How do Cyber-Risks Vary Across Smart City Technologies?

The water leakage detection on pipelines has improved with the advent of remote environmental wireless sensor network (WSN) and Internet of Things (IoT) technologies over the past few years. Leakage detection in underground water pipelines involves algorithms to predict leakage and estimate its location, in which accuracy depends significantly on the distance between the water meters stationed at district water stations. This research proposes to deploy smart wireless water meter nodes at intermediate distances to enhance the accuracy sharply. This requires water meters to operate autonomously, harvesting energy from surroundings, to be self-sufficient. This research proposes a heterogeneous communication with smart water meters that focuses on transferring data and reducing energy consumption by establishing communication with wireless sensor nodes for smart water meter applications.

This article deals with the use of machine learning to detect sudden water leakage. A smart water meter, which enables monitoring the water consumption of the observed object, is used as the source of input data. Based on these data and their analysis, a symbolic regression, which must know not only the input parameters but also the structure of the model, was finally used to build the model. After finding a suitable function and standard deviation from the model, it is possible to set the required sensitivity and thereby detect anomalous states of water consumption in monitored time windows. Since the smart water meter also has a ball valve, if a sudden water leakage is detected, the water meter can autonomously close the main supply and thus avoid extensive damage.

This paper reviews on some of the recent methodologies of intelligent water metering system used in the smart water meter (SWM) to overcome the problem of water crises. The conservation of water is one of the vital problems in worldwide that needs proper attention. Due to the unpredictable rise in water consumption, the entire fresh water sources are diminishing day by day. At present, there is a gradual advancement in the technologies used for the purpose of monitoring of the proper utilization of water sources. This resulted into better functioning and solving various water loss issues in broad spectrum. The different frameworks available for SWM including the advanced communication protocols are also being discussed in this paper that could help for further advancement in the SWM.KeywordsSmart water meter (SWM)FrameworksProtocolsIntelligent water metering system

Smart water meters at household connections are being installed in large numbers throughout the world due to the benefits they are expected to bring to the water utilities and water consumers. Smart metering provides high‐resolution readings and promises benefits to the water utilities, such as demand forecasting, regulating time‐of‐use watering, and making intelligent operation and planning decisions. For the consumers, smart metering promises improved billing and demand reduction by providing detailed and timely information about their water use and early notification of possible water leaks in their premises. However, the fine‐grained information collected by smart meters raises growing concerns of privacy invasion due to personal behavior exposure (private activity, daily routine, etc.). Nevertheless, there is no readily available technology for protecting water consumers from revealing their in‐home private activities. Thus, a viable argument in favor of smart metering technologies will not be possible without proactively accounting for the associated privacy challenges. Here, we present a practical technology coupling a dedicated apparatus with a control model for increasing personal privacy. We quantify the level of privacy achieved using information‐theoretic criterion and an empirically based occupancy detection method between the smart meter readings and actual water use. Furthermore, we evaluate and compare privacy protection using the best effort approach previously developed for masking activities revealed from smart electricity meters. The main results reveal that simple control actions can disguise personal behavior patterns and, thus, hedge against privacy breach in smart water meters. Furthermore, we quantify the trade‐off between the size of the apparatus and the level of privacy protection it provides. Our results demonstrate how “privacy friendly” smart water metering technology could be implemented in real‐life systems and reduce the privacy concerns of water consumers.

Machine learning applications for anomaly detection in Smart Water Metering Networks: A systematic review

There is an increasing trend among local governments in the United States and elsewhere in the world to adopt smart cities technologies (SCT), but the question remains: Do these technologies contribute to government revenue performance? Drawing on the digital-era governance (DEG) literature for theoretical context, this article investigates the effects of commitment to, engagement with, and barriers encountered with SCT on government revenue performance. The effects are examined using performance data obtained from the 2016 International City/County Management Association (ICMA) Smart Cities Survey and the U.S. Census Bureau. The ordinary least squares (OLS) regression results provide empirical support to the assertion that higher engagement with SCT contributes to government revenue performance. Overall, we find that SCT contribute to local retail trade revenue collection efforts and health care and social assistance revenue of establishments in a local government area. The article offers policy implications on how local governments can improve their revenue performance using SCT that contribute to important public values such as timeliness, productivity, efficiency, effectiveness, and government competitiveness, as well as benevolence and human dignity.

