Conventional Meters Research Articles

In-situ measurement of thermal transmittance of building walls: Evaluation of stored heat flux in heavy-weight walls during the cooling season

The conventional heat flow meter (HFM) method is used to measure the thermal performance of building walls. Typically, this method is applicable for measurements on lightweight walls and when the difference between the indoor and outdoor temperatures exceeds 10 °C. However, modern buildings are constructed using highly insulated high-performance heavy-weight walls. Therefore, an in-situ measurement method is required to overcome the limited measurement environment of the conventional HFM method. In this study, a novel stored heat flux (SHF) method is proposed to overcome the limitations of the existing HFM method. This method estimates the stored heat flux in the wall using the thermal energy-conservation equation of the enclosed system and uses a decrement factor and time lag to calculate the thermal transmittance (U-value). The proposed method can be applied to heavy-weight walls in the cooling season when the difference between the indoor and outdoor temperatures is less than 10 °C. Furthermore, the design U-value can be estimated with higher accuracy than that observed in the conventional HFM method. The results of the relative error analysis for the U-values show that the conventional HFM method was approximately 68 % of the design U-value, while the proposed SHF method was approximately 15 %.

Mobile Application Development for Prepaid Water Meter Based on LC Sensor

This study presents a novel low-cost and low-power prepaid water meter system that combines tokenization and LC sensors to monitor water consumption accurately with mobile application via Bluetooth Low Energy (BLE) connectivity compared to conventional meters. Water meters play a vital role in monitoring water usage in Indonesia. Postpaid billing methods that rely on manual data recording are a source of concern due to potential inaccuracies caused by human error. This study presents the development of a prepaid water meter system that integrates LC sensors, BLE connectivity, a tokenization mechanism, and a mobile application to address this issue. The system offers a cost-effective solution by utilizing BLE + Global System for Mobile (GSM) from the user’s mobile phone. Using the design thinking methodology, the mobile application for the prepaid water meter achieved a usability testing score of 80. The load testing results for the back-end server, conducted with a sample size of 515 users, revealed a back-end latency of 1.973 milliseconds and an error rate of 8.74%. Furthermore, the LC sensors integrated into the PWM device showed an average error rate of 1.33%. The power consumption during each work cycle was measured at 129 mA and each battery is expected to last six years. Overall, with simple LC sensors, this system can precisely measure water usage.

On the use of perforated disk inserts in a round pipe to form a gas flow of the required structure in front of an ultrasonic flow meter

Unlike conventional gas meters, ultrasonic flow meters have such advantages as contactless operation, minimal pressure loss and high accuracy. When developing ultrasonic flow meters, like any other devices, assumptions and simplifications related to the theory of ultrasonic flow meters are used. When developing such devices, researchers do not always have the necessary space to deploy such structures. Therefore, the question arises of developing devices that can replace large sections of pipelines with various turns in the role of local resistances. The paper presents some studies conducted during the development of a perforated disk capable of forming a flow profile similar to the profile after a double bend. The presented results of a study of the influence of the perforated disk geometry on the gas dynamics and flow structure. The calculations were carried out using three-dimensional computer modeling. The analysis of the influence of the hole location, their sizes and the angles of inclination of the holes relative to the disk axis on the velocity distribution and the formation of the velocity profile downstream of the disk is the purpose of this study. Scalar and vector fields of velocities downstream of the perforated disk are obtained. Velocity profiles in sections behind the disk are constructed. A comparative analysis of different designs of perforated disks is carried out. The design principles of such flow formers are indicated. The geometric factors influencing the flow structure after the former are revealed. The revealed subtleties and described design principles made it possible to develop straighteners and flow formers based on perforated disks. The final samples of disks and the results of their operation are shown

3D Prototyping of Medical Devices for Non-Invasive Glucose Monitoring

In recent years, as global diabetes rates have increased, a growing number of individuals have been experiencing pain and infections due to the invasive nature of conventional commercial glucose meters.

