Electrical Monitoring Research Articles

Intellectual measurement of electrical energy consumption - monitoring device and software

The article presents the principle scheme and software of the intelligent measurement - controldevice that allows determining the efficiency of electricity consumption and the energy efficiency of electrical devices. Mathematical expressions and calibration coefficients of the device for measuringelectrical quantities were calculated. Electronic devices for converting and amplifying analog signals todigital signals were selected and their communication circuits with Arduino microcontroller weredeveloped. Based on the C++ programming language, the software that integrates with the device has beendeveloped. The software determines the efficiency indicators of electricity consumption on 4 interfaces atthe same time. Based on this software tool and device, it was possible to create a control system based oncloud technologies, which allows determining the energy efficiency indicators of a certain area. At the same time Algorithm of the program of regulation of fuel energy resources for the measurement and control system of the efficiency of electric power consumption, and, The Cloud Meters model of the electricity consumption efficiency measurement and monitoring system has been developed.

Electrical monitoring of organic crystal phase transition using MoS2 field effect transistor.

Hybrid van der Waals heterostructures made of 2D materials and organic molecules exploit the high sensitivity of 2D materials to all interfacial modifications and the inherent versatility of the organic compounds. In this study, we are interested in the quinoidal zwitterion/MoS2 hybrid system in which organic crystals are grown by epitaxy on the MoS2 surface and reorganize in another polymorph after thermal annealing. By means of field-effect transistor measurements recorded in situ all along the process, atomic force microscopy and density functional theory calculations we demonstrate that the charge transfer between quinoidal zwitterions and MoS2 strongly depends on the conformation of the molecular film. Remarkably, both the field effect mobility and the current modulation depth of the transistors remain unchanged which opens up promising prospects for efficient devices based on this hybrid system. We also show that MoS2 transistors enable fast and accurate detection of structural modifications that occur during phases transitions of the organic layer. This work highlights that MoS2 transistors are remarkable tools for on-chip detection of molecular events occurring at the nanoscale, which paves the way for the investigation of other dynamical systems.

New approaches and digital technology automation tasks processes of control and accounting of electricity in distribution networks

This paper studies 0.4 kV power distribution networks (PDN) and automated systems for electricity monitoring and metering (ASEMM) As is known, one of the main tasks of ASEMMs is the digitalization of PDNs, aimed at further improving the efficiency and reliability of their operation. It is advisable that new models, methods, and intelligent technologies used for automation and informatization of distribution networks should also be focused on minimizing their power losses, which are currently fairly high thus significantly compromising the technical and economic performance of automation systems employed and PDNs. Modern (conventional) ASEMMs, implemented at the facilities of utilities, do not have the appropriate technical, algorithmic, and software tools designed to reduce power losses in the PDN. This is due to the fact that conventional ASEMMs mainly solve the problem of remote data collection from the system meters and their digital processing for the purpose of revenue metering of electricity. In this regard, the paper proposes methodological, algorithmic, and digital technologies designed to solve a set of new functional tasks in the conventional ASEMMs, aimed at reducing power losses in DPNs by optimizing their operating conditions.

3D organic bioelectronics for electrical monitoring of human adult stem cells.

