Real-time Readings Research Articles

Variance of total dissolved solids and electrical conductivity for water quality in Sabak Bernam

<span lang="EN-US">Water pollution is one of the most serious environmental problems in Malaysia. The most notable occurrence of pollution happened in Selangor. Currently, there are various water quality monitoring (WQM) methods to observe the quality of water. One of the methods used is the internet of things (IoT) for wireless sensor network technology to obtain real-time data measurement. In this study, the developed WQM system is equipped with a sensor that can measure total dissolved solid (TDS) and electrical conductivity (EC). Arduino UNO was used in this system as a microcontroller to interact with the sensor. The Wi-Fi module, ESP8266, was used to transfer the collected data to ThingSpeak, which acts as a cloud to store all the data. The results showed that both sample populations can be discriminated since the p-value is greater than 0.05 in the normality test, while in the paired sample t-test, the p-value is less than 0.05. In conclusion, this research provides an easier way to monitor water quality by taking up less time at less cost, as well as being reliable in giving real-time data reading.</span>

IOT BASED WEATHER MONITORING SYSTEM

The system proposed in this paper is an advanced solution for monitoring the weather conditions at a particular place and make the information visible anywhere in the world. The technology behind this is Internet of Things (IoT), which is an advanced and efficient solution for connecting the things to the internet and to connect the entire world of things in a network. Here things might be whatever like electronic gadgets, sensors and automotive electronic equipment. The system deals with monitoring and keeps track of temperature, humidity, wind speed and direction, rainfall amount etc. The system displays these readings in real time on a display. It also keeps track of historical information on an hourly and daily basis. This data can be display on LCD and sends the information to the web page and then plot the sensor data as graphical statistics. The data updated from the implemented system can be accessible in the internet from anywhere in the world.

Internet of Things based Control and Monitoring System for Koi Fish Cultivation

Water quality is an important factor for fish koi cultivation. Poor water quality such as inappropriate temperature, pH, and turbidity can disrupt metabolic processes, inhibit growth and cause death in koi fish. Apart from that, feeding and checking water quality are still done manually. Because of this, we need a system that can monitor and control the feeding, temperature, and water quality according to the living environment of koi fish. In this study the system was built on an Android-based mobile application using the flutter framework. In addition, the system has a notification to provide information on changes in sensor readings in real time to users. The notifications are changes in temperature, pH, turbidity, water level, feed level and changes in control device modes. Testing the water temperature readings obtained a relative error value of 0,66%, water turbidity readings obtained an error value of 8,79%, water pH readings obtained a relative error value of 2,45%, water level readings obtained an error relative value of 1,57% and feed availability readings obtained an error value of 3,1%.

Preventing stillbirth from obstructed labor: A sensorized, low-cost device to train in safer operative birth.

98% of stillbirths occur in low- and middle- income countries. Obstructed labor is a common cause for both neonatal and maternal mortality, with a lack of skilled birth attendants one of the main reasons for the reduction in operative vaginal birth, especially in low- and middle- income countries. We introduce a low cost, sensorized, wearable device for digital vaginal examination to facilitate accurate assessment of fetal position and force applied to the fetal head, to aid training in safe operative vaginal birth. The device consists of flexible pressure/force sensors mounted onto the fingertips of a surgical glove. Phantoms of the neonatal head were developed to replicate sutures. An Obstetrician tested the device on the phantoms by performing a mock vaginal examination at full dilatation. Data was recorded and signals interpreted. Software was developed so that the glove can be used with a simple smartphone app. A patient and public involvement panel was consulted on the glove design and functionality. The sensors achieved a 20 Newton force range and a 0.1 Newton sensitivity, leading to 100% accuracy in detecting fetal sutures, including when different degrees of molding or caput were present. They also detected sutures and force applied with a second sterile surgical glove on top. The software developed allowed a force threshold to be set, alerting the clinician when excessive force is applied. Patient and public involvement panels welcomed the device with great enthusiasm. Feedback indicated that women would accept, and prefer, clinicians to use the device if it could improve safety and reduce the number of vaginal examinations required. Under phantom conditions to simulate the fetal head in labor, the novel sensorized glove can accurately determine fetal sutures and provide real-time force readings, to support safer clinical training and practice in operative birth. The glove is low cost (approximately 1 USD). Software is being developed so fetal position and force readings can be displayed on a mobile phone. Although substantial steps in clinical translation are required, the glove has the potential to support efforts to reduce the number of stillbirths and maternal deaths secondary to obstructed labor in low- and -middle income countries.

