Water Meters Research Articles

Optimal design of triangular side orifice using multi-objective optimization NSGA-II.

Triangular orifices are widely used in industrial and engineering applications, including fluid metering, flow control, and measurement. Predicting discharge through triangle orifices is critical for correct operation and design optimization in various industrial and engineering applications. Traditional approaches like empirical equations have accuracy and application restrictions, whereas computational fluid dynamics (CFD) simulations can be computationally costly. Alternatively, artificial neural networks (ANNs) have emerged as a successful solution for predicting discharge through orifices. They offer a dependable and efficient alternative to conventional techniques for estimating discharge coefficients, especially in intricate relationships between input parameters and discharge. In this study, ANN models were created to predict discharge through the triangle orifice and velocity at the downstream of the main channel, and their effectiveness was assessed by comparing the performance with the earlier models proposed by researchers. This paper also proposes a novel hybrid multi-objective optimization model (NSGA-II) that uses genetic algorithms to discover the best values for design parameters that maximize discharge and downstream velocity simultaneously.

Wireless water consumption sensing system for building energy efficiency: A visual-based approach with self-powered operation

The use of smart wireless remote water meters has become popular due to their efficiency in avoiding manual labor and automate meter reading. The current implementation of these measurement instruments often requires expensive external power sources and separate data aggregators, posing challenges for circuit safety and the goal of reducing carbon emissions in aging communities. In response, a novel wireless system has been developed to accurately measure water consumption in buildings. This system incorporates advanced machine learning techniques and utilizes the potential of water-based energy in a seamless manner. This novel methodology utilizes optical sensors to acquire visual data of water gauges and exploits machine learning techniques, specifically the AVSM model also called Advanced Visual Sensing Model (AVSM). This methodology employs a rigorous approach to achieve accurate metric determinations, thereby eliminating the necessity for additional hardware or excessive power configurations. Moreover, an integrated micro water generator has been seamlessly implemented, demonstrating the capability to effectively transfer energy to a lithium battery for the purpose of storage. This implementation guarantees consistent functionality and a significant decrease in reliance on external power supplies. The data augmentation procedure involves the stochastic manipulation of image luminance, resulting in encouraging results when used in conjunction with the AVSM model. Significantly, the dimensions of the model have been significantly decreased, while maintaining a commendable mean average precision (mAP). By leveraging this method and visual-based features, the system can contribute to overall building energy efficiency and reduce the burdens of manual meter reading while supporting CO2 emissions reduction as a feasible and cost-effective solution for building management, promoting sustainability, and advancing energy-efficient practices in old communities. This new wireless system for measuring water usage provides a practical and affordable way to enhance energy efficiency in buildings, lessen the workload of manual meter reading, and help meet carbon emissions reduction goals. As well as optimizing resource and energy use, this method also aligns with eco-friendly solutions to combat global warming and climate change.

DRINKING WATER QUALITY IN THE DON DELTA IN THE LACK OF WATER CONDITIONS

Lack of water and regulation of the Don river runoff led to an irreversible transformation of natural hydrological and hydrochemical processes. At the end of 2022, despite of the shortage of river water, the region began laying a water pipeline to the Donbass, with a capacity of up to 300,000 cubic meters of water per day. Are there enough reserves of water resources for ever-increasing economic needs, throughout the year? The work is based on a targeted study of the chemical composition of water under different regimes and sea levels on the Taganrog coast of the Don Bay and Delta. The experiment covers the period from December 2, 2022 to January 30, 2023, and separate measurements, for comparison, on February 21; 30.03; 17.04.2023. Summary, three types of ionic composition were distinguished, which characterizes the Svinoe arm of the Don delta. Marine - with dominance (more than 80%) of summary amount of sodium and potassium ions, chlorides and salinity up to 7–9 g/L. The Don waters correspond to low mineralization (less than 2 g/l), an increased proportion of Na+ + K+ (50–60%), a close amount of SO\(_{4}^{{2 - }}\) and HCO\(_{3}^{ - }\) (30–40% each). Since 2018, the presence of ground waters has been regularly recorded when the level decreases. There are brackish waters with a salt content of more than 5 g/L. They typically have a high content of sodium and potassium (more than 60%) and sulfate ions (60–80%). Monitoring shows, that the shortage of fresh drinking water will increase, and as its withdrawal increases, it will accelerate in time. It will be replaced (up to 5–7‰) with mineralized ground and Black Sea water. In what proportions will be pumped (redistributed by seasons) weakly brackish (2–4 g/L) and brackish (4–8 g/L) water into water pipelines remains to be explored.