Three-dimensional in vitro stem cell models have enabled a fundamental understanding of cues that direct stem cell fate. While sophisticated 3D tissues can be generated, technology that can accurately monitor these complex models in a high-throughput and non-invasive manner is not well adapted. Here we show the development of 3D bioelectronic devices based on the electroactive polymer poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate)-(PEDOT:PSS) and their use for non-invasive, electrical monitoring of stem cell growth. We show that the electrical, mechanical and wetting properties as well as the pore size/architecture of 3D PEDOT:PSS scaffolds can be fine-tuned simply by changing the processing crosslinker additive. We present a comprehensive characterization of both 2D PEDOT:PSS thin films of controlled thicknesses, and 3D porous PEDOT:PSS structures made by the freeze-drying technique. By slicing the bulky scaffolds we generate homogeneous, porous 250 μm thick PEDOT:PSS slices, constituting biocompatible 3D constructs able to support stem cell cultures. These multifunctional slices are attached on indium-tin oxide substrates (ITO) with the help of an electrically active adhesion layer, enabling 3D bioelectronic devices with a characteristic and reproducible, frequency dependent impedance response. This response changes drastically when human adipose derived stem cells (hADSCs) grow within the porous PEDOT:PSS network as revealed by fluorescence microscopy. The increase of cell population within the PEDOT:PSS porous network impedes the charge flow at the interface between PEDOT:PSS and ITO, enabling the interface resistance (R1) to be used as a figure of merit to monitor the proliferation of stem cells. The non-invasive monitoring of stem cell growth allows for the subsequent differentiation 3D stem cell cultures into neuron like cells, as verified by immunofluorescence and RT-qPCR measurements. The strategy of controlling important properties of 3D PEDOT:PSS structures simply by altering processing parameters can be applied for development of a number of stem cell in vitro models as well as stem cell differentiation pathways. We believe the results presented here will advance 3D bioelectronic technology for both fundamental understanding of in vitro stem cell cultures as well as the development of personalized therapies.

Prototype of Electric Power Monitoring System and Load Control in Residential Houses Using IoT-Based ESP8266

The use of the Internet of Think (IoT) for a system that can monitor the use of load and electrical power in a residential house will be very necessary. This is because homeowners who often go out and leave their homes with loads that are still active, for example, house lights that are always turned on will be a waste of electrical energy. The purpose of making this article is to create a system that can control electricity use automatically using the Internet Of Think (IoT) and monitor the electricity data in real time, calculate the amount of current, voltage, and power in an entire load. Calculating the comparison of sensor and manual values by looking at the percentage of errors on the sensor, and analyzing whether the sensor is suitable for use or not. The systems used are: Pzem 004t as an overall reader of electrical power, LDR sensor as light input to turn on the lights automatically when it is dark, and nodemcu esp8266 as input/output process and sends data to the internet via a wifi network which will be monitored through the application. Blynk Iot 2.0 ABSTRAKPenggunaan Internet of Think (IoT) untuk sistem yang dapat memonitoring penggunaan beban dan daya listrik  pada sebuah rumah tinggal akan sangat diperlukan. Hal tersebut karena pemilik rumah yang sering berpergian keluar dan meninggalkan rumahnya dengan beban yang masih aktif contohnya lampu rumah yang selalu dihidupkan akan menjadi pemborosan energi listrik tersebut. Tujuan dari pembuatan artikel ini adalah yaitu membuat sistem yang dapat mengontrol penggunaan listrik secara otomatis menggunakan Internet Of Think (IoT) serta memonitoring data listrik tersebut secara realtime, menghitung jumlah arus, tegangan, dan daya pada suatu keseluruhan beban yang ada. Menghitung perbandingan nilai sensor dan manual dengan cara melihat persentase kesalahan pada sensor tersebut, dan menganalisa pada sensor tersebut layak digunakan atau tidak. Adapun sistem yang digunakan yaitu: Pzem 004t sebagai pembaca keseluruhan daya listrik, sensor LDR sebagai input cahaya untuk menghidupkan lampu secara otomatis ketika hari sudah gelap, dan nodemcu esp8266 sebagai proses input/ouput dan pengirim data ke internet melalui jaringan wifi yang akan dimonitoring lewat aplikasi Blynk Iot 2.0.

