Article
Computer Science, Information Systems
Riccardo Zese, Elena Bellodi, Chiara Luciani, Stefano Alvisi
Summary: This study applies supervised Machine Learning techniques to automatically detect leaks of different magnitudes and compares the results with an empirical algorithm. The experimental results show that ML techniques significantly improve the detection performance of leaks.
Article
Green & Sustainable Science & Technology
Steven Hendrik Andreas Koop, Sharon Helena Pascale Clevers, Elisabeth Johanna Maria Blokker, Stijn Brouwer
Summary: Digital Water Meters (DWM) provide real-time water-usage feedback and have high acceptance rates among respondents in the Netherlands, with 93% supporting utility investment in DWM and 78% willing to accept DWM for benefits like improved leakage detection, lower costs, and environmental considerations. Using an attitude-based customer segmentation approach can effectively predict respondents' motivation to endorse DWM, offering promising opportunities for tailored water conservation messaging strategies.
Article
Construction & Building Technology
L. Canale, T. Cholewa, G. Ficco, A. Siuta-Olcha, B. Di Pietra, P. Kolodziej, M. Dell'Isola
Summary: Within the residential sector, it is important to increase users' awareness and induce virtuous behaviors to reduce excessive uses of Domestic Hot Water (DHW) production. Individual metering and consumption-based billing have been found to be useful tools for reducing energy and water waste and increasing end-use energy efficiency. This study investigates the effect of individual metering systems on DHW consumption in the residential sector and finds that after the installation of individual DHW meters, there was a significant decrease in daily heat consumption and DHW volume withdrawn by buildings.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Engineering, Environmental
Morgan Faye DiCarlo, Emily Zechman Berglund
Summary: This research explores customer compliance with water advisories using water consumption data collected through Advanced Metering Infrastructure (AMI). The study analyzes water use changes during a water main break and evaluates the volume of water saved through compliance with utility notifications. The results provide insights into the expected level and variation of water conservation during a Water Service Interruption (WSI).
Article
Water Resources
Diogo Fidelis Costa, A. K. Soares
Summary: Accurately determining water consumption is crucial for improving hydraulic modeling reliability. Smart metering systems can provide consumption data at a customer level and in small time intervals. This study focuses on a residential condominium in Brazil, where a smart metering system is implemented, to model consumers' water consumption and propose a system for detecting metering failures and internal water loss.
URBAN WATER JOURNAL
(2023)
Article
Engineering, Environmental
Morgan Faye DiCarlo, Emily Zechman Berglund
Summary: This research examines the impact of water advisories on consumer water conservation behaviors using data collected through Advanced Metering Infrastructure. The study found that water use behaviors changed during a major water service interruption, but different user segments responded differently to the water advisories. Statistical analysis showed that some consumers reduced their water usage in accordance with utility notifications and achieved water conservation goals.
Article
Construction & Building Technology
Samuele Spedaletti, Mose Rossi, Gabriele Comodi, Luca Cioccolanti, Danilo Salvi, Matteo Lorenzetti
Summary: This study successfully implemented a comprehensive approach to reduce water losses in a Water Distribution Network in Osimo, Italy, utilizing the DMA method. By monitoring flow rates, calibrating hydraulic models, and installing smart meters, a 12.5% reduction in water losses was achieved, resulting in energy and cost savings.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Computer Science, Interdisciplinary Applications
Camilo J. Bastidas Pacheco, Joseph C. Brewer, Jeffery S. Horsburgh, Juan Caraballo
Summary: Developed CIWS is an open-source architecture to automate the process of collecting and managing high temporal resolution residential water use data. Through two case studies, it was tested for scalability and performance, proving to be reliable and effective. All elements of CIWS and the case study data are freely available for re-use.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Chemistry, Analytical
Nour A. Attallah, Jeffery S. Horsburgh, Arle S. Beckwith, Robb J. Tracy
Summary: The datalogger presented is an open source device that can collect and analyze high temporal resolution residential water use data without disrupting the operation of existing analog residential water meters. By performing computation directly on the meter, it reduces data transmission requirements and latency, making it an efficient and effective edge computing solution.