A large-scale evaluation of machine learning algorithms in mid-term water demand forecasting

ABSTRACT Water utilities currently face challenges in accurately measuring user-end consumption as they have to visit every conventional meter that is installed in their service area. This study explores the use of accessible machine learning models to forecast water demand at two crucial temporal scales, addressing practical needs such as customer billing. To draw meaningful conclusions, these models were tested and trained from actual user-end water consumption data from over 2.1 million customers over a 10-year period. These data were provided by the Water and Sewage Company of Greece (EYDAP). The large-scale experiment included the use of statistical models (ARIMA and SARIMA), deep learning [long short-term memory (LSTM)], and clustering techniques (k-NN algorithm). The model with the best performance was ARIMA, outperforming all the other models including the more complex ones. The LSTM model did not perform as expected in predicting water consumption, it excelled only in predicting the total amount of water consumed. These forecasts can be valuable tools for water utility companies, aiding in tasks such as customer billing and water balance calculations. This paper covers all the necessary steps that must be taken to achieve meaningful user-end water consumption forecasts, from raw data preprocessing to hyperparameter tuning for machine learning algorithms.

Low-Cost Source Measure Unit (SMU) to Characterize Sensors Built on Graphene-Channel Field-Effect Transistors.

This study introduces a flexible and low-cost solution for a source measure unit (SMU), which is presented as an alternative to conventional source meter units and a blueprint for sensor FET drivers. An SMU collects current-voltage (I-V) curves with an additional variable voltage or current and is commonly used to characterize semiconductors. We present the hardware design, interfacing, and test results of our SMU. Specifically, we present representative I-V curve measurements for graphene-channel FETs to demonstrate the SMU's capability to efficiently characterize these devices with minimal noise and sufficient accuracy. This cost-effective solution presents a promising avenue for researchers and developers seeking reliable tools for sensor development and characterization. We demonstrate, with the example of surface illumination, how the sensing behavior of graphene-channel FETs can be characterized without the need for expensive equipment. Additionally, the SMU was validated with known passive and active components, along with probe station integration for semiconductor die-scale connection. The SMU's focus on collecting I-V curves, coupled with its ability to identify device defects, such as parasitic Schottky junctions or a failed oxide, contributes to its utility in quality testing for semiconductor devices. Its low-cost nature makes it accessible for various research endeavors, enabling efficient data collection and analysis for graphene-based and other nanomaterial-based sensor applications.

A learning‐based method for optimal dynamic privileged parking permit policy

AbstractThe privileged permit service can be provided as an alternative to the conventional meter and reserved services in the off‐street parking lots. In view of the unbalanced demand and the simplistic off‐street parking lot management, this paper proposes a novel parking management problem for setting up and withdrawing the temporary permit‐only policy. To optimize the access rule regarding uncertainty demand on the time of day and the utilization of the parking lot, a deep Q‐learning (DQL) method is proposed to address the uncertainty and dimensionality in the framework of deep reinforcement learning (DRL). To replicate real‐world demand pattern for training deep Q network, a short‐term parking demand model is presented by integrating the long‐short term memory neural network and multivariant Gaussian process. A case study is performed on urban parking lots on university campus. The numerical experiments of a rule‐based strategy, a tabular Q‐learning (TQL) method, and the proposed DQL method are conducted to justify the effectiveness of the proposed method. The proposed method outperforms the static (s, S) inventory policy by 65% and TQL with linear Q‐value estimation by 15% in the total revenue. The sensitivity analyses show the DQL method is capable to handle capacity‐reduced, demand‐increased, and special‐event scenarios while the comparable strategy underperforms the proposed method

Novel AMI in Zigbee Satellite Network Based on Heterogeneous Wireless Sensor Network for Global Machine-to-Machine Connectivity