Design and Development of Wireless-Based Electric Load Control Monitoring System on Autobuses Vehicles

The electrical installation structure on autobuses is generally still based on the old concept that relies on the fuse, where the fuse is the only safety as well as an indicator of the presence or absence of electrical power supply to several electrical devices contained in the autobus. For conditions where there is a short circuit on the line to the electrical load, the electrical equipment on the autobus cannot be operated again. With the problem in the electrical system on the autobus, a monitoring system for controlling the power used on the autobus vehicle was created automatically based on wireless. In this study, the system created using Arduino Uno is functioned as a server node. Then there is a sensor node which will later function to receive incoming data from the Ina219 sensor, then sent using wireless communication to the server node. Then on the server node, all data will be monitored via the LCD display and notification LED, then if there is excessive use the system will turn off the relay where the point is using excess power. From the test results, the sensor node is able to send data from the sensor node readings. Then it is sent to the Node Server and the results obtained are 2% for packet loss. The delay value is 0.29s for the highest result.

A Monitoring System for Electric Vehicle Charging Stations: A Prototype in the Amazon

Among the main problems faced in the context of electric mobility today, the management and monitoring of electric vehicle charging stations, the integration between the diverse types of technologies that make up its architecture, and its low scalability stand out. Therefore, we will present the implementation and complete integration of an electric vehicle charging system in an electric mobility pilot project being executed in the Amazon region in Brazil. Therefore, a literature review of related works will be presented, and its entire implementation will be addressed, from the charging infrastructure, through its back-end system and its Internet of things platform, to its front-end web system for monitoring charging stations. In addition, a complete prototype is created with a real testbed to verify the scalability of the implemented physical system. Based on the testbed evaluations performed, we observe that the implemented system performs well in receiving and sending data from up to 160 electric vehicle charging stations, achieving an average consumption of 26% for CPU and 95% for memory. In addition, it is important to mention that the deployed system supports horizontal scalability, enabling the connection of more charging stations and making it ideal for other integrated systems similar to ours. Based upon the main results obtained with the implemented system, the possibility of carrying out the management and monitoring of charging stations stands out; the integration of different technologies, from the back end and IoT middleware to its front end; a system that supports scalability, enabling the connection of more charging stations; and a reference architecture for charging station management and monitoring systems for the Amazon region.

Design of an Individualized Electric Consumption Monitoring for Sub-Metered Tenants

Electric submeters are energy monitors that break down individual tenants’ electric usage. However, sub-metering uses traditional energy meters for individualized power consumption. The designed individualized electric consumption monitoring system alternates the said energy meters by integrating a microcontroller, Android application, and Short Message Service (SMS). The system comprises two (2) physical parts: the main and metered units. The meter unit plays the part of an energy meter where it records consumption with a maximum of 30 amps, while the main unit saves the data from the meter unit. These two communicate using Radio-frequency identification (RFID). Data is held in a Micro-SD Card and used for sending the amount by the landlord to the sub-metered individuals. The study uses prototyping during the methodology process, then productive interactions and comparative testing on the evaluation. The system’s accuracy evaluation garnered an average percentage error of 0.108% in voltage and 6.502% in current. Overall, the system substitutes the usage of traditional energy meters in sub-metered tenants, and by applying the recommendation, the system is ready for community usage.

Electrical Energy Monitoring and Control System In Boarding Rooms Based On The Internet of Things