Proposition of water meter for buildings based on a thin-film resistive sensor: electromechanical and thermal characterizations

Notoriously, measurement proves to be essential to encourage water conservation. Thus, this work characterizes two thin-film resistive sensors (bend sensors) with different coatings aiming at their application to measure water consumption. For this, the individual water measurement system is presented and discussed briefly. Then, resistive sensor parameters and operating principles are detailed, as well as the mathematical formulation of the correlation of the sensor resistance with the flow velocity. Methodologically, the system developed for the electromechanical and thermal characterization of the sensor is presented. The results allowed obtaining a quadratic relationship between the sensor deflection angle and the resistance. Furthermore, it was observed that the polyester-coated sensor presented a low hysteresis value when subjected to temperature variation, obtaining a negative linear relationship between the sensor resistance and temperature. In turn, the polyimide-coated sensor did not show low hysteresis when exposed to temperature change and flexed at 50° and 70° angles. Finally, it is proposed for future work computer simulations and experimental tests to confirm the applicability of the sensor for water measurement.

Effects of Surface Water on Artificial Recharge of Coastal Aquifers by GIS Zoning Maps: A Case Study in Ghaemshahr, Iran

Background: The study aimed to assess surface water resources for potential use during non-irrigation seasons to boost groundwater aquifers. This method also helps reduce aquifer depletion, mitigate land subsidence, and enhance groundwater quality. Methods: In this study, artificial feeding methods were used to determine the appropriate location for the Ghaemshahr plain. Water resources were tested in terms of quantity and quality through field and laboratory studies. Based on the findings, geographic information system (GIS) mapping was utilized to create maps and select the best location and feeding method. Results: The most important source of nutrition for recharging the aquifer in terms of quantity and quality was the Talar River. The study area’s conditions like aquifer thickness, permeability, topographic slope, and land use were analyzed using GIS and thematic maps. The results indicated that by using these methods, it is possible to store 5 million cubic meters of surface water in the aquifer for 6 months. Conclusion: This study demonstrated the feasibility of using surface waters in the area for artificial feeding, employing the pond method1. Additionally, it is recommended to dig measuring wells to monitor the water level rise at the bottom of the pond 1. It also suggests the use of simulation software like PMVIN, Mod flow, and GMS to optimize the artificial replenishment process and select the most suitable approach from the defined scenarios before taking any actions.

The Optimization of Water Storage Timing in Upper Yangtze Reservoirs Affected by Water Transfer Projects

To alleviate regional disparities in water resource distribution and consequent scarcity, China has initiated and planned a series of inter-basin water transfer projects using the Yangtze River Basin as the source. These projects are expected to divert approximately 33.4 billion cubic meters of water annually from the Yangtze River Basin. The implementation of these water transfer projects will inevitably alter the hydrological conditions in the upper reaches of the Yangtze River, impacting the reservoir storage strategies of cascading hydroelectric stations under current end-of-flood-season operational plans. This study quantitatively assesses the impact of water transfer projects on end-of-flood-season reservoir storage in cascading systems using the reservoir fullness ratio as an indicator. Employing reservoir storage analysis models, optimization techniques, and flood risk assessment methods, we simulated reservoir storage processes to evaluate associated flood risks and derive an optimized timing strategy for cascading reservoir storage. The results indicate that advancing the reservoir filling schedule by five days for both the Baihetan and Three Gorges dams can offset the adverse impacts of water transfer projects on reservoir storage efficiency. This adjustment restores the reservoir fullness ratio to levels observed in scenarios without water transfers while still meeting flood control requirements. After optimizing the timing of reservoir filling, the electricity generation capacity for the Baihetan and Three Gorges dams increased by 1.357 and 3.183 billion kWh, respectively, under non-transfer scenarios. In water transfer scenarios, the electricity generation for the Baihetan and Three Gorges dams increased by 1.48 and 2.759 billion kWh, respectively. By optimizing reservoir filling schedules, we not only improved the reservoir fullness ratio but also enhanced the electricity generation efficiency of the cascading systems, offering valuable insights for future reservoir operation optimization.

