Humidity Parameters Research Articles

Implementation of Environmental Parameter Control System in Green House to Increase Vegetable Production

The use of green houses in plant cultivation is one way to approach optimal conditions for plant growth. Green houses are generally useful for protecting plants from extreme air temperatures. This requires further study of the smart features that will be built to support the concept of greenhouse agriculture. The development of automation technology is expected to help the monitoring system of parameters that affect the production of vegetable crops such as air temperature, and air humidity. These parameters will be monitored remotely using the Internet of Things (IoT) method. Based on the measurement results from the location at POLMED campus. For Medan Selayang the maximum temperature is 26.4oC and humidity is 68.8%. For the location in Medan Johor the maximum temperature is 25.4oC and humidity is 68.1%. For Medan Baru location, the maximum temperature is 25.1oC and humidity is 68.3%. For Medan Helvetia location, the maximum temperature was 24.7oC and humidity was 69%. Based on the test results, the temperature and humidity parameters can be monitored remotely by 106.4 km via the internet.

Thermal design of a thermoelectric refrigerator operating near room temperature using artificial neural network

The current study aimed to design and test a prototype of a thermoelectric cooler (TEC) using thermoelectric modules (TEM) operating near room temperature. The thermoelectric cooler utilized in this investigation has a maximum cooling power of 46 W and dimensions of 40 mm × 40 mm × 3.6 mm. After a series of measurements, the device temperature decreased from an ambient temperature of 19.6 °C to 1.6 °C, with a notable coefficient of performance around 0.9, achieved through the utilization of both serial and parallel connections. The secondary objective of this research was based on an artificial neural network (ANN) approach. An ANN model was constructed using an experimental database acquired from our thermoelectric refrigeration device. The input parameters of humidity, time, performance coefficient, cooling power, and heat dissipation were introduced into the model to enhance the cold temperature as the output. Using a multilayer perceptron (MLP), the experimental dataset was used for training, testing, and validating the ANN. The precision of the model was evaluated using three established statistical metrics: mean squared error (MSE), mean absolute percentage error (MAPE), and R-squared (R2).

Implementation of an IoT-based System for Monitoring Parameters and Tracking Transport Vehicles

The integration of Internet of Things (IoT) technology in vehicle monitoring systems has emerged as a promising solution for enhancing the efficiency, safety, and sustainability of transportation. Especially in refrigerated trucks, which transport fresh goods, monitoring parameters in the vehicle plays an important role in ensuring the quality of transported goods. These parameters can be monitored directly on the vehicle by the driver and at the same time, the manager needs to monitor remotely. This paper will present an IoT-based system to monitor critical parameters of vehicles, including temperature, humidity, fuel consumption, and positioning. The proposed system integrates a network of sensors within the vehicle to capture real-time data, which is transmitted to a centralized control unit for analysis and visualization. Through experiments, the effectiveness and reliability of the proposed system in providing accurate and timely information on vehicle parameters are demonstrated. The results highlight the potential of IoT solutions to revolutionize vehicle monitoring and management, bringing benefits and reducing costs in the transportation sector. Moreover, a discussion on the future trends and solutions in transportation and logistics will be presented.

Behavior and changes in rectal temperature in dogs and cats undergoing hyperbaric oxygen therapy: clinical data review

Antunes BN, Müller DCM, Milech V, Caye P, Degregori E, Vargas D, Reinstein RS, Brun MV. Behavior and changes in rectal temperature in dogs and cats undergoing hyperbaric oxygen therapy: clinical data review. Undersea Hyperb Med. 2024 Fourth Quarter; 51(4):361-367. The assessment of rectal temperature and behavior is an important parameter in all patients for whom hyperbaric oxygen (HBO2) therapy is used. The study aims to verify if there is less reduction in body temperature after HBO2 therapy in restless patients and their behavior during the therapeutic session. Clinical data from 217 HBO2 therapy sessions with 2 to 2,5 atmospheres absolute (ATA) were reviewed under therapy protocols of 30 (P1) or 45 (P2) minutes, covering 29 canines and 13 felines. Behavioral data, initial rectal temperature (iRT), final (fRT), and variation between them (RTv) of each patient were recorded. Parameters of oxygen concentration, humidity, temperature, and chamber flow rate were also recorded. Three of 217 patients experienced major adverse effects (seizure and auto-trauma). 144/217 HBO2 therapy session records were selected for statistical analysis. In P1 sessions, 33.3% of the canine and 33.3% of the feline patients were restless. In P2 sessions, 40.7% of the canine and 28.1% of the feline patients were restless. The study did not observe a correlation between vRT and patients' behavior (p> 0.089) or differences in vRT between quiet and restless patients. There was a difference between iRT and fRT only in canines submitted to P1 (p<0.001) and felines submitted to P2 (p<0.001). Older canine patients were more restless than young canine patients at P1 (p= 0.02). We conclude that there may be a reduction in the fRT of dogs and cats submitted to 2 ATA for 30 minutes and 2.5 ATA for 45 minutes, respectively. Keywords: adverse effect; canine and feline; chamber; monoplace; oxygen