Electrical energy is an essential requirement in various activities today. Almost all electronic devices that are used require electrical energy to operate. Therefore, the public needs to know how much electrical energy is used to maintain the quality of electronic devices. Electrical energy monitoring is a process of monitoring and a source of information on electrical energy that can be viewed directly or remotely with real-time output results. Electrical energy monitoring is designed as a routine process of collecting or measuring information source data that determines the level of electricity consumption achievement in real-time. By using real-time information technology, the operating conditions of the hardware system and programs have clear timeframes. Based on this background, the authors want to conduct research designed to monitor and obtain sources of information on the results of the use of electrical energy in boarding rooms, of course this monitoring tool is based on microcontrollers and the Internet of Things (IoT), with the creation of this monitoring of electrical energy, with all parameters electricity such as voltage, current, electric power, electrical energy, and power factor used can be measured using the PZEM-004T sensor. Monitoring electrical energy using the NodeMCU platform as an input and output processor will then be displayed on the control panel display and internet of things (IoT) based Blynk server. From these problems, the authors are interested in conducting research that aims to monitor and obtain sources of information on the use of electrical energy in boarding rooms. This monitoring tool is based on a microcontroller. In addition, this monitoring tool is also based on IoT so that power consumption can be monitored directly and remotely with real-time output results. From the results of the measurement test using the PZEM-004T sensor, it was obtained that the difference in the value of the deviation that occurred was relatively small for voltage 0.538%, current 0.007%, electric power 0.383%, electrical energy 0.005% and power factor 0.039%, it was concluded that the PZEM-004T sensor could be used to further observations. At the same time, the real-time control panel output results to the Blynk server using the NodeMCU ESP8266 produce real-time work, as well as the use of relays as controllers of the tools that have been made, have been tested and obtained satisfactory results.

Electrical Machine Breakdown Monitoring System Using IoT

Nowadays, electrical machines of different types and designs are used in hybrid production systems. Electrical machines are needed to control and implement various mechanisms to produce final products. However, sometimes, electrical machines stop working and cause downtime. This affects workers’ productivity during peak hours and reduces business profits. To overcome this problem, a suitable machine-monitoring system is required so that the problem can be addressed and rectified immediately. In this paper, an IoT prototype for an electrical machine failure monitoring system using Heltec LoRa ESP32 as the microcontroller to communicate with the Blynk IoT platform server was proposed and developed. The monitored parameter values are voltage, current and motion sensor readings. A ZMPT101b voltage sensor is used to measure the AC voltage, while an ACS712 current sensor is used to measure the AC current flowing through the machine. In addition, a tilt sensor is used to detect the vibrating motion of the motor. The measured values indicate machine health and are monitored using the developed Blynk IoT GUI platform, which is accessible from mobile phones and the web. A notification from Blynk application will be sent to users to alert them about a specific condition when a value measured and uploaded to the Blynk cloud exceeds the configured average. Three tests were performed using the serial monitor, the Blynk application and the multimeter, and the results showed that the lowest percentage of error between the voltage sensor readings extracted from the serial monitor and the multimeter was 1.19% and the lowest percentage of error between the current sensor readings extracted from the serial monitor and the multimeter was 17.63%. Overall, all parameter values were successfully displayed on the IoT platform. In future works, the accuracy of the current sensor can be improved by integrating a signal conditioning circuit to filter out noise.

Research on Elevator Operation Harmonic Current Characteristics Analysis and Electrical Fire Detection Technology

The elevator will generate high-frequency harmonic current during operation, and the leakage current generated by the high-frequency harmonic current to ground will cause interference to the residual current type electrical fire monitoring detector due to the existence of parasitic capacitance in the distribution line. This paper analyzes the high-frequency interference signals generated during the operation of elevators and studies the residual current analysis method based on digital filtering technology. Firstly, the causes of false alarms generated by residual current type electrical fire monitoring detectors are analyzed according to the residual current interference signals generated during elevator start-up. Then, the frequency characteristics of the disturbance signal of the elevator in different operating states are proposed by analyzing the spectrum of the disturbance signal during the stationary, ascending, and descending processes of the elevator. Finally, the method of using a fast Fourier transform to analyze the residual current in elevator distribution lines is presented. The experimental results show that the frequency of the residual current interference signal generated when the elevator is running is mainly distributed above 3000 Hz, the energy of the interference signal at 3700 Hz is the largest when the elevator is stationary, and the energy of the interference signal at 4500 Hz is the largest when the elevator is ascending or descending. The amplitude of the signal can be used as a criterion for whether the distribution line generates leakage.

