work is the use of free software (Qgis, Epanet and Google My Maps) in all stages, which fosters digitisation in supply companies with a low budget. Chapter 4 develops an early warning system based on water pressure monitoring. The communication node developed ad-hoc for this work, sends water pressure data to the cloud, where users can visualise them with a device with an internet connection. Among its advantages are its low cost, it allows the use of different communication systems and has a high autonomy powered by batteries, which makes it well adapted to supply systems. The proposed monitoring system detects failures in the network due to pressure drops, alerting managers of the affected zone. Chapter 5 explains the decision support tool developed to deal with failures in water transmission networks. The web platform that supports this tool is divided into 3 independent modules: fault detection, alerts, and fault repair. The first module is responsible for detecting, geolocating and classifying faults in the hydraulic network using the information recorded in real time by the pressure monitoring system described in the previous chapter. The second module is responsible for sending alerts selectively to the workers in the area of the failure. Finally, the third module estimates, applying the hydraulic model, the maximum time that the manager has to fix failures, avoiding supply cuts using the water stored in regulation tanks when the failure occurs. The fault detection and classification module has demonstrated a 95% accuracy when applied to a real case. Chapter 6 contains the general conclusions of the thesis, as well as possible lines of future work. In summarise, water management is experiencing a paradigm shift. This transformation requires sufficiently mature technologies to ensure good results. Therefore, studies are needed that not only advance towards smart management, but also evaluate the tools available now and their integration into the current management model. This thesis presents a decision support system applied to supply networks, which help managers to make decisions based on objective information, not on intuition or experience. The use of open-source software and hardware in all the developments of this thesis must be emphasised. This specific feature allows the adoption of the methodologies proposed by water companies, regardless of size or financial resources, enabling the whole system or only part of it to be adapted to the operation of the company.Las Naciones Unidas prevén que la población mundial en 2050 alcanzará los 9.700 millones de personas. Este crecimiento exponencial supondrá un aumento de la demanda global de agua disponible para el consumo humano. Además, el avance del cambio climático está provocando la aparición de sequías más frecuentes, especialmente en las zonas áridas y semiáridas. Indirectamente, esto supone un aumento de los costes asociados al transporte y la depuración del agua, ya que hay que extraerla de fuentes cada vez más alejadas de los puntos de consumo y la calidad es cada vez peor. La gestión tradicional del abastecimiento de agua en las ciudades está cambiando hacia un modelo más sostenible orientado a un uso eficiente de los recursos (agua, energía, mano de obra) que además de reducir los costes de gestión, es más respetuoso con el medio ambiente. Esta transformación se está produciendo gracias al desarrollo de otras disciplinas transversales (computación en la nube, sistemas de comunicación, Big Data, electrónica, etc.) aplicadas a diversos campos de la ciencia, que aplicadas a la gestión del agua, pueden aportar considerables beneficios. Además, para conseguir una gestión inteligente de una red de abastecimiento de agua, es necesario apoyarse en herramientas actuales que proporcionen un conocimiento objetivo del sistema. Por ejemplo, los sistemas de información geográfica (SIG) junto con los modelos hidráulicos sirven como base de datos georreferenciada donde se puede simular el comportamiento de cualquier red hidráulica en diferentes escenarios. El Internet de las Cosas (IoT) permite la conexión de una red de sensores para conocer las principales variables hidráulicas en cada momento, aportando información clave para que los modelos hidráulicos reproduzcan fielmente el comportamiento de los sistemas modelizados en tiempo real. La propia digitalización favorece el uso de las tecnologías de la información y la comunicación (TIC) para convertir la gestión tradicional en una gestión inteligente. Por estas razones, son necesarios nuevos estudios para evaluar el potencial y la aplicabilidad de estas nuevas herramientas. Esta tesis se organiza en 6 capítulos centrados en el desarrollo y aplicación de un sistema de apoyo a la decisión que permita al gestor de una red de abastecimiento de agua tomar decisiones basadas en datos registrados en tiempo real. Todas las herramientas desarrolladas a lo largo de esta tesis han sido probadas en una red real de abastecimiento de agua situada en el sur de España, gestionada por la Empresa Provincial de Aguas de Córdoba (EMPROACSA). El capítulo 1 muestra la trayectoria de la gestión del abastecimiento urbano: explicando el punto de partida y hacia dónde se espera llegar. A continuación, el capítulo 2 describe el objetivo principal y los objetivos específicos de esta tesis, así como la estructura de este documento. El capítulo 3 presenta una metodología que sirve de base para iniciar el proceso de digitalización