Article
Chemistry, Multidisciplinary
Marion Dumay, Hussein Al Haj Hassan, Philippe Surbayrole, Thibaut Artis, Dominique Barthel, Alexander Pelov
Summary: This paper presents a generic header compression mechanism named SCHC and demonstrates its energy savings effect on a cellular IoT network through real-life implementation and measurements. It also compares the energy consumption and latency between using SCHC over the non-IP transport mode of NB-IoT and the legacy IP mode.
APPLIED SCIENCES-BASEL
(2023)
Article
Energy & Fuels
Godfred Amankwaa, Richard Heeks, Alison L. Browne
Summary: Worldwide, smart metering is becoming increasingly prevalent in the utility sector, particularly in the water sector where it is used to address water management and access challenges. However, little research has been done on its deployment and implementation in urban Global South contexts. This study conducted a mixed-method empirical case study in urban Ghana and found that smart meters are utility-centric and often give limited upgrades and impacts to existing systems and actors. The study also highlighted the friction, mistrust, and skepticism between the utility and users, calling for more customer-centric design and implementation in digital water infrastructure.
Article
Energy & Fuels
Rajesh K. Ahir, Basab Chakraborty
Summary: This paper presents a novel analysis framework to examine residential electricity consumption and understand consumption behavior through clustering analysis of energy usage patterns. The study emphasizes the importance of examining consumption habits and provides insights for better planning of future electricity needs for power utilities.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Energy & Fuels
Anna Mutule, Marcos Domingues, Fernando Ulloa-Vasquez, Dante Carrizo, Luis Garcia-Santander, Ana-Maria Dumitrescu, Diego Issicaba, Lucas Melo
Summary: One of the main challenges in smart city models is guiding consumer behavior towards energy efficiency. Collaboration between energy researchers, ICT experts, and application developers in projects like ITCity aims to facilitate adoption of sustainable energy technologies.
Article
Energy & Fuels
David Nilsson, Par Blomkvist
Summary: The study findings suggest that the Jisomee Mita benefits property owners but does not effectively address the needs of low-income end-users, thus it cannot be considered a pro-poor innovation in its current implementation.
Article
Energy & Fuels
Fanlin Meng, Qian Ma, Zixu Liu, Xiao-Jun Zeng
Summary: In this paper, a multiple dynamic pricing approach for demand response in the electricity retail market is proposed. An adaptive clustering-based customer segmentation framework is used to categorize customers into different groups based on their usage patterns. Customized demand models with important market constraints are developed for each group to improve accuracy and enable meaningful pricing. The approach is evaluated through simulations and results show that it captures changing consumption patterns and achieves better profit gain compared to uniform pricing.
Review
Engineering, Environmental
Zhiguo Yuan, Gustaf Olsson, Rachel Cardell-Oliver, Kim van Schagen, Angela Marchi, Ana Deletic, Christian Urich, Wolfgang Rauch, Yanchen Liu, Guangming Jiang
Article
Computer Science, Information Systems
Rachel Cardell-Oliver, Chayan Sarkar
ACM TRANSACTIONS ON SENSOR NETWORKS
(2019)
Article
Environmental Sciences
Ary Mazharuddin Shiddiqi, Rachel Cardell-Oliver, Amitava Datta
Article
Agriculture, Multidisciplinary
Omar Anwar, Adrian Keating, Rachel Cardell-Oliver, Amitava Datta, Gino Putrino
Summary: This study presents a multi-sensory, remote data acquisition system for beekeeping, which collects data from beehives and analyzes the impact of various environmental factors on hive weight changes. By evaluating different sensors and environmental variables, the system enhances decision making capability and contributes to the monitoring and management of beehives.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Economics
Rachel Cardell-Oliver, Doina Olaru
Summary: This paper proposes the CIAM model for classifying long-term passenger engagement with public transport. By evaluating a 5-year dataset, it identifies distinct patterns of long-term ridership and emphasizes the impact of passenger churn on ridership.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Computer Science, Artificial Intelligence
Omar Anwar, Adrian Keating, Rachel Cardell-Oliver, Amitava Datta, Gino Putrino
Summary: This work presents Apis-Prime, a hybrid deep learning model for soft sensing and time series forecasting, which estimates the daily weight variations of honeybee hives. It improves the state-of-the-art of the earlier proposed WE-Bee model and optimizes the beehive monitoring systems for weight variation estimation. The weight variations of a honeybee hive are crucial indicators of productivity and colony health.
