Groundwater data management by water service providers in peri-urban areas of Lusaka

Groundwater management by water service providers in Lusaka, Zambia, includes borehole siting, drilling and on-going monitoring. Semi-structured interviews were conducted with Lusaka Water and Sewerage Company (LWSC) and devolved Water Trust managers, in order to assess their needs and collect their suggestions to improve data management. The research found that both the Water Trusts and LWSC lacked the capacity to fully utilize hydrogeological information. Prior to the research, none of the ten Water Trusts collected water level data. Four have started to collect data recently and another four have plans to, and they would like to share this data more widely

A review of the internet of floods : near real-time detection of a flood event and its impact

Worldwide, flood events frequently have a dramatic impact on urban societies. Time is key during a flood event in order to evacuate vulnerable people at risk, minimize the socio-economic, ecologic and cultural impact of the event and restore a society from this hazard as quickly as possible. Therefore, detecting a flood in near real-time and assessing the risks relating to these flood events on the fly is of great importance. Therefore, there is a need to search for the optimal way to collect data in order to detect floods in real time. Internet of Things (IoT) is the ideal method to bring together data of sensing equipment or identifying tools with networking and processing capabilities, allow them to communicate with one another and with other devices and services over the Internet to accomplish the detection of floods in near real-time. The main objective of this paper is to report on the current state of research on the IoT in the domain of flood detection. Current trends in IoT are identified, and academic literature is examined. The integration of IoT would greatly enhance disaster management and, therefore, will be of greater importance into the future

Use cases for Internet of Things (IoT) in the construction sector: Lessons from leading industries

This study conducts a cross-sectoral comparative analysis of academic and industry literature to determine the use cases of the internet of things (IoT). Specifically, the research seeks to explore digital applications (e.g., building information modeling (BIM), radio frequency identification (RFID)) within the construction supply chain – a sector berated for its lack of innovation. An interpretivist epistemological lens provides the overarching methodological approach adopted in which the literature constitutes units of analysis. Ensuing discussion defines the architecture of proposed real-life scenarios and provides a description of an IoT layout for these scenarios. In practical terms, the study contributes to the field by raising awareness of potential use cases of IoT for construction practitioners as ‘proof of concepts’. For researchers, the findings provide a blueprint template layout of suggested use cases to be tested in future research studies hence, offering a sound basis and a fertile ground for advancing the body of knowledge on this topic area

Franklin Township Municipal Broadband and Wireless Network

Franklin Township is a municipality in Somerset County, New Jersey covering an area of approximately 46.15 square miles and a population of 62,300 as of the 2010 Census. The town relies on a cellular provider to provide data connections for computers in municipal vehicles such as police cars, public works vehicles, fire inspection trucks, building inspectors and other departments. Additionally, the municipality pays for connections for security cameras at remote facilities and for smart garbage can monitoring throughout the town. These services are costly for the municipality and create a dependency on service providers for access to information needed by municipal employees. This paper explores the current solution in place for data connections and a proposed solution of implementing a municipal broadband network. It lists disadvantages and advantages of each solution. It also explores the failures and successes of similar projects. The paper covers the implementation process that would need to be followed. Finally, it examines two potential wireless technologies which could be implemented for the wireless connection. The goal is to show the potential benefits of Franklin Township implementing its own network and the potential benefits through long term cost savings and gathering or access to data

Overløpskontroll i avløpsnett med forskjellige modelleringsteknikker og internet of things

Increased urbanization and extreme rainfall events are causing more frequent instances of sewer overflow, leading to the pollution of water resources and negative environmental, health, and fiscal impacts. At the same time, the treatment capacity of wastewater treatment plants is seriously affected. The main aim of this Ph.D. thesis is to use the Internet of Things and various modeling techniques to investigate the use of real-time control on existing sewer systems to mitigate overflow. The role of the Internet of Things is to provide continuous monitoring and real-time control of sewer systems. Data collected by the Internet of Things are also useful for model development and calibration. Models are useful for various purposes in real-time control, and they can be distinguished as those suitable for simulation and those suitable for prediction. Models that are suitable for a simulation, which describes the important phenomena of a system in a deterministic way, are useful for developing and analyzing different control strategies. Meanwhile, models suitable for prediction are usually employed to predict future system states. They use measurement information about the system and must have a high computational speed. To demonstrate how real-time control can be used to manage sewer systems, a case study was conducted for this thesis in Drammen, Norway. In this study, a hydraulic model was used as a model suitable for simulation to test the feasibility of different control strategies. Considering the recent advances in artificial intelligence and the large amount of data collected through the Internet of Things, the study also explored the possibility of using artificial intelligence as a model suitable for prediction. A summary of the results of this work is presented through five papers. Paper I demonstrates that one mainstream artificial intelligence technique, long short-term memory, can precisely predict the time series data from the Internet of Things. Indeed, the Internet of Things and long short-term memory can be powerful tools for sewer system managers or engineers, who can take advantage of real-time data and predictions to improve decision-making. In Paper II, a hydraulic model and artificial intelligence are used to investigate an optimal in-line storage control strategy that uses the temporal storage volumes in pipes to reduce overflow. Simulation results indicate that during heavy rainfall events, the response behavior of the sewer system differs with respect to location. Overflows at a wastewater treatment plant under different control scenarios were simulated and compared. The results from the hydraulic model show that overflows were reduced dramatically through the intentional control of pipes with in-line storage capacity. To determine available in-line storage capacity, recurrent neural networks were employed to predict the upcoming flow coming into the pipes that were to be controlled. Paper III and Paper IV describe a novel inter-catchment wastewater transfer solution. The inter-catchment wastewater transfer method aims at redistributing spatially mismatched sewer flows by transferring wastewater from a wastewater treatment plant to its neighboring catchment. In Paper III, the hydraulic behaviors of the sewer system under different control scenarios are assessed using the hydraulic model. Based on the simulations, inter-catchment wastewater transfer could efficiently reduce total overflow from a sewer system and wastewater treatment plant. Artificial intelligence was used to predict inflow to the wastewater treatment plant to improve inter-catchment wastewater transfer functioning. The results from Paper IV indicate that inter-catchment wastewater transfer might result in an extra burden for a pump station. To enhance the operation of the pump station, long short-term memory was employed to provide multi-step-ahead water level predictions. Paper V proposes a DeepCSO model based on large and high-resolution sensors and multi-task learning techniques. Experiments demonstrated that the multi-task approach is generally better than single-task approaches. Furthermore, the gated recurrent unit and long short-term memory-based multi-task learning models are especially suitable for capturing the temporal and spatial evolution of combined sewer overflow events and are superior to other methods. The DeepCSO model could help guide the real-time operation of sewer systems at a citywide level.publishedVersio