Advancements in Artificial Intelligence-mediated Fabrication of 3D, 4D, and 5D Printed for Fabrication of Drug Delivery Formulations

: One of the most powerful and inventive fabrication techniques used to create novel structures and solid materials using precise additive manufacturing technology is 5D and 4D printing, which is an improved version of 3D printing. It catches people's attention because of its capacity to generate fast, highly complex, adaptable product design and fabrication. Real-time sensing, change adaptation, and printing state prediction are made possible by this technology with the use of artificial intelligence (AI). The process of 3D printing involves the use of sophisticated materials and computer-aided design (CAD) with tomography scanning controlled by artificial intelligence (AI). The printing material is deposited according to the specifications of the file, typically in STL format; however, the printing process takes time.4D printing, which incorporates intelligent materials with time as a fourth dimension, can solve this drawback. About 80% of the time will be saved by this technique's self-repair and self-assembly qualities. One limitation of 3D printing is that it cannot print complex shapes with curved surfaces. However, this limitation can be solved by using 5D printing, which uses rotation of the print bed and extruder head to achieve additive manufacturing in five different axes. Some printed materials are made sensitive to temperature, humidity, light, and other parameters so they can respond to stimuli. With its effective and efficient manufacturing for the necessary design precision, this review assesses the potential of these procedures with AI intervention in medicine and pharmacy.

Spatial and Temporal Characterization of Near Space Temperature and Humidity and Their Driving Influences

Near space refers to the atmospheric region 20–100 km above Earth’s surface, encompassing the stratosphere, mesosphere, and part of the thermosphere. This region is susceptible to surface and upper atmospheric disturbances, and the atmospheric temperature and humidity profiles can finely characterize its complex environment. To analyze the relationship between changes in temperature and humidity profiles and natural activities, this study utilizes 18 years of temperature and water vapor data from the TIMED/SABER and AURA/MLS instruments to investigate the variations in temperature and humidity with altitude, time, and spatial distribution. In addition, multiple linear regression analysis is used to examine the impact mechanisms of solar activity, the El Niño–Southern Oscillation (ENSO), and the Quasi-Biennial Oscillation (QBO) on temperature and humidity. The results show that in the mid- and low-latitude regions, temperature and water vapor reach their maxima at an altitude of 50 km, with values of 265 K and 8–9 × 10⁻⁶ ppmv, respectively; the variation characteristics differ across latitudes and altitudes, with a clear annual cycle; the feedback effects of solar activity and the ENSO index on temperature and humidity in the 20–40 km atmospheric layer are significantly different. Among these factors, solar activity is the most significant influence on temperature and water vapor, with response coefficients of −0.2 to −0.16 K/sfu and 0.8 to 4 × 10⁻⁶ ppmv/sfu, respectively. Secondly, in the low-latitude stratospheric region, the temperature response to ENSO is approximately −1.5 K/MEI, while in the high-latitude region, a positive response of 3 K/MEI is observed. The response of water vapor to ENSO varies between −1 × 10⁻⁷ and −4 × 10−⁷ ppmv/sfu. In the low-latitude stratospheric region, the temperature and humidity responses to the QBO index exhibit significant differences, ranging from −1.8 to −0.6 K/10 m/s. Additionally, there are substantial differences in responses between the polar regions and the low-latitude equatorial region. Finally, a three-dimensional model coefficient was constructed to illustrate the influence of solar activity, ENSO, and QBO on temperature and humidity in the near space. The findings of this study contribute to a deeper understanding of the temperature and humidity variation characteristics in near space and provide valuable data and model references for predicting three-dimensional parameters of temperature and humidity in this region.