УПРАВЛЕНИЕ ПРОПУСКНОЙ СПОСОБНОСТЬЮ ЭНЕРГОСЕТИ В ЗАДАЧАХ ПРОГНОЗИРОВАНИЯ ЭЛЕКТРИЧЕСКОЙ НАГРУЗКИ

The paper considers the software-modeling complex of the power grid management system andits elements. The relevance of the work is due to the requirements of the current legislation for forecastingelectricity consumption to solve the problem of maintaining a balance of capacity betweenthe generating side and electricity consumption. The developed algorithms and control methods areused as part of a software-modeling complex for managing the power grid and power equipment, themost relevant is the use of autonomous consumers and micro-grids in local power systems. For theeffective conduct of experimental research, an experimental methodology was developed, includingthe stage of development of the experimental plan-program; the choice of means of conducting theexperiment; conducting the experiment; processing and analysis of experimental data. It is shownthat it is possible to use the technical and information basis of a hierarchical automated informationmeasuring system for monitoring and accounting of electricity to build a technological managementsystem of a regional grid company. It is shown that the smart meters of the intelligent electricity meteringsystem (ISU) are in continuous communication with the producer and consumer of energy, thatis, monitoring takes place in real time. The developed neural network model (NS) model reduces thetask of short-term forecasting of power consumption to the search for a matrix of free coefficients bytraining on available statistical data (active and reactive power, ambient temperature, date and indexof the day, predictive estimates of power consumption of the forecasting model, some connections, thepower system of the magnitude of the consumed active and reactive power has an acceptable level ofprediction error. A neural network has been developed to estimate the capacity, calculate and predictthe temperature of the cores of a power cable line in real time based on data from the temperaturemonitoring system, and taking into account changes in the current load of the line. The analysis ofthe obtained characteristics showed that the maximum deviation of the data received from the neuralnetwork from the data of the training sample was less than 3%, which is quite an acceptable result.The comparison of the forecast values with the actual ones allows us to speak about the adequacy ofthe chosen network model and its applicability in practice for the reliable operation of the cable systemof power supply to consumers. The analysis of the results showed that the more the insulationmaterial of the power cable line is aged, the greater the temperature difference between the originaland the aged sample.

Application of Passive Wireless Temperature Online Monitoring System Based on Internet of Things Technology in Substation

With the improvement of the automation level of the power system, the number of operation and maintenance personnel continues to decrease, but the use of switchgear is quite large. Since the switchgear is a metal armoured device with a closed shell, the hot spots inside the switchgear cannot be detected in time during operation. Effective temperature measurement and the safety of equipment cannot be effectively guaranteed. In order to avoid the aging caused by the excessive current load of the switch cabinet, poor contact of cable joints and contacts, or long-term operation, which will cause heat in the place, forming a vicious circle and eventually leading to insulation breakdown or fire accidents, Establish a wireless temperature measurement system for switch cabinets to monitor the temperature of the parts where the equipment is prone to overheat, and issue an alarm message when the temperature rises abnormally. At present, the manual inspection of switch cabinets in the power supply system cannot effectively and timely detect fire hazards, so the problem of online monitoring of switch cabinet temperature is particularly prominent. Using the Internet of Things sensing technology and communication technology, build an Internet of Things-based electrical connection point temperature online monitoring system, the all-weather real-time monitoring of the connection parts of high-voltage electrical equipment can effectively reduce the equipment failure rate, promote the condition maintenance of power equipment, and ensure the safe and economical operation of the power system.

Electric Energy Monitoring Node Design Based on NodeMCU and MQTT Protocol

Intelligent electricity management systems can be widely used for monitoring the regional power consumption of enterprises, factories, campuses, properties, etc. To meet the current demand of electricity consumers for monitoring the power data of each node, a node design method based on Modbus and MQTT protocols for monitoring power consumption has been proposed. It can monitor the power, current, voltage, electricity, and other related parameters of the power nodes so that the electricity consumers can control the electric energy data of each power node in real time. The test results show that the node scheme can effectively monitor the data of each power node and realize the real-time monitoring of power consumption data, which shows that the design scheme is effective and feasible.