Urban hydroinformatics: past, present and future

This is the author accepted manuscriptHydroinformatics, as an interdisciplinary domain that blurs boundaries between water science, data science and computer science, is constantly evolving and reinventing itself. At the heart of this evolution, lies a continuous process of critical (self) appraisal of the discipline’s past, present and potential for further evolution, that creates a positive feedback loop between legacy, reality and aspirations. The power of this process is attested by the successful story of hydroinformatics thus far, which has arguably been able to mobilize wide ranging research and development and get the water sector more in tune with the digital revolution of the past 30 years. In this context, this paper attempts to trace the evolution of the discipline, from its computational hydraulics origins to its present focus on the complete socio-technical system, by providing at the same time, a functional framework to improve the understanding and highlight the links between different strands of the state-of-art hydroinformatic research and innovation. Building on this state-of-art landscape, the paper then attempts to provide an overview of key developments that are coming up, on the discipline’s horizon, focusing on developments relevant to urban water management, while at the same time, highlighting important legal, ethical and technical challenges that need to be addressed to ensure that the brightest aspects of this potential future are realized. Despite obvious limitations imposed by a single paper’s ability to report on such a diverse and dynamic field, it is hoped that this work contributes to a better understanding of both the current state of hydroinformatics and to a shared vision on the most exciting prospects for the future evolution of the discipline and the water sector it serves

smart sustainable islands vs smart sustainable cities

This paper has several aims: a) the presentation of a critical analysis of the terms "smart sustainable cities" and "smart sustainable islands" b) the presentation of a number of principles towards to the development methodological framework of concepts and actions, in a form of a manual and actions guide, for the smartification and sustainability of islands. This kind of master plan is divided in thematic sectors (key factors) which concern the insular municipalities c) the creation of an island's smartification and sustainability index d) the first steps towards the creation of a portal for the presentation of our smartification actions manual, together with relative resources, smart applications examples, and, in the near future the first results of our index application in a number of Greek islands and e) the presentation of some proposals of possible actions towards their sustainable development and smartification for the municipalities - islands of Paros and Antiparos in Greece, as case studies

Node assembly for waste level measurement: embrace the smart city

Municipal Solid Waste Management Systems (MSWMS) worldwide are currently facing pressure due to the rapid growth of the population in cities. One of the biggest challenges in this system is the inefficient expenditure of time and fuel in waste collection. In this regard, cities/- municipalities in charge of MSWMS could take advantage of information and communication technologies to improve the overall quality of their infrastructure. One particular strategy that has been explored and is showing interesting results is using a Wireless Sensors Network (WSN) to monitor waste levels in real-time and help decision-making regarding the need for collection. The WSN is equipped with sensing devices that should be carefully chosen considering the real scenario in which they will work. Therefore, in this work, three sets of sensors were studied to evaluate which is the best to be used in the future WSN assembled in Bragança, Portugal. Sets tested were HC-SR04 (S1), HC-SR04 + DHT11 (S2), and US-100 (S3). Tests considered for this work were air temperature and several distances. In the first, the performance of each set to measure a fixed target (metal and plastic box) was evaluated under different temperatures (1.7 - 37 ℃). From these results, two best sets were further used to assess distance measurement at a fixed temperature. This test revealed low absolute errors measuring the distances of interest in this work, ranging from 0.18% to 1.27%.This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/05757/2020, UIDB/00690/2020, LA/P/0045/2020, UIDB/50020/2020, and UIDP/50020/2020. Adriano Silva was supported by FCT-MIT Portugal PhD grant SFRH/BD/151346/2021, and Thadeu Brito was supported by FCT PhD grant SFRH/BD/08598 /2020. Jose L. Diaz de Tuesta acknowledges the finantial support through the program of Atraccion de Talento of Atraccion al Talento of the Comunidad de Madrid (Spain) for the individual research grant 2020-T2/AMB-19836.info:eu-repo/semantics/acceptedVersio