Internet of Things Enabled Smart Water Excellence Observing and Outflow Recognition System

Currently, global water demands are increasing at an alarming rate, largely due to the depletion of resources caused by factors such as water waste, climate change, and urbanization.Unfortunately, conventional water metering schemes are often performed manually by human resources, which can be both cumbersome and ineffective for conservation efforts. To address the shortcomings of the-state-of-the models, this paper introduces an autonomous water quality monitoring system based on IoT technology to optimize water utilization. The proposed system analyzes and monitors the usage of water in the aquatic industry such as circulation speed measurement and optimization of water supply to reduce water waste and encourage conservation. Also, the proposed system uses pH and conductivity sensors to monitor the quality of the water that is delivered to each residence.

Techno-economic and environmental estimation assessment of floating solar PV power generation on Akosombo dam reservoir in Ghana

Ghana has developed energy policies to help increase the use of renewable energy in its energy mix. With abundant water reservoirs and solar irradiation, the potential to deploy floating solar photovoltaic is feasible to increase the country’s renewable electricity generation. RETScreen Expert software was used for studying a proposed FPV-Hydro hybrid plant system. This study conducted a feasibility analysis for a 420 MWp FPV on Akosombo Dam reservoir a location with 4.66 kWh/m2/day solar energy. The study recommended FPV power plant with capacity factor of 14.1%, and would consist of 500,000 units of solar panels covering a minimum area of 2,460,457 m2 to generate a total annual electricity of 520,233 MWh. The project will save 73,327 cubic metres of water from evaporating which can produce approximately 10 MWp hydroelectric power annually. FPV economic analysis shown that it will results in lower LCOE of US$ 0.10/kWh, annual revenue of USD $52,238,576.00 and 12-years simple payback time, indicating positive economic indicators. Additionally, it will significantly reduce GHG emissions by 308,904.5 tCO 2/MWh annually. The FPV-Hydropower hybrid plants prove feasible and contributes to a greener and less costly energy generation system to meeting the 10% additional Renewable Energy (RE) target of Ghana.

What builds consumer intention to use smart water meters – Extended TAM-based explanation

Water scarcity is an issue that affects the life on earth. Technological advancements, such as IoT water meters, are proven to be effective when it comes to household water reduction. However, there is a lack of research on what influences consumer to apply such devices in their households. This research aims to investigate predictors of the intention to apply smart water meters by extending the Technology of Acceptance Model; hypothesizing that intention to apply IoT water meters is predicted by attitude towards them, which, is determined by perceived usefulness and ease of IoT water meter use. To extend the model frugality, personal innovativeness and environmental concerns were added as moderators of the relationship between perceived ease of use and usefulness as well as attitudes towards IoT water meters. Afterwards, a survey was constructed, and data were collected from 657 participants. The results supported the hypotheses. Intention to adopt water meters was determined by attitude, which was predicted by perceived ease of use and perceived usefulness of IoT water meters. Regarding the moderators, environmental concern was found to be the only variable moderating the influence between perceived ease of use and perceived usefulness on attitudes towards IoT water meters.

Dynamic and harmonious allocation of irrigation water resources under climate change: A SWAT-based multi-objective nonlinear framework

Efficient allocation of water resources in irrigation districts can alleviate regional water shortages and promote sustainable irrigated agriculture development. However, existing research on water resource allocation in irrigation districts does not address the lack of coordination within the “diversion-delivery-irrigation” chain for multiple water sources and users in a changing environment. Hence, poor water supply and demand matching, low efficiency and poor climate change responses pose challenges for efficient water resource allocation in irrigation districts. Therefore, this study couples the SWAT runoff simulation model with a multiobjective nonlinear programming model and proposes a weather-driven dynamic and optimal allocation model for multiple water sources. This model accounts for fluctuations in water supply and fine-tunes the allocation of water resources to different water sources, different channels and different crop fertility periods in the irrigation area. The model is designed to achieve synergistic improvements in water supply and demand, economic efficiency, equity in water distribution and efficiency in water use. The model was applied to the Qindeli Irrigation District in Heilongjiang Province. The results show that an increase in water supply at the head of the channel promotes a synergistic increase in economic efficiency and water supply and demand matching. This model can improve water use efficiency under water scarcity by reasonably optimizing the water use structure of the irrigation district. Compared with the traditional irrigation method, the optimized model saves 4 % of water and increases yield by 399 kg/ha, economic efficiency by 0.2 yuan per cubic meter of water, water use efficiency by 9 %, and water supply and demand matching by >80 % at all stages of fertility. The model ensures that water resources are allocated in an equitable manner at all levels.