An exploration of smart city approaches by international ICT firms

<p><b>Local governments are innovatively applying smart city technology to resolve challenges in their jurisdictions. These challenges commonly relate to environmental sustainability, infrastructure, and transportation, and result in novel discourses within local government strategies and operations, such as Smart Environment, Smart Infrastructure, and Smart Mobility. Driven by the success of these discourses, local governments seek further solutions through converging the smart city technology with other disciplines. The next likely convergence is with the heritage discipline, subsequently producing the Smart Heritage discourse. Academic literature records that Smart Heritage is an emergent yet unformed discourse that is on the verge of application within local government. Smart Heritage presents opportunities to converge historical narratives with the automated and autonomous capabilities of smart technology. However, due to its novelty, the local government sector has no guidance on delivering Smart Heritage within strategies and operations. Therefore, this thesis comprehensively explores and defines the Smart Heritage discourse and addresses Smart Heritage's delivery within local government strategies and operations.</b></p> <p>The original contributions to knowledge in this thesis are the first thorough definition of Smart Heritage in academic literature and the production of Smart Heritage Principles, which direct the delivery of Smart Heritage within local government. This thesis firstly defines Smart Heritage through an investigation into the nascent patchwork of academic literature at the intersection of the smart city and heritage disciplines. This definition establishes the discursive framework for the subsequent inquiry into how to deliver Smart Heritage in local government organisations. In this inquiry, the researcher conducts three case studies on local governments in Australia: Broken Hill City Council, the City of Melbourne, and the City of Newcastle. In each case study, the researcher analyses strategic smart city and heritage documents and then interviews their smart city and heritage advisors regarding strategic and operational convergences between the disciplines. The researcher then synthesises the resulting data into cross-case key considerations that contextualise a base understanding of how local governments deliver Smart Heritage. Using this understanding, the researcher conducts a second round of interviews and synthesis that, in turn, produces the refined Smart Heritage Principles. The researcher validates the principles’ relevancy and applicability through an additional case study with Wellington City Council in New Zealand.</p> <p>The research finds that Smart Heritage in the academic literature is nascent yet organically forming around a shared discourse between the smart city and heritage disciplines. As a result, there are numerous understandings of Smart Heritage. Nevertheless, these understandings agree that Smart Heritage convergences historical contextual narratives with automatic and autonomous technologies and advances from the passive Digital Heritage discourse. The case studies find that there is a foundation for Smart Heritage within local government through strategic documents that share similar focuses and advisors who seek multi-disciplinary convergences. However, the disciplines’ overlapping is not explicitly recognised in strategic documents and operational models, leading to inadequate financial and staff resourcing of Smart Heritage and inefficient cross-disciplinary initiatives in local government. The research identifies four thematic key considerations that address delivering Smart Heritage within local government; recognition, delivery, resourcing, and innovation; and proposes four Smart Heritage Principles for local governments to follow in order to deliver the discourse. The researcher presents the principles in an industry-ready document at the end of the thesis.</p> <p>The implications of this research are the increased visibility of Smart Heritage as an academic discourse and support for the delivery of Smart Heritage within local government strategies and operations. Smart Heritage becomes more visible as this research solidifies then illuminates a discursive pathway that researchers can engage with. Importantly, this research presents evidence that Smart Heritage is extant within academic literature and local governments, supporting its position as a constructive academic and practical discourse. The Smart Heritage Principles support the delivery of Smart Heritage within local government strategies and operations through the applied guidance they offer the organisations. As the industry-ready document is the first publication with this focus, the influence on the delivery of Smart Heritage is significant. The researcher aspires to share the Smart Heritage Principles document beyond this research context through its distribution to other councils globally.</p>

Water monitoring in households provides occupants and utilities with key information to support water conservation and efficiency in the residential sector. High costs, intrusiveness, and practical complexity limit appliance-level monitoring via sub-meters on every water-consuming end use in households. Non-intrusive machine learning methods have emerged as promising techniques to analyze observed data collected by a single meter at the inlet of the house and estimate the disaggregated contribution of each water end use. While fine temporal resolution data allow for more accurate end-use disaggregation, there is an inevitable increase in the amount of data that needs to be stored and analyzed. To explore this tradeoff and advance previous studies based on synthetic data, we first collected 1 s resolution indoor water use data from a residential single-point smart water metering system installed at a four-person household, as well as ground-truth end-use labels based on a water diary recorded over a 4-week study period. Second, we trained a supervised machine learning model (random forest classifier) to classify six water end-use categories across different temporal resolutions and two different model calibration scenarios. Finally, we evaluated the results based on three different performance metrics (micro, weighted, and macro F1 scores). Our findings show that data collected at 1- to 5-s intervals allow for better end-use classification (weighted F-score higher than 0.85), particularly for toilet events; however, certain water end uses (e.g., shower and washing machine events) can still be predicted with acceptable accuracy even at coarser resolutions, up to 1 min, provided that these end-use categories are well represented in the training dataset. Overall, our study provides insights for further water sustainability research and widespread deployment of smart water meters.