Aloud real- time reading of intensive care unit diaries: A feasibility study

ObjectivesMemories of frightening/delusional intensive care unit experiences are a major risk factor for subsequent psychiatric morbidity of critical illness survivors; factual memories are protective. Systematically providing factual information during initial memory consolidation could mitigate the emotional character of the formed memories. We explored feasibility and obtained stakeholder feedback of a novel approach to intensive care unit diaries whereby entries were read aloud to the patients right after they were written to facilitate systematic real time orientation and formation of factual memories. Research methodologyProspective interventional pilot study involving reading diary entries aloud. We have also interviewed involved stakeholders for feedback and collected exploratory data on psychiatric symptoms from patients right after the intensive care stay. SettingVarious intensive care units in a single academic center. Main outcome measuresFeasibility was defined as intervention delivery on ≥80% of days following patient recruitment. Content analysis was performed on stakeholder interview responses. Questionnaire data were compared for patients who received real-time reading to the historical cohort who did not. ResultsOverall, 57% (17 of 30) of patients achieved the set feasibility threshold. Following protocol adjustment, we achieved 86% feasibility in the last subset of patients. Patients reported the intervention as comforting and appreciated the reorientation aspect. Nurses overwhelmingly liked the idea; most common concern was not knowing what to write. Some therapists were unsure whether reading entries aloud might overwhelm the patients. There were no significant differences in psychiatric symptoms when compared to the historic cohort. ConclusionWe encountered several implementation obstacles; once these were addressed, we achieved set feasibility target for the last group of patients. Reading diary entries aloud was welcomed by stakeholders. Designing a trial to assess efficacy of the intervention on psychiatric outcomes appears warranted. Implications for Clinical PracticeThere is no recommendation to change current practice as benefits of the intervention are unproven.

A Review on a Milk Quality Detection and Analysis

The milk is the important nutrition for mortal being. The good quality milk should be free from the pollutants. Milk is substantially vended by original merchandisers as well as by super requests. still, in original areas to increase the volume of milk certain pollutants are added which may affect the nutritive quality of milk. Milk contamination is a social problem. The problem of contamination is faced by both Indian and foreign countries. Application of thinned milk causes severe health problems and a great concern to the food assiduity. The Country milk directors and consumers facing problem to find the quality of milk, accept the show of price and consumption. So, it's necessary to insure the quality of milk by measuring the vital parameters present in the milk and the pollutants that are added to the milk. Then we're measuring the different parameters of milk similar as pH, turbidity, conductivity, odor, temperature using detectors. Also, with the help of IOT( Internet of effects) process the milk assiduity should be suitable to shoot the real time reading information of milk to the government so that it helps to overcome the illegal effects similar as milk quality during the product of milk packet. This proposed system is enforced using At mega328 microcontroller. All the detectors arecombined to form compact and flexible system which dissect and classify the quality of milk into different grades and eventually affair displayed on TV screen. Problem faced in small journals and by the individualities can be averted by detecting the quality of milk, and help from causing the dangerous conditions by detecting the contamination of milk. husbandry is an important part of India and the dairy business is an overall benefit to India's business or frugality. Farmers force milk to dairy products and admit payments grounded on the chastity of the milk. As it's known, the world is moving presto now that people with further luxurious cultures are responding to trends and requirements. thus, there's a need to ameliorate the agrarian life of India. In milk, colorful factors are calculated, similar as fat, pH, and the asked rate of fat mass. The system calculates these parameters and the microcontroller reads the data and sends to android phone. The Blynk app installed on the phone can be used to perform billing computations and calculate the diurnal payments. This technology offers a clever mobile operation that help in determining the quantum of fat in milk. Both Arduino boards and microcontrollers may use the detector. The fashion for relating fat in milk samples is veritably affordable. The sector offers fair rates to growers and gives governments with real- time dairy value andproportions through the Internet of effects(IoT) procedure.