Modeling of the modern climatic range of <i>Cydalima perspectalis</i> (Lepidoptera, Crambidae) in Eurasia

Modeling of the modern climatic range of a dangerous plant pest of the genus Buxus L. box tree moth Cydalima perspectalis (Walker, 1859) is carried out in order to determine possible territories of its further expansion in Eurasia. Information on the loci of actual C. perspectalis detection both in native (East and South Asia) and invasive (Europe and West Asia) parts of the range was collected from various sources (species distribution databases and publications). Six bioclimatic (three temperature and three humidity) parameters are used as distribution predictors. Original methods for determining the number of pseudo-absence points and their selective generation are developed and applied. The final classification and partitioning of the space of bioclimatic factors is carried out using gradient boosting. The modern Eurasian climatic range of the box tree moth is calculated and mapped. It is shown that the invasion has not yet reached its limits and there are a number of territories in Eurasia where climatic conditions are favorable for the emergence of C. perspectalis populations both in the native part of the range (certain southern and eastern regions of China, the DPRK, the southern foothills of the Himalayas) and in its invasive part (Northern and Eastern Europe, Caucasus, and Turkey). A comparative assessment of the importance of different climatic factors in determining the box tree moth distribution area is given. It has been found out that the sum of the driest month precipitation is of greatest importance for constructing a model of the C. perspectalis climatic range (47.6%). A significant difference in climatic conditions between the native and invasive parts of the range is revealed and assumptions about the possible causes of its occurrence are made.

Features of Providing Air Temperature and Humidity Parameters in the Engine Room Working Area at Sewage Pumping Stations

Statement of the problem. There is an important task for engineers to improve the working conditions of workers in industrial facilities. The waste water system includes a large number of structures with different temperature and humidity microclimate characteristics. The possibility has been discussed to improve these characteristics by redistributing air flows in the engine room of a city sewage pumping station with PLI panel. Results. There are the results of the temperature and humidity microclimate parameters research in the working area of the engine room at a high-voltage sewage pumping station which is located in Moscow. The author has proved the possibility of use the cooled air from the machine room lower level in a high-voltage pumping station at the machine room main working area. It has been described the calculation features of the heat transfer coefficients in the proposed model for local ventilation at the main technological working area. It has been described the results of temperature and humidity parameters instrumental study in the main working area and the lower level. Conclusion. Thelocal ventilation systems could be used for the working area, where an employee performs repair work of the main technical equipment in a sewage pumping station. The balanced mathematical thermal model includes PLI panel’s potential location.

Influence of Traditional Wall Façade from Taneyan Lanjhang House to Thermal Sensation

<p><em>Of the various ethnic groups that comprise Indonesia, Madurese ethnic belongs to the top five in ethnic group population numbers in Indonesia. As an ethnic group, Madurese developed a traditional settlement called natively Taneyan Lanjhang (TL). TL is described as a specific pattern settlement that follows local and Islamic-influenced cultural norms. This research aims to find local wisdom properties in tectonics configuration in Bangsal housing unit concerning thermal comfort and sensation aspect of a vernacular design. The study is using quantitative method with field observation using lidar scanner, hot-wire anemometer and model simulation using computational fluid dynamics. The final result of the study is finding a correlation between closing and opening wall configuration related to thermal comfort defined by airflow, temperature and relative humidity parameter. </em></p>

Optimal Determining Air Supply Humidity for Multi-Location Demands Under Different Objectives in an Indoor Moisture Environment: A Comprehensive Method and Case Study

Within high-precision indoor environments, such as semiconductor fabrication or textile plants, humidity control is paramount for preserving product integrity and reducing energy expenditure. The non-uniform indoor air environment poses a significant challenge in achieving humidity regulation that meets the distinct requirements of various locations. Traditional feedback control mechanisms may lead to instability, overshooting, and oscillation in indoor parameters. This paper proposes a comprehensive method to address humidity assurance issues in high-precision indoor environments by establishing analytical expressions that link the demand parameters at different locations with air supply parameters. Using a case study, this paper examines several typical operational scenarios with diverse control objectives, including minimizing dehumidification energy consumption, minimizing air supply humidity adjustment values, and constraints on adjustable air supply inlets. This method enables rapid calculation of air supply humidity and regulation of humidity parameters at multiple locations within the indoor environment. It considers various locations, requirements, optimization targets, and precision, demonstrating that it can quickly determine the optimal air supply parameters based on the objective function. This method facilitates rapid adjustment and high-precision assurance of different humidity requirements at multiple locations, making it suitable for high-precision design and control of indoor humidity environments.