Integrated Pumped Hydro Reverse Osmosis System optimization featuring surrogate model development in Reverse Osmosis modeling

The pressure head generated by the upper reservoir of a pumped hydro energy storage system can be sufficient for creating the pressure gradient required for a reverse osmosis desalination plant. Combined with the fact that many drought-stricken coastal areas have nearby mountains at the necessary elevation for these upper (mountaintop) reservoirs, a symbiotic relationship can be ascertained through the co-location of a pumped storage hydropower (PSH) system with a reverse osmosis (RO) desalination system. Merging PSH and RO into one Integrated Pumped Hydro Reverse Osmosis System (IPHROS) instead of implementing each individually could result in a number of benefits, including reduced capital investment, lower maintenance costs, and a natural mechanism for diluting the highly saline brine discharge generated from the RO process. This paper extends the work of Slocum et al. in 2016, who first introduced the concept of IPHROS, by optimizing the amount of seawater sent to and diverted from the upper reservoir for maximal energy recapture and freshwater production, respectively, while also seeking to maximize the RO system recovery ratio. For this multiobjective optimization, a new reverse osmosis model is created that utilizes a blend of empirical and fundamental equations based on the solution–diffusion model of membrane transport and boundary layer effects that naturally occur along reverse osmosis membranes. Additionally, surrogate models are developed to predict the permeate flowrate and fractional salt rejection rate for a Seamaxx™-440 RO element. Optimizing the presented IPHROS model reveals a 16% decrease in the break even time for IPHROS compared to PSH and RO being implemented individually, and that at the best design with regards to the energy, freshwater, and RO system recovery objectives, 79.5 million kWh of energy and 5.79 million cubic meters of fresh water can be delivered to a population, significant amounts for a population seeking to transition to a renewable energy-based grid and alleviate dire freshwater conditions. Enhanced modeling and optimization, as was initiated in this paper, will eventually aid in IPHROS’ large-scale adoption into energy and freshwater infrastructures.

Comparison of Wireless Data Transmission Protocols for Residential Water Meter Applications

Comparison of Wireless Data Transmission Protocols for Residential Water Meter Applications

THE COVID-19 PANDEMIC OUTCOMES ON FOOD WASTE AND CARBON FOOTPRINT OF CAFÉS IN BANDAR BARU BANGI AND SUNGAI PETANI, MALAYSIA

Cafés, a subcategory of the foodservice industry, are popular as a place to eat and meet with others, among Malaysians and the world population. Their operation partly contributes to food waste and carbon footprint. However, the volume of these parameters fluctuated throughout the COVID-19 pandemic. Further, there is a need to diversify the food waste data of foodservice establishments in Malaysia, across different regions and cultures. Therefore, we conducted an environmental assessment of ten cafés in two of Malaysia’s cafe hot spots, Sungai Petani and Bandar Baru Bangi, to determine their food waste (preparation loss and plate loss) and carbon footprint generation in a week when the COVID-19 restrictions were relaxed. Data on carbon footprint were collected by reading the electricity and water meters and calculated using emission factors. Sungai Petani generated substantially more food waste (77.68 % in total, equivalent to 93.04 kg) than Bandar Baru Bangi (22.32 %, equivalent to 26.73 kg), as revealed by material flow and descriptive analyses. Similarly, the carbon footprint from water consumption in Sungai Petani was 1.03 kgCO2e, generated from 3m3 water consumption, whereas Bandar Baru Bangi produced 0.82 kgCO2e of carbon footprint from 2.39 m3 water consumed, both districts on a Sunday. Contrarily, the carbon footprint related to the electricity usage in both locations was comparable. The largest amount of carbon footprint produced in Sungai Petani was on Sunday, while Saturday showed the highest carbon footprint in Bandar Baru Bangi. These findings will help the future redirection of Malaysia cafés’ management towards more sustainable practices, which can be enhanced with the help of information on customer footfall.