IoT-Based Smart Wireless Communication System for Electronic Monitoring of Environmental Parameters with a Data-Logger

As the transition toward automated industrial environments gains momentum, the necessity for dependable, real-time environmental monitoring systems becomes increasingly critical. Addressing this urgent need, this paper unveils a sophisticated IoT-based wireless communication system specifically engineered for electronic monitoring of key environmental parameters. An Arduino Nano microcontroller is central to the system’s design, which interfaces with a diverse suite of sensors to monitor temperature, humidity, gas concentrations, and even emergency conditions like fire hazards. Leveraging the capabilities of an nRF24L01 wireless module, the system transmits these multi-faceted sensor readings in real time to a control unit. Once received, the data is vividly displayed on an (organic light emitting diode) OLED screen and logged onto a Micro-SD card for subsequent analysis and historical trend monitoring. Additionally, the system features audio-visual alerts through an electric buzzer and LED, providing instantaneous warnings in critical situations. Notably, the sensor data undergoes rigorous validation by being compared with reference values obtained from NASA’s official databases, ensuring high accuracy and reliability. This comprehensive solution significantly advances industrial safety and efficiency, serving as a robust tool for monitoring and responding to environmental changes in real time.

PMA-Treatment of Human Monocytes Induces a M1 Phenotype in Adherent Macrophages

Background: Human monocyte lines are widely used in basic research as model of inflammation, mostly following adherence with phorbol 12-myristate 13-acetate (PMA). However, the SC line, of normal human monocytes is not well documented, unlike tumour-derived cell lines, such as THP-1. Aim: The purpose of this study was to determine the phenotype of adherent macrophages, induced after the treatment with PMA in three different concentrations, starting from the most widely reported concentration in the literature. Methods: Normal human monocytes SC (ATCC CRL-9855) were routinely maintained according to manufacturer’s instructions. Cells were treated with Phorbol 12-myristate 13-acetate (PMA Sigma Aldrich P1585), in concentrations of 200 ng/mL, 100 ng/mL, 25 ng/mL and adhesion was documented using an Evos phase-contrast inverted microscope. Cell behaviour was validated by real-time impedance readings. The adhered cells were treated with bacterial lipopolysaccharide (LPS) in concentrations of 50 ng/mL (mimicking chronic inflammation) and 1 μg/mL (mimicking acute inflammation). The supernatant was collected twice, after 4 hours, respectively after 18 hours of treatment with LPS. A screening of pro- and anti-inflammatory cytokines was performed using the multiplexing platform Luminex 200. ELISA tests were performed to validate the cytokines secretion: IL-6, IL-8, IL-10, IL-23 and TNF-ɑ, using a LEGEND MAX Human ELISA kit specific to each cytokine. Results: Cell adhesion was studied by time-lapse microscopy for 48 hrs. The lowest concentration of PMA which induced cell adherence was 25 ng/mL. Multiplex screening of cytokines showed a pro-inflammatory phenotype of macrophages stimulated with LPS. This finding was validated by ELISA tests for IL-6, IL-8, IL-23 and TNF-ɑ (as pro-inflammatory cytokine) and IL-10 (an anti-inflammatory molecule). For the first category, we noticed a time-dependent response, present in adherent macrophages, but not in circulating monocytes. Regarding the second category of cytokines, the secretion is present only for the adhered and LPS treated cells. It is also present in a time-dependent manner (a higher concentration can be noticed in the collected supernatant after 18 hours of treatment compared with the one collected after 4 hours of treatment). Conclusion: The macrophages obtained from normal human monocytes with PMA are M1 type, regardless of the concentration used for differentiation.

상호사고 관점에서 화상 도구 기반 실시간 독서 토론의 언어적 상호작용 양상 분석

Objectives The purpose of this study was to find out how interthinking conditions emerged in zoom-based real-time reading discussion of elementary school students.
 Methods Of the 10 sessions of zoom-based real-time reading discussion conducted at the J Children's Library in J-gu, Seoul, verbal interaction of the 2nd, 6th, 8th, and 10th class were recorded, transcribed and analyzed qualitatively and quantitativey to the criteria of conditions for forming Interthinking Development Zone.
 Results The basic rules for forming Interthinking Development Zone were not explicitly provided. And the teacher-led cumulative talk and the characteristics of contextualization were more or less formulated. The speech to promote interthinking was used voluntarily by teachers and had impact on students. But the teacher-led conversation were dominantly appeared in this situation.
 Conclusions As conditions for successful Interthinking formation in zoom-based real-time reading discussion, basic rules for interaction agreed upon by the participants, various forms of cumulative talking and listening using online tools, and capability for contextualization are prepared by all learners and teachers.