Classification and recognition method of rice situation based on gray correlation degree

Grain storage is a complex process, affected by factors such as mold, temperature, humidity, and moisture. The use of multiple sensors to detect changes in rice pile parameters has gained prominence as a means to ensure the accuracy and timeliness of grain condition monitoring. However, the current technology does not effectively utilize data. The assessment criteria primarily rely on grain temperature, and the analysis of grain condition is simplistic. Additionally, it fails to adequately integrate information on temperature, humidity, moisture, gas concentration, and other parameters of the grain pile to form a unified assessment result. To address the isolated and one-sided reaction of various parameters in the grain pile, this thesis conducts research on the storage characteristics of heating, condensation, and mold condition. It combines the information fusion of temperature, humidity, moisture, and CO2 with normal grain conditions, constructs an assessment model based on the classification and identification of grain conditions under gray correlation, and achieves real-time dynamic assessment of the state of the grain pile. The experimental results show that the assessment model based on gray correlation can accurately discriminate between normal and mold conditions, but the accuracy in distinguishing heating and condensation still requires improvement. The overall recognition rate of the four types of grain conditions is 79%, which demonstrates the effectiveness of the model in identifying abnormal grain states.

Application of Experimental Studies of Humidity and Temperature in the Time Domain to Determine the Physical Characteristics of a Perlite Concrete Partition

These days, the use of natural materials is required for sustainable and consequently plus-, zero- and low-energy construction. One of the main objectives of this research was to demonstrate that pelite concrete block masonry can be a structural and thermal insulation material. In order to determine the actual thermal insulation parameters of the building partition, in situ experimental research was carried out in real conditions, taking into account the temperature distribution at different heights of the partition. Empirical measurements were made at five designated heights of the partition with temperature and humidity parameters varying over time. The described experiment was intended to verify the technical parameters of perlite concrete in terms of its thermal insulation properties as a construction material used for vertical partitions. It was shown on the basis of the results obtained that the masonry made of perlite concrete blocks with dimensions of 24 × 24.5 × 37.5 cm laid on the mounting foam can be treated as a building element that meets both the structural and thermal insulation requirements of vertical single-layer partitions. However, it is important for the material to work in a dry environment, since, as shown, a wet perlite block has twice the thermal conductivity coefficient. The results of the measurements were confirmed, for they were known from the physics of buildings, the general principles of the formation of heat and the moisture flow in the analysed masonry of a perlite block. Illustrating this regularity is shown from the course of temperature and moisture in the walls. The proposed new building material is an alternative to walls with a layer of thermal insulation made of materials such as polystyrene or wool and fits into the concept of sustainable construction, acting against climate change, reducing building operating costs, improving living and working conditions as well as fulfilling international obligations regarding environmental goals.

Зоотехния лабораторных хомяков

One of the most common types of rodents kept in the laboratory and used as test systems for research is the Syrian hamster. At the same time, a responsible approach to the conditions of accommodation, as well as to feeding and reproduction of this species of animals guarantees a healthy population, which, in turn, is necessary for the correct interpretation of the data obtained during the experiments. The purpose of this review is to conduct a traditional analysis of the scientific literature on the animal science of laboratory hamsters. The search for publications was performed in the PubMed and Google Scholar databases. The review included publications available for search on February — May 2024. The review examines the zootechnical aspects of keeping a Syrian hamster in a research laboratory, including the recommended parameters of maintenance cells, microclimate conditions, including temperature, humidity, ventilation and lighting, as well as nutrient requirements and reproduction features of this animal species. Proper maintenance and feeding of hamsters used in research are of great importance for animal welfare, the collection of reliable research data, for the health and safety of animal care personnel, growth, reproduction and the health of the animals themselves. When analyzing the literature data, the main recommendations for the maintenance of Syrian hamsters in laboratory conditions were collected, taking into account all zootechnical needs for their placement and reproduction.