3E assessment of a solar-driven reverse osmosis plant for seawater desalination in a small island of the Mediterranean Sea

Water scarcity in many regions of the world and global demographic growth make the desalination of seawater and/or brackish an effective solution to meet the growing demand for fresh water. Nowadays, reverse osmosis has the largest share of the global installed desalination capacity. The impelling need to reduce greenhouse gas emissions has been pushing the search for sustainable technologies to produce the electricity needed to power reverse osmosis plants. Among solar technologies, little attention has been paid to the possibility of powering reverse osmosis with electricity from the dish-Stirling solar concentrator. To fill this knowledge gap, this paper assesses the energy-saving potential of a reverse osmosis plant coupled with a cogenerative dish-Stirling concentrator on a small island in the Mediterranean Sea. A model of the integrated systems was developed based on data measured on a real dish-Stirling concentrator. Moreover, the variation of the energy consumption of the reverse osmosis plant with the temperature of the feedwater solution was also accounted for. Hourly simulations showed that almost 36% of the annual water demand could be covered by driving the plant using electricity from the concentrator, and the solar fraction of the electricity consumed by the reverse osmosis plant accounted for 48%. Finally, economic and environmental analyses revealed that the levelized cost of water of €1.08 per cubic meter of fresh water, consistent with the literature, and the system could avoid emitting 34.16 tons of carbon dioxide equivalent emissions per year.

Automatic Piston-Type Flow Standard Device Calibration System

Measurement of flow is crucial for assuring product quality, increasing manufacturing effectiveness, and promoting the development of science and technology. With the advancement of calibration and automation, standard devices using the mass method, volumetric method, and master meter method have limitations, such as low calibration efficiency and automation, large size, and complex operation. Innovations in this area are desperately needed. To realize the automation of calibrating ultrasonic water meters, a piston-type flow standard device calibration system with a high degree of automation, high calibration efficiency, small size, and easy operation was designed. A piston-type flow standard device was designed, the standard device was modeled, the selection of the main hardware and the design of the automated control of the hardware parts were completed; an automation control system adapted to the flow standard device was developed; and, furthermore, a water meter flow point calibration algorithm integrating the start–stop method and the dual-time method, as well as a water meter flow correction algorithm, was devised to improve the efficiency of ultrasonic water meter calibration. An uncertainty assessment of the designed system was completed; the standard uncertainty and expanded uncertainty of the device were 0.013% and 0.026%. Meanwhile, flow calibration tests were conducted, validating the rationality of the automated calibration algorithm for ultrasonic water meters. The results show that ultrasonic water meters calibrated with flow correction have a flow error within ±3% in the “low flow range” and within ±2% in the “high flow range”, with a repeatability of less than 0.05%. This indicates that a piston-type flow standard device, coupled with an automation calibration control system, can efficiently, accurately, and conveniently perform water meter calibration, and the system has good practical value.

Development of the Exowave Oscillating Wave Surge Converter

With increasing demand for renewable energy resources, the development of alternative concepts is still ongoing. The wave energy sector is still in vast develop- ment on the way to contribute to the energy production world wide. The present study presents the development of the Exowave wave energy converter made so far. A numerical model has been established supported by wave flume tests performed at Aalborg University during the first phase of the development. Furthermore, a successful open sea demonstration has been performed on 7 meters of water at Blue Accelerator, Belgium, from which the concept has been proven. As part of the ongoing research, verification of the numerical model will be made through experimental testing in the wave tank of Aalborg University, and an open sea demonstration at 14 meters of water depth will be executed off the coast of Hanstholm, Denmark.

Metric Modes and Fluid Meter in Mande Drumming Music

This article proposes a model that unites a broad range of performances of Mande drumming music within a single cohesive and fluid sub-beat metric framework. The framework categorizes musical performance in terms of two metric modes, each of which includes a set of metric cycles featuring non-isochronous pulsations. A novel feature of the proposed model that distinguishes it from previous research is that it frames metric non-isochrony in terms of the ranges for pulsation positions within a pulsation cycle. This approach is shown to be especially useful for analyzing and describing mechanisms of metrical change and transformation and for connecting seemingly distinct phenomena and repertoire.