This study endeavored to enhance the efficiency and utility of microcomputer meters. In the past, their role was predominantly confined to remote meter reading, entailing high construction and communication transmission costs, coupled with subsequent maintenance and operational expenditures. These factors collectively impacted the enthusiasm of various stakeholders to invest in this realm. Hence, in alignment with the smart city development initiative, the natural gas industry has pioneered the establishment of an advanced metering infrastructure with heterogeneous wireless sensor networks (HWSNs) at its core. This visionary leap incorporates global machine-to-machine connectivity (G-M2MC) technology, interconnecting all facets of its operations, thereby positioning itself as a trailblazer within the industry. While advancing this endeavor, the project’s scheduling aligns with the enterprise’s sustainability goals in the early stages of digital transformation. This strategic allocation of resources is responsive to government policies and aspires to cultivate a digitally connected smart green energy hub, thereby expediting the transformation of the living environment. The objective is to provide a stable, secure, cost-effective, and reliable system that can be shared among peers. Furthermore, this study delved into the analysis of congestion avoidance in intelligent Zigbee satellite transport networks based on the HWSNs-GM2MC of non-synchronous satellite orbit system (NGSO) pivotal technologies, utilizing them to integrate the smart LNGas management system (SGMS). Concurrently, it developed application services through the smart meter application interface (SMAPI), distinct from conventional microcomputer meters. However, it is imperative to acknowledge that cloud computing, while processing sensitive data, grapples with issues of latency, privacy, efficiency, power consumption, and zero-trust security risk information management and ethical authority management capabilities in the defense of disaster relief responses.

DESIGN OF SECLUDED ENERGY METER FOR TAMPERING AND UNAUTHORIZED ACCESS DETECTION IN SMART GRID

This paper deals with an energy metering system for electricity monitoring for each and every household that is different from the conventional energy meter. This proposed design is meant to be a better alternative for an efficient and more secure line for energy usage by the consumer without any illegal access to their connections so that they don’t have to pay for something they aren’t accountable for in the first place and protect the supplier/provider, which is the government, from incurring any losses from the theft as well as from customers who tamper with the meter values. These things are vital in today’s world. So,we are taking this into account and designing a smart meter with the IoT technology for monitoring data values at the tip of our fingers, readily available at any moment. It serves many purposes, from the monitoring of energy consumption to easily using mobile phones to work on managing the energy usage according to their budget. It is also easy for the supplier to monitor without manually inspecting the location. The WiFi module ESP8266 is used for the purpose of transmitting the energy data to the server. This paper also deals with a smart grid system in which energy meters are used as a two-way communication system as opposed to conventional meters with one-way communication, which will be a more efficient system. This IoT is good in terms of its development towards an easy and advanced metering infrastructure, which also needs secure communication between the supplier and consumer to protect that data.

Study and development of a technique for measuring concentration and mass flow rate for saline solutions

The purpose of this work is the design and construction of a non-invasive meter for concentration in saline solutions and the proposal of a low-cost mass flow meter for absorption refrigeration systems with LiBr/H2O. The proposed meter makes use of a capacitive sensor relating the electrical capacitance of the LiBr/H2O mixture to the mass fraction of LiBr in the solution. Thus, an experimental apparatus composed of a capacitive sensor with cylindrical geometry, high-frequency oscillators, and a temperature control system was built. Tests involving samples of the solution at concentrations from 50 to 64% LiBr were conducted to reproduce the typical operating conditions of the absorption chiller, establishing correlations between concentration, voltage, and temperature. The matches of these correlations between concentration and density were very good with maximum relative errors of less than 2.5%. The same procedure was performed for the density measurement, achieving a density, voltage, and temperature relationship with errors of less than 0.27%. For the determination of the volumetric flow rates, a turbine-type meter, equipped with a Hall effect sensor W1305347 and an Arduino microcontroller (MEDY FLOW), was adopted, which proved to be effective when dealing with the LiBr/H2O salt solution and good accuracy when compared to conventional meters, showing statistically proven relative errors of less than 4%. The results showed a satisfactory level of repeatability and accuracy with errors of 0.4% and 2.5%, for the range of operation evaluated.