Smart meters for enhanced water supply network modelling and infrastructure planning

Smart Water Meters (SWM) hold significant potential to mitigate water scarcity challenges in tourism-intensive destinations, yet their effectiveness in non-residential contexts remains underexplored. This study evaluates the impact of digital metering and feedback mechanisms on water consumption within tourism accommodations, utilising a geolocated panel dataset encompassing 213 high water-consuming establishments in San Bartolomé de Tirajana (Canary Islands). As a leading year-round destination, this region faces operational constraints that complicate conservation initiatives. Our comprehensive dataset integrates water network technical characteristics, tourism demand and supply variables, and climate factors across sub-municipal tourism zones to account for diverse guest profiles and management practices. Employing a random-effects regression model, we identify key determinants of water usage and uncover distinct consumption patterns between hotels and apartment complexes. The results reveal that while SWM installation significantly improves consumption tracking and enables early leak detection—primarily benefiting utilities—access to frequent digital feedback via web platforms correlates with increased water use. These findings challenge the assumption that digitalisation alone ensures efficiency, emphasising the importance of behavioural, organisational, and financial strategies while offering actionable insights for policymakers, utilities, and tourism operators to optimise digital engagement and adapt water governance.

This paper aims to explore the most important disruptive technologies in the development of the smart city. Every smart city is a dynamic and complex system that attracts an increasing number of people in search of the benefits of urbanisation. According to the United Nations, 68% of the world population will be living in cities by 2050. This creates challenges related to limited resources and infrastructure (energy, water, transportation system, etc.). To solve these problems, new and emerging technologies are created. Internet of Things, big data, blockchain, artificial intelligence, data analytics, and machine and cognitive learning are just a few examples. They generate changes in key sectors such as health, energy, transportation, education, public safety, etc. Based on a comprehensive literature review, we identified the main disruptive technologies in smart cities. Applications that integrate these technologies help cities to be smarter and offer better living conditions and easier access to products and services for residents. Disruptive technologies are generally considered key drivers in smart city progress. This paper presents these disruptive technologies, their applications in smart cities, the most important challenges and critics.

A smart city is a complex system that combines various technologies to provide services and address urban challenges. It aims to minimize human involvement in management, operations, and finance. Blockchain technology is a key component of this system, simplifying procedures and reducing costs through asset decentralization. It enhances transparency, security, and eliminates data duplication. However, implementing blockchain technology in smart cities can be challenging due to lack of knowledge about governing organizations' physical structures. The chapter discusses current trends and challenges in implementing blockchain technology in smart cities, highlighting its potential to aid modernizing network technology and infrastructure management systems.

Chapter 5 - Blockchain-based energy-efficient smart green city in IoT environments

Water management, metering and billing are essential services for any industry and residential settlement, and having these running as efficiently as possible is key to an improved standard of living. Energy efficiency and reading or topping up meters remotely are important in ensuring no loss to the regulatory authority or disruption of service to the user. Smart water meters have emerged as a major innovation in the drive to achieve this efficiency through multiple forms and protocols that have shown varying energy consumption, range and durability, relieving physical water meter readers from the strains of doing their job in inclement weather, difficult terrain or under poor coordination. To model and develop a system that addresses these issues as closely as possible to Zimbabwe’s current needs, the study assesses real-world systems deployed in Harare, taking into account the costs, logistics, licensing and other challenges involved in current operation. This study focuses on the energy analysis and development of a remote smart meter system using LoRaWAN as a communication protocol. This compact system aims to be as energy conscious and efficient as possible, all while flawlessly collecting meter data and transmitting it to a remote gateway or billing system. It focuses on the energy consumption of the system when used by different users models on their consumption, recharge behavior and system activity up-time.