An Advanced Internet of Things System for Heatstroke Prevention with a Noninvasive Dual-Heat-Flux Thermometer.

Heatstroke is a concern during sudden heat waves. We designed and prototyped an Internet of Things system for heatstroke prevention, which integrates physiological information, including deep body temperature (DBT), based on the dual-heat-flux method. A dual-heat-flux thermometer developed to monitor DBT in real-time was also evaluated. Real-time readings from the thermometer are stored on a cloud platform and processed by a decision rule, which can alert the user to heatstroke. Although the validation of the system is ongoing, its feasibility is demonstrated in a preliminary experiment.

The self-powered electrochemical biosensing platform with multi-amplification strategy for ultrasensitive detection of microRNA-155

A self-powered biosensor (SPB) was constructed for the ultra-sensitive detection of microRNA-155 (miR-155) by combining a capacitor/enzymatic biofuel cell (EBFC), a strategy of rolling circle amplification (RCA) and a digital multimeter (DMM). The experimental results show that the sensitivity of the assembled EBFC-SPB can reach 15.85 μA/pM with the action of matching capacitor, which is 513% of that without capacitor (3.09 μA/pM). This achieves the first signal amplification. Furthermore, when the target miR-155 triggers RCA, electrons are continuous generated and flow to the biocathode through the external circuit to catalyze the reduction of oxygen and release [Ru(NH3)6]3+ electron acceptor. This achieves the second signal amplification. Finally, DMM is used to convert the signal into instantaneous current and amplify it for real-time reading. This achieves the third signal amplification. Therefore, the limit of detection (LOD) of the developed biosensor is as low as 0.17 fM (S/N = 3), and the linear range is between 0.5 fM and 10,000 fM, indicating that the EBFC-SPB has a broad application prospect for cancer marker of miR-155 with ultrasensitive detection.

Wearable microneedle array-based sensor for transdermal monitoring of pH levels in interstitial fluid

Microneedle-based wearable sensors offer an alternative approach to traditional invasive blood-based health monitoring and disease diagnostics techniques. Instead of blood, microneedle-based sensors target the skin interstitial fluid (ISF), in which the biomarker type and concentration profile resemble the one found in the blood. However, unlike blood, interstitial fluid does not have the same pH-buffering capacity causing deviation of pH levels from the physiological range. Information about the skin ISF pH levels can be used as a biomarker for a wide range of pathophysiological conditions and as a marker for the calibration of a wearable sensor. The ISF pH can significantly affect the detection accuracy of other biomarkers as it influences enzyme activity, aptamer affinity, and antibody-antigen interaction. Herein, we report the fabrication of a high-density polymeric microneedle array-based (PMNA) sensing patch and its optimization for the potentiometric transdermal monitoring of pH levels in ISF. The wearable sensor utilizes a polyaniline-coated PMNA having a density of ∼10,000 microneedles per cm2, containing individual microneedles with a height of ∼250 μm, and a tip diameter of ∼2 μm. To prevent interference from other body fluids like sweat, an insulating layer is deposited at the base of the PMNA. The wearable pH sensor operates from pH 4.0 to 8.6 with a sensitivity of 62.9 mV per pH unit and an accuracy of ±0.036 pH units. Furthermore, testing on a mouse demonstrates the ability of the PMNA to provide a real-time reading of the transdermal pH values. This microneedle-based system will significantly contribute to advancing transdermal wearable sensors technology, simplifying the fabrication process, and improving the cost-effectiveness of such devices.

Hybrid magnetic resonance and optoacoustic tomography (MROT) for preclinical neuroimaging

Multi-modal imaging is essential for advancing our understanding of brain function and unraveling pathophysiological processes underlying neurological and psychiatric disorders. Magnetic resonance (MR) and optoacoustic (OA) imaging have been shown to provide highly complementary contrasts and capabilities for preclinical neuroimaging. True integration between these modalities can thus offer unprecedented capabilities for studying the rodent brain in action. We report on a hybrid magnetic resonance and optoacoustic tomography (MROT) system for concurrent noninvasive structural and functional imaging of the mouse brain. Volumetric OA tomography was designed as an insert into a high-field MR scanner by integrating a customized MR-compatible spherical transducer array, an illumination module, and a dedicated radiofrequency coil. A tailored data processing pipeline has been developed to mitigate signal crosstalk and accurately register image volumes acquired with T1-weighted, angiography, and blood oxygenation level-dependent (BOLD) sequences onto the corresponding vascular and oxygenation data recorded with the OA modality. We demonstrate the concurrent acquisition of dual-mode anatomical and angiographic brain images with the scanner, as well as real-time functional readings of multiple hemodynamic parameters from animals subjected to oxygenation stress. Our approach combines the functional and molecular imaging advantages of OA with the superb soft-tissue contrast of MR, further providing an excellent platform for cross-validation of functional readings by the two modalities.