Design of a Monitoring System for Power-consumption Devices Based on Modbus Protocol

To better monitor the usage status of electric energy for production and living devices, the paper has put forward an electric energy monitoring system based on Modbus protocol, starting by analyzing the demand for monitoring and management of users’ electric energy. A three-layer structure has been used in the system, which consists of the sensing layer, control layer, and application layer. The lower computer of the sensing layer used the one-master-multi-slave mode to collect the power data of multiple devices in the bus in real time and transmits the voltage, current, power consumption, and other data of power-consumption devices to the host through the RS-485 interface, Modbus protocol, and GPRS network. Meanwhile, the lower computer interacts with the remote user monitoring terminal to realize the monitoring and management of power consumption data of the devices. The test has shown that the system can steadily monitor and manage the power consumption status of the devices in real time, and can be applied to energy saving, monitoring of power-consumption devices, property management, and other fields, which have good application prospects.

Smart fiber orientation monitoring system in a mold via electrical route modeling

The orientation of unidirectional carbon fibers (UDCFs) in a manufacturing process is critical to the mechanical properties of carbon fiber reinforced plastics (CFRPs). This study presents a method to monitor the orientation of UDCFs on a mold using electrical resistance during the CFRP manufacturing process. An equivalent electrical model for UDCFs was proposed to develop an in situ sensor in a mold. The orientation of UDCFs during the CFRP manufacturing process is investigated in terms of its orthotropic electrical properties. The proposed technique can have strong implications on in situ monitoring of composite molding process where the fiber orientation is unseen by monitoring electrical resistance with Cu tapes as electrodes. • Fiber orientation and the corresponding electrical resistance was correlated. • Analogous 3D model for electrical route was proposed with empirical rationales. • Fiber orientation in a mold can be detected by electrical resistance monitoring. • Fiber orientation monitoring is available during the composite manufacturing.

Nutritional Status of Slovene Adults in the Post-COVID-19 Epidemic Period.

Background: Monitoring nutritional status data in the adult population is extremely important to mediate their health status. Unfortunately, for Slovenia (2.1 million European Union citizens), data on the body composition status of the general adult population are currently rare or nonexistent in scientific journals. Furthermore, dietary intake was last assessed several years before the COVID-19 epidemic period. Methods: We randomly recruited 844 adult Slovenes from all regions of Slovenia. The primary aim of the cross-sectional study was to examine body composition status (using a medically approved electrical bioimpedance monitor) during the post-COVID-19 epidemic period. In addition, we assessed dietary intake (using a standardized food frequency questionnaire) and compared the obesity propensity for both sexes separately using the body mass index (BMI) and body fat percentage (FAT%) obesity classification of the World Health Organization. Results: Regarding BMI classification, 43% of the whole sample was overweight (28%) or obese (15%), and there were more older adults than adults (64% vs. 42%, p < 0.001). The average FAT% of adult females and males was 26.9% and 19.5% (p < 0.001), respectively, while for older adult females and males, it was 32.7% and 23% (p < 0.001). In addition, a comparison of the proportions of obese people between the two cut-off obesity classifications (BMI vs. FAT%) showed a significantly underestimated proportion of obese female participants based on BMI classification (13% vs. 17%, p = 0.005). In terms of the dietary intake of the assessed nutrients in comparison with the national dietary reference values for energy and nutrient intake, the participants, on average, had lower intake than the recommended values for carbohydrates, fiber, vitamins C, D and E (for males) and calcium, and higher intake than the recommended values for total fat, saturated fatty acids, cholesterol, sodium and chloride (for males). Conclusions: The results urgently call for the need to not only improve the overall national nutritional status but also for regular national monitoring of body composition and dietary intake statuses.