Water Meter Reading Application System Development using Image Processing A Case Study from Sindangsari Village Water Services

PAMDES is a drinking water company managed by local villagers. The water meter data are read and recorded manually without any technology, which is ineffective and inefficient. Digital image processing can be implemented to read and record the water meter data automatically. When implemented in the water meter, it can help PAMDES officers to read the data without the internet, without changing the conventional water meter device, and the water meter data can be read and recorded effectively and efficiently. This research used the agile method, one of the methods used in the Software Development Life Cycle (SDLC). The method is done repetitively within a short period of time. The output of this research is an application with a digital image processing model that can read water meter data up to 82% in normal conditions and still can be improved. This research aims to make the water meter data reading and recording more effective and efficient and to contribute to the transformation of Sindangsari village into a digitalized village.

Relaxation times and dynamic behavior of an optofluidic flow meter in the nanoliter per minute regime

Accuracy and temporal resolution of flow meters are often unacceptable below the microliter per minute scale, limiting their ability to evaluate the real-time performance of many microfluidic devices. For conventional flow meters, this problem arises from uncertainties that depend on physical effects, such as evaporation, whose relative impacts scale inversely with flow rate. More advanced techniques that can measure nanoliter per minute flows are often not dynamic and require specialized equipment. Herein, we report on new experimental and theoretical results that overcome both limitations using an optofluidic flow meter. Previously, we showed that this device can measure flow rates as low as 1 nl/min with roughly 5% relative uncertainty by leveraging the photobleaching rate of a fluorescent dye. We now extend that work by determining the flow meter's relaxation time over a wide range of flow rates and incident irradiances. Using a simplified analytical model, we deduce that this time constant arises from the interplay between the photobleaching rate and transit time of the dye through the optical interrogation region. This motivates us to consider a more general model of the device, which, surprisingly, implies that all time constants are related by a simple scaling relationship depending only on the flow rate and optical irradiance. We experimentally validate this relationship to within 5% uncertainty down to 1 nl/min. Additionally, we measure a relaxation time of the flow meter on the order of 100 ms for 1 nl/min flows, demonstrating the ability to make dynamic measurements of small flows with unprecedented accuracy.

Feature Extraction of Risk Group and Electricity Theft by using Electrical Profiles and Physical Data for Classification in the Power Utilities

Non-technical loss (NTL) is one of the problems that has been a major issue in lost revenue for many years. Electricity distributors have attempted to reduce NTL by detecting electricity theft using various methods. Some events are difficult to detect that conventional meters inspection is inadequate. Moreover, many anomaly patterns found are very complex, confusing in identifying or distinguishing what types of electricity customers are at abnormal risk or energy theft that affects NTL. This paper proposes five key feature extraction methods and six classifying electricity customers using supervised learning. The main problem was studied and collected information, including kilowatt meters, electronic meters, TOU meters, and AMR meters, which cover four customer types that were recorded in the Provincial Electricity Authority (PEA) of Thailand. An electrical profile to be extracted for in-depth analysis of the behavior of each type of electricity customer, combined with the information of physical data to help enhance and increase efficiency. All features examined the relationships in each feature using Pearson correlation and handled unbalanced data using random oversampling (ROS). Then, the extracted data has been trained, validated, and tested to classify three classes: normal, risk, and theft, where we evaluate the results with performance metrics. The results show that random forest (RF) outperforms the rest of the classifiers by achieving a precision-recall area under the curve of 90% and a receiver operating characteristic curve of 78%. Significantly, the results were compared to previous studies and benchmark datasets, which revealed that the proposed method gave better results than other techniques.

Structural assessment of sewer pump stations using a novel photonics-based sensor system

This paper reports the outcome of the research jointly developed and implemented by Sydney Water and City, University of London (City) to create innovative sensing solutions to long term monitoring of wastewater pump stations (PS) which form part of a network owned and operated by Sydney Water (SW). This has been achieved through recognising the potential of photonic devices for use in this environment and thus designing, fabricating and installing innovative optical fibre sensors, (achieving a strain resolution as low as ~1 microstrain), in two representative pump stations chosen by SW (and designated PS072 and PS001). This innovative sensor system has been complemented by conventional cover meter inspection for reinforcement identification. Being sensitive to the structural differences between the two sites chosen, the scientific rationale behind the sensor design, including the sensor positioning, the number of sensors installed, and the types of sensors required has been justified in detail in this paper. This contextualises the sensor data analysis and the key information extracted from the sensor systems designed and installed, thereby allowing better diagnosis of their respective structural operational conditions. Through this type of synergy of sensor data and structural integrity assessment, the key achievements of the work have been to create not just a continuous data-stream but allow accurate assessment of strain and vibration conditions of the structure in both time and position, through real time in situ monitoring and thus to warn of the potential for structural failure and collapse – the prime objective of the work.