APPLIED SOFT COMPUTING
(2023)
Article
Chemistry, Analytical
Weiyan Xu, Jack Sun, Rachel Cardell-Oliver, Ajmal Mian, Jin B. Hong
Summary: Smart metering systems (SMSs) are widely used for real-time tracking, outage notification, load forecasting, etc. However, the consumption data it generates can violate privacy. Homomorphic encryption (HE) offers privacy protection based on its security guarantees and computability over encrypted data. This paper proposes a privacy-preserving framework using HE with trust boundaries for different SMS scenarios, showing its feasibility in terms of performance and data privacy.
Proceedings Paper
Construction & Building Technology
Maira Alvi, Rachel Cardell-Oliver, Tim French
Summary: This paper proposes a method called AETL to enhance the performance of transfer learning in wastewater processing predictive models. The method leverages an autoencoder to generate large volumes of training data with a distribution similar to the target domain, and shows promising results on a real-world dataset.
PROCEEDINGS OF THE 2022 THE 9TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILDINGS, CITIES, AND TRANSPORTATION, BUILDSYS 2022
(2022)
Article
Computer Science, Information Systems
Maira Alvi, Tim French, Rachel Cardell-Oliver, Philip Keymer, Andrew Ward
Summary: Wastewater treatment plants are complex systems that require monitoring using sensor systems. Soft sensor models can be a cost-effective alternative to expensive sensors for certain parameters in wastewater. This paper proposes a hybrid neural network architecture for learning soft sensors for complex phenomena, and validates the effectiveness using real-world data from a wastewater treatment plant. Additionally, a annotated dataset of a secondary wastewater treatment plant is publicly released to accelerate research in the development of soft sensors.
Review
Water Resources
Richard Koech, Rachel Cardell-Oliver, Geoff Syme
Summary: The adoption of smart water metering technology has been increasing in recent decades, primarily driven by engineering and efficiency considerations. As the technology matures and costs decrease, the adoption rate of smart water meters is expected to rise. Regulatory and social factors will also play a role in shaping the adoption of this technology.
AUSTRALASIAN JOURNAL OF WATER RESOURCES
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Rachel Cardell-Oliver, Prathyusha Sangam
BUILDSYS'19: PROCEEDINGS OF THE 6TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILDINGS, CITIES, AND TRANSPORTATION
(2019)
Proceedings Paper
Computer Science, Software Engineering
Rachel Cardell-Oliver, Christof Huebner, Matthias Leopold, Jason Beringer
DATA'19: PROCEEDINGS OF THE SECOND ACM WORKSHOP ON DATA ACQUISITION TO ANALYSIS
(2019)
Proceedings Paper
Computer Science, Hardware & Architecture
Benjamin Dix-Matthews, Rachel Cardell-Oliver, Christof Huebner
PROCEEDINGS OF THE 7TH INTERNATIONAL WORKSHOP ON REAL-WORLD EMBEDDED WIRELESS SYSTEMS AND NETWORKS (REALWSN'18)
(2018)
Proceedings Paper
Computer Science, Information Systems
Michael Stewart, Wei Liu, Rachel Cardell-Oliver, Rui Wang
2018 9TH IEEE INTERNATIONAL CONFERENCE ON BIG KNOWLEDGE (ICBK)
(2018)
Proceedings Paper
Computer Science, Information Systems
Rachel Cardell-Oliver, Travis Povey
BUILDSYS'18: PROCEEDINGS OF THE 5TH CONFERENCE ON SYSTEMS FOR BUILT ENVIRONMENTS
(2018)