Biomechanical Sensing Systems for Cardiac Activity Monitoring.

Cardiovascular disease is consistently ranked high among the causes of death on a global scale. Monitoring of cardiovascular signs throughout the course of a long period of time and in real time is necessary in order to discover anomalies and begin early intervention at the appropriate time. To this purpose, a significant amount of interest among researchers has been directed toward the creation of flexible sensors that may be worn or implanted and are capable of constant, immediate observation of a variety of main physiological indicators. The real-time readings of the heart and arteries' pressure fluctuations can be reflected directly by mechanical sensors, which are one of the many types of sensors. Potential benefits of mechanical sensors include excellent accuracy and considerable versatility. Capacitive, piezoresistive, piezoelectric, and triboelectric principles are the foundations of the four types of mechanical sensors that are discussed in this article as recent developments for the purpose of monitoring the cardiovascular system. The biomechanical systems that are present in the cardiovascular system are then detailed, along with their monitoring, and this includes blood and endocardial pressure, pulse wave, and heart rhythm. In conclusion, we examine the usefulness of the use of continuous health monitoring for the treatment of vascular disease and highlight the difficulties associated with its translation into clinical practice.

BS-Join: A novel and efficient mixed batch-stream join method for spatiotemporal data management in Flink

The new computing model, mixed batch-stream data processing, plays a crucial role in big spatiotemporal data managements. As the core of the above computing method, mixed batch-stream data join has high requirements on the throughput and latency due to the coexistence of two types of data sources. Apache Flink is the most suitable distributed system for mixed batch-stream data join, with lower latency than the join calculation model based on Hadoop and Spark, and it simulates remote real-time reading of batch data sources and completes join calculation with the DataStream API. However, as the degree of parallelism increases, frequent remote data reads will cause huge disk and communication pressure, thereby reducing the job efficiency and scalability. To make things trickier, the above effects are further amplified when simulating complex operations such as range joins. Aiming at the above difficulties and the characteristics of mixed batch-stream data join, a cache-based framework supporting mixed batch-stream join computing natively is proposed, which increases the search speed in the process of data join by building indexes in batch data sources. Meanwhile, for equijoin and range join, an optimization mechanism based on hotspot awareness and an optimization mechanism based on skip list are proposed respectively to further improve the job efficiency. In summary, the advantages of our work are highlighted as follows: (1) The proposed framework enables Flink to natively support mixed batch-stream data join, and can improve throughput by 5 times and speedup by 4 times; (2) The optimization mechanism based on hotspot awareness can further improve the efficiency of equijoin; (3) Compared with range queries by traditional Operators in Flink, the throughput can be increased by 6 times while the latency is reduced by 45%.

A high-quality genome assembly of Lactarius hatsudake strain JH5.

Lactarius hatsudake is a species of Lactarius commonly found in pine forests, is edible with a delicious and nutritious fruiting body, and exhibits medicinal properties. It is an ideal natural multifunctional food with bioactive components including fungal polysaccharides, crude fiber, unsaturated fatty acids, nucleic acid derivatives, various amino acids, and vitamins. However, biological and genomic analyses of this mycorrhizal mushroom are sparse, thereby hindering large-scale cultivation. Previously, we isolated and screened L. hatsudake JH5 strains and have applied our garnered knowledge to the large-scale cultivation of mycorrhizal seedlings. In this study, we produced a high-quality genome assembly of L. hatsudake JH5 by combining Illumina paired-end and PacBio single molecule real-time sequencing, resulting in PacBio single molecule real-time reads of 7.67 Gb and Illumina Pair-End reads of 1,560 Mb. Based on the distribution of k-mer frequencies, the genome size of this strain was estimated to be 63.84 Mb (1.14% heterozygosity). Based on de novo genome assembly, the final genome size was determined to be 76.7 Mb, with scaffold N50 of 223.2 kb and N90 of 54.5 kb, and a GC content of 54.38%. BUSCO assessment showed that genome completeness was 89.0%. The N50 length of the JH5 genome was 43.6% longer than that of the previously published L. hatsudake MG20 genome. This high-quality L. hatsudake genome assembly will facilitate research on the functional genome, molecular breeding, yield enhancement, and sustainability of L. hatsudake cultivation.