Average Wind Speed Prediction in Giresun-Kümbet Plateau Region with Artificial Neural Networks

In order to estimate the electricity generation capacity and schedule the supply for vendor needs, wind speed prediction is crucial for wind power plant frameworks. Prior to the installation of the wind power plants, a reliable wind behaviour model is neccesary. To have such a model, wind data is recorded periodically. In this study, hourly recorded meteorological data of actual pressure, relative humidity, temperature, wind direction and average wind speed for the year 2023 were obtained from the General Directorate of Meteorology for the Kümbet plateau region of Giresun province. The data is used to accurately predict the future wind speed for the region. Matlab Artificial Neural Networks (ANN) is utilized. Actual pressure, relative humidity, temperature and wind direction parameters are defined as input in the prediction process. 85% of the data set is used as training data and remainin 15% data set is used for testing data. An optimization process is applied to determine the number of hidden layers to have the prediction value with the smallest error. Bayesian Regularization training process was performed by seeing that the hidden layer has the lowest error at 90 neurons. Performance evaluations are performed with Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Pearson Correlation Coefficient (R) metrics. The values of the metrics for the test data are 26.7137, 5.1685, 3.5055 and 0.7457 respectively. The results show that, ANN based model is useful for the wind speed prediction over the region.

Utilizing IoT-Enhanced Multilayer Perceptron and Run Length Encoding for Classifying Plant Suitability Based on pH and Soil Humidity Parameters

This research proposes an IoT-based system for classifying plant suitability using pH data and soil humidity parameters. The system utilizes Run-Length Encoding (RLE) to compress sensor data, which is transmitted to a database server via the Esp8266 module. A Multilayer Perceptron (MLP) algorithm is employed to classify the data, achieving an accuracy of 0.82 with only two parameters. The classification results are displayed on a website, providing real-time recommendations for farmers. The system's performance is evaluated using a dataset from Kaggle. The Kaggle dataset contains 2200 instances for 22 different plants and the results show that the proposed system can effectively classify plant suitability based on environmental factors. This research contributes to the development of IoT-based recommendation systems for precision agriculture, and future studies can build upon this work to improve accuracy and quality.

Evaluating influence of weather on Ascochyta blight severity in chickpea using correlation network, regression and principal component analysis

Aim: Weather parameters play a critical role in the survival and propagation of the causal pathogen Ascochyta rabiei. In the absence of vertical host resistance, the present study was designed to explore the weather-disease interrelationship for effective disease management. Methodology: Field experiments were conducted with three chickpea cultivars and three sowing times for two years. The relationship between the percent severity index (PSI) at weekly interval and observed weather data was explored using multivariate statistical techniques. Results: The correlation networks revealed that temperature and relative humidity parameters were negatively and positively associated with the blight PSI, respectively. Humid thermal ratio (HTR) significantly correlated with PSI among all three chickpea cultivars. The linear regression of PSI with weather variables exhibited a significant negative slope (β) with all thermal variables whereas a strong positive β was displayed with relative humidity and HTR. The Best subset multiple regression models further affirmed that PSI in three chickpea cultivars can be strongly predicted with models constituted with temperature, humidity and HTR. Principal component analysis showed that PC1 and PC2 explained 88.2% variability with weather variables affecting the PSI. The clustering of thermal and humidity condition parameters around the first two PCs explained their pivotal role in disease severity progress. Interpretation: The multivariate analysis revealed that air temperature, relative humidity and HTR had significant influence on periodic Ascochyta blight severity in chickpea crop. Present exploration will be vital in developing more targeted disease prediction and management strategies to secure chickpea production. Key words: Ascochyta blight, Best subset regression, Chickpea, Correlation network, Weather variables

A simultaneous detection method for oxygen concentration, temperature, and humidity parameters based on fiber Bragg grating string

Due to oxygen being one of the indispensable and most active gases in nature, the detection technology of oxygen-related physical quantities (concentration, humidity, temperature) is a necessary research content in gas sensing. Meanwhile, fiber optic sensors have been widely used in gas detection due to their small size and high-performance advantages. However, designing a highly accurate, cross-sensitive, discriminative method for detecting multiple oxygen parameters is challenging. In this study, a technique based on fiber Bragg grating (FBG) string for simultaneous identification and detection of oxygen multiple parameters is proposed. This method combines three FBGs in series for fusion and cladding design. Not only does it solve the interference of temperature on FBG, but it also achieves accurate simultaneous detection of three parameters. The experimental results indicate that the oxygen concentration sensitivity is 0.714 pm/ppm in the 300 ppm to 1800 ppm range. Within the 25 % to 75 % range, the air humidity sensitivity is 31.4 pm/RH. It is simultaneously equipped with temperature detection capability, with a 10.1 pm/°C sensitivity. The relative detection error in 20 experimental data sets does not exceed 0.45 %. Meanwhile, the sensor has excellent reproducibility and durability and can be widely applied in oxygen detection.