Condition Monitoring and Auto Diagnostics the Electrical Vehicles Using the Internet of Things

Every year pollution level is starting to increase day-by-day. The major sources of generating pollution are: industry and the other one is automobile vehicles. Particularly automobile vehicles generate more air pollution as well noise pollution. This pollution is not only harmful to birds, but it is also starting to affect human being too. In recent days government takes multiple policies to stop pollution created by automobile vehicles. Such as the decision to demolish old automobile vehicles, provide 30% subsidy to convert automobile vehicles into an electric vehicles, etc. The main objective is to reduce air pollution as well as noise pollution created by automobile vehicles because automobile vehicle number was equally occupied as the human beings in every house. Automobile vehicle conversion technology used to convert automobile vehicles into electrical vehicles. These electrical vehicle condition monitoring and auto diagnostic execute by the Internet of Things (IoT). The IoT uses to communicate each notification to the user through various tools such as Short Message Service (SMS), E-mail, App, etc. In recent days, lot of free cloud data storage services uses to store the past week's data easily. These modern technique uses to handle electric vehicle-friendly approaches. The output of the proposed system is not only cost-effective and environment-friendly but also provide the healthy nature for present and future generations.

Predictive Data Analytics for Electricity Fraud Detection Using Tuned CNN Ensembler in Smart Grid

In the smart grid (SG), user consumption data are increasing very rapidly. Some users consume electricity legally, while others steal it. Electricity theft causes significant damage to power grids, affects power supply efficiency, and reduces utility revenues. This study helps utilities reduce the problems of electricity theft, inefficient electricity monitoring, and abnormal electricity consumption in smart grids. To this end, an electricity theft dataset from the state grid corporation of China (SGCC) is employed and this study develops a novel model, a mixture of convolutional neural network and gated recurrent unit (CNN-GRU), for automatic power theft detection. Moreover, the hyperparameters of the proposed model are tuned using a meta-heuristic method, the cuckoo search (CS) algorithm. The class imbalance problem is solved using the synthetic minority oversampling technique (SMOTE). The clean data are trained and then tested with the proposed classification. Extensive simulations are performed based on real energy consumption data. The simulated results show that the proposed theft detection model (CNN-GRU-CS) solved the theft classification problem better than other approaches in terms of effectiveness and accuracy by 10% on average. The calculated accuracy of the proposed method is 92% and the precision is 94%.

Zebrafish Embryos Display Characteristic Bioelectric Signals during Early Development.

Bioelectricity is defined as endogenous electrical signaling mediated by the dynamic distribution of charged molecules. Recently, increasing evidence has revealed that cellular bioelectric signaling is critical for regulating embryonic development, regeneration, and congenital diseases. However, systematic real-time in vivo dynamic electrical activity monitoring of whole organisms has been limited, mainly due to the lack of a suitable model system and voltage measurement tools for in vivo biology. Here, we addressed this gap by utilizing a genetically stable zebrafish line, Tg (ubiquitin: ASAP1), and ASAP1 (Accelerated sensor of action potentials 1), a genetically encoded voltage indicator (GEVI). With light-sheet microscopy, we systematically investigated cell membrane potential (Vm) signals during different embryonic stages. We found cells of zebrafish embryos showed local membrane hyperpolarization at the cleavage furrows during the cleavage period of embryogenesis. This signal appeared before cytokinesis and fluctuated as it progressed. In contrast, whole-cell transient hyperpolarization was observed during the blastula and gastrula stages. These signals were generally limited to the superficial blastomere, but they could be detected within the deeper cells during the gastrulation period. Moreover, the zebrafish embryos exhibit tissue-level cell Vm signals during the segmentation period. Middle-aged somites had strong and dynamic Vm fluctuations starting at about the 12-somite stage. These embryonic stage-specific characteristic cellular bioelectric signals suggest that they might play a diverse role in zebrafish embryogenesis that could underlie human congenital diseases.