Exploring the Relationship Between Teacher and Multilingual Student Discourse During Small Group Text-Based Discussions

Few studies investigate how teacher discourse moves relate to subsequent student discourse moves in real-time small-group reading instruction with multilingual learners (MLLs). Grounded in sociocultural theory and classroom discourse research, this study examines how fourth-grade MLLs engage in reasoning discourse during text-based discussions. We argue that by examining reasoning discourse holistically - beyond speaker turns - we can capture teacher-talk moves that facilitate or constrain student reasoning. This examination illuminates discourse practices such as “procedural instruction” and “reference to text,” with important consequences for MLLs. Our study has implications for scholarship analyzing classroom talk and literacy educators facilitating discussions where MLLs engage in sophisticated and complex reasoning discourse.

Blockchain-Based Decentralized Replay Attack Detection for Large-Scale Power Systems

Large-scale power systems are composed of regional utilities with assets that stream sensor readings in real time. In order to detect cyberattacks, the globally acquired, real-time sensor data needs to be analyzed in a centralized fashion. However, owing to operational constraints, such a centralized sharing mechanism turns out to be a major obstacle. In this article, we propose a blockchain-based decentralized framework for detecting coordinated replay attacks with full privacy of sensor data. We develop a Bayesian inference mechanism employing locally reported attack probabilities that is tailor made for a blockchain framework. We compare our framework to a traditional decentralized algorithm based on the broadcast gossip framework both theoretically as well as empirically. With the help of experiments on a private Ethereum blockchain, we show that our approach achieves good detection quality and significantly outperforms gossip-driven approaches in terms of accuracy, timeliness, and scalability.

Low Budget Respirometer Chamber Design Based on Wireless Sensor Network

Fresh fruit respiration information is essential optimizing food storage systems. Meanwhile, respiration is defined as the process of oxygen production and carbon dioxide release during storage in a closed respiratory chamber. Therefore, this study aims to design a low-budget computerized respiratory chamber for enhancing fruit packaging and storage system. Real-time fruit respiration can be measured by applying wireless gas sensors network. The respirometer consisted of 3,600 mL glass jar with a screw stainless lid, while the electrochemical and non-dispersive infrared sensors were mounted on the cover of the glass jar for collecting data on the oxygen, carbon dioxide, and temperature during mangoes’ respiration. Arduino USB port was used to record all measured parameters consisting of oxygen (%) and carbon dioxide concentrations (ppm, as well as temperature in the respiration chamber. Additionally, a controlled cooling chamber was applied to maintain the temperature during storage, while data communication was supported by Xbee S2C based on radio frequency. According to the respirometer real-time reading, there was a decrease in oxygen concentration caused by increasing carbon dioxide release with temperature. The low-budget respirometer was used to measure the respiration rate and record the data through a wireless sensor network system. The data plot shows that the respiration rate increased as the storage temperature and the respiratory quotient ranged from 0.32-0.44.

A Direct-Reading MEMS Conductivity Sensor with a Parallel-Symmetric Four-Electrode Configuration.

This work proposes a design for a direct-reading conductivity sensor with a parallel symmetrical four-electrode structure, which integrates a silicon-based platinum thin-film strip electrode and a serpentine temperature compensation electrode. The optimal structural parameters of the electrode were determined by finite element simulations performed via COMSOL Multiphysics. Next, the designed conductivity sensor chip was fabricated using MEMS technology, and subsequently, the conductivity measurement circuit was designed to test the fabricated sensor’s performance. In laboratory tests, the optimal AC excitation frequency was observed to be 1.067 kHz, while the maximum measurement range was 0–107.41 mS/cm and the measurement precision in low concentration range (0–76.422 mS/cm) was ±0.1 mS/cm. Furthermore, the maximum measurement error of the sensor evaluated using the National Center of Ocean Standards and Metrology was ±0.073 mS/cm. The designed sensor possesses the characteristics of high accuracy, high range, and miniaturization, and enables real-time reading of conductivity value and temperature compensation, which is of great significance for the on-site observation of the physical parameters of marine environment.