Fabrication of Smart Meter for Accurate Use in Home and Industry

This study addresses the challenges posed by conventional energy meters, which rely on manual readings, leading to human errors and inefficiencies. In response to this, a battery-powered smart meter was developed utilizing an STM32 microcontroller, ADE7758 and STPM32 metering integrated circuits (ICs), SIM and ESP32 communication modules, along with a MYSQL database. Real-time energy data from both single and three-phase appliances were collected, and their energy consumption, errors, Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) were quantified. The model demonstrated an acceptable accuracy level, with an estimated MAE of approximately 2.912 units and an estimated RMSE of around 4.048 units, particularly in predicting motor power consumption. Additionally, ARIMA forecasting was applied to a three-phase asynchronous motor, revealing an average active motor power of 250.95 watts, indicating precise results over time.

Point-of-Care Blood Glucose Testing: Post-Market Performance Assessment of the Accu-Chek Inform II Hospital-Use Glucose Meter

A point-of-care glucose testing (POCT) is an essential component of care in patients with hyperglycemia and hypoglycemia in inpatient and outpatient settings. In Russian medical facilities (MFs), conventional glucose meters designed for self-monitoring by patients with diabetes are commonly used for POCT. These home-use meters have two serious disadvantages: the first is large measurement bias and the second - they can't be integrated into laboratory information systems, so measurement data have to be recorded into patient charts manually. Both factors may lead to medical errors. It is reasonable to use in the MFs specialized POCT glucose meters, as they are superior to conventional ones in accuracy and may be easily connected to laboratory information systems. With this in mind, physicians at the Russian Children's Clinical Hospital decided to substitute conventional meters with the Accu-Chek Inform II POCT meter, however, after preliminary performance assessment of the model. To test the Accu-Chek Inform II performance characteristics: accuracy, linearity, repeatability, and mean absolute relative difference (MARD). Performance of the Accu-Chek Inform II was tested by comparing the results of parallel CGL measurements with the meter and reference laboratory analyzer in capillary blood samples. Overall, 99 parallel CGL measurements were made in 45 samples. Accuracy was evaluated according to the ISO 15197-2013 and POCT12-A3 criteria. The Accu-Chek Inform II meter met the requirements of ISO 15197-2013 and POCT12-A3 and demonstrated high linearity (correlation coefficient, r=1,0), good repeatability (mean coefficient of variation, CV=1,38%) and acceptable MARD (4,9%). The Accu-Chek Inform II POCT glucose meter may be efficiently and safely used in inpatient and outpatient MFs and particularly in pediatric clinics.

Study on Improvement of Radio Propagation Characteristics of Cast Iron Boxes for Water Smart Meters.

Water utilities in Japan face a number of challenges, including declining water demand due to a shrinking population, shrinking workforce, and aging water supply facilities. Widespread use of smart water meters is crucial for solving these problems. The widespread use of smart water meters is expected to bring many benefits such as reduced labor by automating meter reading, early identification of leaks, and visualization of pipeline data to strengthen the infrastructure of water services, business continuity, and customer service, as detailed data can be obtained using wireless communication. Demonstration tests are actively conducted in Japan; however, many problems have been reported with cast iron meter boxes blocking radio waves. To address the issue, a low-cost slit structure for cast iron meter boxes is investigated in this study. The results confirm that the L-shaped tapered slit array structure with a cavity, which can be fabricated in a cast iron integral structure, satisfies the design loads required for road installation. The proposed slit structure achieved gain characteristics from -3.32 to more than 9.54 dBi in the 800 to 920 MHz band. The gain characteristics of conventional cast iron meter boxes range from -15 to -20 dBi, and the gain has been significantly improved. Antennas with a gain of -2.0 to +1.5 dB (0.8 to 2.5 GHz) were used for the transmitter antenna, which was found to have a higher gain than the transmit antenna in the 800 to 880 MHz frequency band. In the 1.5 to 2.0 GHz band, a high peak gain of 4.25 dBi was achieved at 1660 MHz, with no null and the lowest gain confirmed that this is an improvement of more than 10 dBi over conventional products.