Design and Development of User-Friendly Vertical Aquaponics Set-up for Ornamental Fish and Plants

One vertical aquaponics unit following the principle of Nutrient Film Technique (NFT) has been designed and developed at ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar centre of All India Coordinated Research Project on Plasticulture Engineering in Agriculture Structures and Environment Management (AICRP on PEASEM). The developed unit is constructed using three major components, viz., fish tank/ aquarium tank (0.127 m3), vertical hydroponic pipe (Ø0.16×1.5 m) and the water distribution system. The unit experimented with 30 numbers of Guppy fish (Poecilia reticulata) in 0.1 cubic meters of water and 6 numbers of Petunia plant (Petunia × hybrida) and 6 numbers of Zinnia plant (Zinnia angustifolia) in 780 CC hydroponics cups arranged at 20° from the vertical axis on a PVC pipe. The quad channel sprinkler is fixed inside the pipe at the top surface. The water dispersion efficiency concerning the availability of nutrient-rich water at the roots of the plants for its flowering has been evaluated in the present study. The optimum water quality and flower production from the plants were achieved at 200 LPH flow rate from the fish tank. At this hydrolic loading rate, maximum plant length & spread were observed among the three replications . The length & spread for Zinnia angustifolia and Petunia x hybrida were 37.17±4.27 cm & 39.54±7.45 cm, and 33.43±2.53 cm & 29.58±7.26 cm respectively. There was no significant difference (p>0.05) in the water quality parameters at 200 & 250 LPH flow rates in the vertical aquaponics system.The cost of one unit is calculated to be INR 7000, with approximately a 10-20% price reduction in case of mass production. The newly developed integrated system of aquarium is designed for peri-urban and urban hobby farming as well as home decoration.

An Internet of Things-Based Home Telehealth System for Smart Healthcare by Monitoring Sleep and Water Usage: A Preliminary Study

Recently, the Internet of Things (IoT) has attracted wide attention from many fields, especially healthcare, because of its large capacities for information perception and collection. In this paper, we present an IoT-based home telehealth system for providing smart healthcare management for individuals, especially older people. Each client node of the system is mainly composed of an electronic water meter that records the user’s daily water usage, in order to analyze their living patterns and lifestyle as well as ascertain their well-being, and an unobtrusive sleep sensor that monitors the user’s physiological parameters during sleep, such as heart rate (HR), respiratory rate (RR), body movement (BM), and their states on the bed or outside the bed. The collected data can be transmitted to a remote centralized cloud service by a wireless home gateway for analyzing the living pattern and rhythm of users. Furthermore, the periodic feedback of results can be provided to users themselves, as well as their family and health advisers. In the present study, data was collected from a total of 18 older subjects for one year to evaluate the effectiveness of the proposed system. By analyzing living patterns and rhythm, preliminary results indicate the effectiveness of the telehealth system and suggest the potential of the system regarding improvement in the quality of life (QoL) of older people and promotion of their health.

Smart water metering as a non-invasive tool to infer dwelling type and occupancy – Implications for the collection of neighbourhood-level housing and tourism statistics

The international rollout of advanced metering infrastructure (AMI) in the residential water supply sector affords tremendous benefits in driving water-use efficiencies, accurate billing and network management (e.g. leak detection). AMI, using ‘smart meters’ fitted at a dwelling level, record water consumption at high temporal resolution. Since water is typically only consumed when householders are present, these data could offer a non-intrusive means of inferring dwelling occupancy patterns. These insights could have a range of benefits dependent upon the spatiotemporal scale and the intended application – our interest is in the potential of these data to identify dwelling type, specifically to identify dwellings that have occupancy patterns associated with tourism, such as second homes or short-term holiday rentals. We focus on these data in a UK context and draw on data rarely available for academic research. Our data relate to a sample of dwellings in Devon and Cornwall, South West England. They capture high-temporal resolution water consumption during Covid-19 ‘lockdown’ and ‘staycation’ periods, providing a unique opportunity to demonstrate that these data can reveal the unusually pronounced property-level occupancy trends evident during this period. We apply Non-Intrusive Occupancy Monitoring (NIOM) to extract dwelling-level occupancy status (occupied/unoccupied) on a day-by-day basis. We group properties according to their occupancy trends, inferring a set of properties that exhibit occupancy characteristics associated with tourism. We demonstrate that these show correspondence with underlying indicators of tourism activity, drawn from AirDNA records of short-term tourist rental properties in this area. Ongoing global rollout of AMI means that these data will be routinely available at the dwelling level and we reflect on the benefits they could provide in generating near real time insights into dwelling occupancy. Drawing on our collaboration with the Office for National Statistics (the UKs national statistical institute) we outline the considerable potential that these data and approaches could offer in the collation of small area housing and tourism statistics.