de las redes de abastecimiento de agua. El sistema desarrollado se basa en tres pilares: el sistema de información geográfica, el modelo hidráulico y la aplicación para dispositivos móviles. El sistema de información geográfica proporciona una base de datos georreferenciada de las infraestructuras que componen la red hidráulica; el modelo hidráulico simula la respuesta de la red ante diferentes escenarios de operación; y, por último, la aplicación móvil facilita la retroalimentación del sistema para mantenerlo siempre actualizado con los cambios en los sistemas. Uno de los rasgos distintivos de este trabajo es el uso de software libre (Qgis, Epanet y Google My Maps) en todas las etapas, lo que favorece la digitalización en empresas de abastecimiento con bajo presupuesto. El capítulo 4 desarrolla un sistema de alerta temprana basado en la monitorización de la presión del agua. El nodo de comunicación desarrollado ad-hoc para este trabajo, envía los datos de la presión del agua a la nube, donde los usuarios pueden visualizarlos con un dispositivo con conexión a internet. Entre sus ventajas están su bajo coste, permite el uso de diferentes sistemas de comunicación y tiene una gran autonomía alimentada por baterías, lo que hace que se adapte bien a los sistemas de abastecimiento. El sistema de monitorización propuesto detecta fallos en la red por caídas de presión, alertando a los gestores de la zona afectada. El capítulo 5 explica la herramienta de apoyo a la toma de decisiones desarrollada para hacer frente a las averías en las redes de abastecimiento en alta. La plataforma web, que soporta esta herramienta, se divide en 3 módulos independientes: detección de averías, alertas y reparación de averías. El primer módulo se encarga de detectar, geolocalizar y clasificar las averías en la red hidráulica a partir de la información registrada en tiempo real por el sistema de monitorización de presiones descrito en el capítulo anterior. El segundo módulo se encarga de enviar alertas de forma selectiva a los trabajadores de la zona de la avería. Por último, el tercer módulo estima, aplicando el modelo hidráulico, el tiempo máximo del que dispone el gestor para solucionar las averías, evitando los cortes de suministro con el agua almacenada en los depósitos de regulación cuando se produce la avería. El módulo de detección y clasificación de averías ha demostrado una precisión del 95% cuando se aplica a un caso real. El capítulo 6 contiene las conclusiones generales de la tesis, así como posibles líneas de trabajo futuras. En resumen, la gestión del agua está experimentando un cambio de paradigma. Esta transformación requiere tecnologías suficientemente maduras para garantizar buenos resultados. Por ello, son necesarios estudios que no sólo avancen hacia una gestión inteligente, sino que evalúen las herramientas disponibles en la actualidad y su integración en el modelo de gestión actual. Esta tesis presenta un sistema de apoyo a la decisión aplicado a las redes de suministro de agua, que ayuda a los gestores a tomar decisiones basadas en información objetiva y no en la intuición o la experiencia. Cabe destacar el uso de software y hardware de código abierto en todos los desarrollos de esta tesis. Esta particularidad permite la adopción de las metodologías propuestas por las empresas de agua, independientemente de su tamaño o recursos financieros, permitiendo adaptar todo el sistema o sólo una parte de él al funcionamiento de la empresa

Implementación de tecnologías RFID e IoT inalámbricas en el Modelado de información de construcción (BIM)

ABSTRACT: The integration and installation of innovative Radio Frequency Identification (RFID) technologies in combination with wireless Internet of Things (IoT) technologies in Building Information Modelling (BIM), assigned building elements, can create connectivity between the physical- and the virtual world. Beyond the identification of physical objects, further information can be connected, which can be made available to different user groups during the entire life cycle of the building structure. This provides a high level of transparency, in that by scanning the tagged building elements, complete associated information can be accessed and presented to users via applications, in visual and audio form. One use of an RFID and BIM-supported electronic guidance system, namely for the visually impaired, has already been investigated in my bachelor thesis at the University of Applied Sciences (Technische Hochschule Mittelhessen, THM). This Master’s Thesis focuses on the implementation of passive RFID technology into BIM models in combining them with open-source software applications. BIM represents the digital twin of building models in the digital world and can be linked to physical structures (buildings, roads, sewer systems and such others) and building materials (e.g. textiles, mineral and plastic floor coverings, concrete components) by integrating RFID tags. Connecting the parametric BIM models with the physical building elements by using RFID and wireless IoT technologies in a multi-platform application enables the BIM building models to be actively used throughout the life cycle of a building, not only by the facility management, but also by the public for various use cases. During the literature review, suitable software and hardware components were selected, and a prototype multi-platform application for a navigation and positioning system was developed as proof of