Prepaid water meters and water distribution system improvement: A case study of Jenin city, Palestine

A total of 1792 prepaid water meters (PPWMs) were installed along with the activities to improve water distribution in Jenin City, Palestine. The tariff collection rate, previously at 40%, increased to over 90%, thereby resulting in a revenue increase of 1.93 times. PPWMs reduced the need for direct contact between utility staff and customers, resulting in less susceptibility to COVID-19 than conventional meters. The PPWMs fostered water distribution equity by promoting conservation. While these meters boost the revenue of water utilities, increasing user satisfaction by optimizing water distribution is essential, ensuring suitable PPWM installation rates and sustainability. Concerns linger about consistent customer resistance to PPWMs, support for low-income households, and the provision of maintenance services post-warranty.

IoT-based Electrical Power Recording using ESP32 and PZEM-004T Microcontrollers

The electricity usage recording system in Indonesia still uses conventional kWh meters. Electricity usage is recorded by officers who visit customers' homes every month. This results in the electricity company having to provide employees who become a burden on the company's costs. Technological advances enable convergence between communication channels and various things. A technology known as the Internet of Things (IoT) allows customer kWh meters to be recorded in real-time. This research aims to create an Internet of Things (IoT)-based kWh meter that can make it easier for electricity companies to monitor each customer's electricity usage. The IoT kWh meter created can be monitored and controlled from a remote location in real-time. If there is a change in load usage, it will be monitored directly via a mobile device because the kWh meter is directly connected to the internet network and cloud server. To determine the functionality of the tool being made, several tests were carried out, such as a) sensor testing, b) LED indicator, buzzer, and relay testing, c) OLED display testing, d) Firebase database testing, and e) load testing. The test results obtained are used to calculate the error of the tool made with a comparator, and the results show that the percentage of voltage error with different loads is very small, namely 0.35% and 1.45%. This research produced a prototype using ESP32 and PZEM-004T, which is so accurate that it is recommended for recording electrical power, which can reduce the burden on operational costs for electricity companies.

Surface Quality Optical Measurement of Part Inclined Planes Manufactured by FDM Technology

Fused Filament Deposition (FDM) additive manufacturing technology allows the generation of three-dimensional parts by overlapping layers of an extruded polymer. The staircase effect caused by overlapping is well known and makes the manufactured parts have poor surface quality. This problem has been focused on by numerous works trying to optimize the surface quality by studying the process technological parameters or part geometry. Also, post-processing techniques have been developed that improve this roughness, but which involve an increase in manufacturing time and cost. In this work, a methodology to measure the roughness based on laser confocal microscopy is proposed. To evaluate the methodology, an experimental study is carried out that relates the surface roughness of parts manufactured with FDM with the building orientation and the layer height. The main objective of this study is to compare two roughness measurement methodologies: a mechanical measurement with a conventional contact roughness meter, and an optical measurement with a confocal microscope. The contact roughness meter provides a direct value of the roughness of the part wall profile, while the confocal microscope provides an image of the three-dimensional surface of the part wall, which must be processed. The data from the confocal microscope are evaluated with the Internet-based software Surface Metrology Algorithm Testing System (SMATS) developed by the National Institute of Standards and Technology (NIST) of the USA. The SMATS will provide an average value of the roughness of the analyzed surface. The test results with both methodologies are very similar, with an average difference of 5%. These results show the influence of the printed plane inclination angle on the roughness, which is higher for low values of the angle. It can also be seen that this influence decreases for low-layer heights.