concept for the Industry Foundation Classes (IFC) file. (See Demo Version at https://opennavibim.herokuapp.com/ ). The challenge was to read the RFID tags in different installation scenarios. Depending on the installation situations (under, over or in the material), various requirements were specified for RFID tags and readers (RFID, handhold personal digital assistant “PDA”). In this field, further hardware developments are necessary.RESUMEN: Mediante la integración e instalación de la innovadora tecnología de identificación por radiofrecuencia (RFID, Radio Frequency Identification) en el modelado digital de información de construcción (BIM, Building Information Modelling), con la interconexión inalámbrica del internet de las cosas (IoT, Internet of Things), es posible crear una conectividad entre el mundo físico y el virtual. Más allá de la mera identificación de objetos existentes, esta conectividad permite incorporar información adicional, que puede ponerse en disposición de los diferentes grupos de usuarios que intervienen durante el ciclo completo de vida de la estructura de la edificación. Se consigue un alto de nivel de transparencia en ese traspaso de información, accesible por medio del escaneado de los elementos etiquetados en la edificación, al tener una completa información asociada que es presentada a los usuarios vía aplicaciones en formato visual o de audio. Una investigación en la aplicación de tecnología RFID basada en BIM para un sistema de navegación electrónica, destinada a personas con discapacidad visual, ha sido desarrollada en mi trabajo fin de grado en la Universidad de Ciencias Aplicadas de Mittelhessen (THM). El presente Trabajo Fin de Master se centra en la implementación de tecnología RFID pasiva en modelos BIM combinados con aplicaciones de software libre. El modelo BIM representa el gemelo digital de los elementos de construcción en el mundo virtual, permitiendo establecer una relación del modelo con estructuras físicas (edificios, carreteras o sistemas de alcantarillado, entre otros) y materiales de construcción (por ejemplo, textiles, cubiertas de suelo minerales o plásticas, componentes de hormigón, …) por medio de la integración de etiquetas RFID. La conexión de los modelos paramétricos BIM con los elementos físicos del edificio, mediante el uso de tecnologías RFID e IoT inalámbricas en una aplicación multiplataforma, permite que los modelos de construcción BIM se utilicen activamente a lo largo del ciclo de vida de un edificio, no solo por la gestión de las instalaciones, sino también por el público para diversos casos de uso. Durante la revisión bibliográfica, se seleccionaron los componentes de software y hardware adecuados, y se desarrolló un prototipo de aplicación multiplataforma para un sistema de navegación y posicionamiento como prueba de viabilidad del concepto del modelo Industry Foundation Classes (IFC). (Véase la versión de demostración en https://opennavibim.herokuapp.com/ ). La lectura de las etiquetas RFID en diferentes en diferentes situaciones de instalación presenta un desafío, dependiendo de la instalación (debajo, encima o en el material) los requisitos impuestos a las etiquetas y lectores RFID son diferentes. Por lo tanto, es necesario seguir desarrollando el hardware en este ámbito.Máster en Ingeniería de Caminos, Canales y Puertos (Plan 2020

A learning model for battery lifetime prediction of LoRa sensors in additive manufacturing

Today, an innovative leap for wireless sensor networks, leading to the realization of novel and intelligent industrial measurement systems, is represented by the requirements arising from the Industry 4.0 and Industrial Internet of Things (IIoT) paradigms. In fact, unprecedented challenges to measurement capabilities are being faced, with the ever-increasing need to collect reliable yet accurate data from mobile, battery-powered nodes over potentially large areas. Therefore, optimizing energy consumption and predicting battery life are key issues that need to be accurately addressed in such IoT-based measurement systems. This is the case for the additive manufacturing application considered in this work, where smart battery-powered sensors embedded in manufactured artifacts need to reliably transmit their measured data to better control production and final use, despite being physically inaccessible. A Low Power Wide Area Network (LPWAN), and in particular LoRaWAN (Long Range WAN), represents a promising solution to ensure sensor connectivity in the aforementioned scenario, being optimized to minimize energy consumption while guaranteeing long-range operation and low-cost deployment. In the presented application, LoRa equipped sensors are embedded in artifacts to monitor a set of meaningful parameters throughout their lifetime. In this context, once the sensors are embedded, they are inaccessible, and their only power source is the originally installed battery. Therefore, in this paper, the battery lifetime prediction and estimation problems are thoroughly investigated. For this purpose, an innovative model based on an Artificial Neural Network (ANN) is proposed, developed starting from the discharge curve of lithium-thionyl chloride batteries used in the additive manufacturing application. The results of experimental campaigns carried out on real sensors were compared with those of the model and used to tune it appropriately. The results obtained are encouraging and pave the way for interesting future developments