Simulation method of heat-mass transfer between hot wind and wet coating in the manufacturing process of pole piece

In order to improve the complex numerical calculation process for wet coating of pole piece, a three-dimensional numerical model of heat-mass transfer characteristics is established between hot wind and wet coating based on multi-field coupling theory of porous media and meshless parallel method, and its reliability is verified through literature data. Meanwhile, the difference calculation method and evaluation process are proposed for heat-mass transfer characteristics to solve this numerical model. The results show that the maximum errors are less than 14.7 % for this model. In addition, a scale modeling method is proposed to improve computational efficiency based on similarity theory. Meanwhile, the influences of different scale factors on temperature and humidity parameters are analyzed for wet coating. The results show that this method is accurate and reliable because the determination coefficient R2 of all parameters is more than 0.99. Meanwhile, compared with the calculation time of original model, the calculation efficiency increases by 44.6 % for the model with scale factor selected as 800. Finally, the variation and distribution of internal parameters are analyzed for wet coating during pore emptying process based on above simulation method. The results show that the variation trends of liquid film thickness, pore emptying rate, water saturation, gas saturation and effective gas diffusion coefficient are corresponding with the accelerated, uniform and decelerated drying processes of porous media. Meanwhile, the location of four-corner edges for wet coating is the weak link in heat-mass transfer process. Therefore, the heat-mass transfer characteristics for wet coating can be improved by increasing its initial thickness or adjust reasonable drying position in engineering.

Effects of Low-Pressure Systems on Temperature, Humidity, Egg Production, and Feed Utilization Efficiency in Large-Scale Poultry Houses during Summer.

Low-pressure systems (LPSs) are among the most critical weather systems, producing excessive precipitation that causes air temperatures to drop and rise considerably. Acute temperature changes directly affect poultry feed intake (FI) and laying performance. To explore the effects of LPSs on hens, the parameters of air temperature, relative humidity, egg production, and feed utilization efficiency were evaluated during different LPSs in three houses. Results indicated that about 2.8 ± 0.7 d, 2.4 ± 0.5 d, and 2.4 ± 0.5 d before the LPS landfall in houses 1, 2, and 3, respectively, the indoor air temperature started to decrease, with the average decreases being 1.7 °C ± 0.4 °C, 2.4 °C ± 0.6 °C, and 1.8 °C ± 0.4 °C, respectively. Significant differences were observed between different LPSs for reducing indoor air temperature (p < 0.05) in the three houses. In house 1, the egg production rates (EPRs) were decreased by 6.6% and 1.1% when LPSs 1 and 2 landed. The average egg weight (AEW) and FI during the LPS landfall were significantly higher than those before the LPS landfall (p < 0.01). Under successive LPSs landfall in the three houses, the EPRs initially reduced by 3.9%, 4.0%, and 0.5%, respectively, but the second LPS event increased the EPRs by 1.8%, 5.3%, and 1.0%, respectively. Furthermore, the LPS landfall increased the feed conversion ratio (FCRe) in the three houses, all above 2.00. In conclusion, LPSs can reduce heat stress, lower the EPRs, and lead to higher FI, FCRe, and AEW.

Shrinkage evolution and mechanism of self-curing concrete cooperatively cured with superabsorbent polymers and waterborne epoxy coatings

Shrinkage-induced cracking is a common phenomenon in concrete structures. To reduce concrete shrinkage, herein, a novel curing approach involving the concurrent application of internal superabsorbent polymers (SAPs) and external waterborne epoxy coatings (WECs) was adopted. Subsequently, the combined effects of the SAPs and WECs on the internal temperature, water retention behavior, relative humidity, and shrinkage performance of concrete were investigated. Furthermore, their underlying shrinkage-mitigation mechanisms were clarified and verified through mercury intrusion porosimetry tests. Results revealed that increasing the WEC application rates and number of spraying turns increased the relative humidities and reduced the shrinkage strains of the concrete specimens. The combined use of SAPs and WECs led to considerable reductions in the specimens’ humidity drop, water loss, and shrinkage values. The water losses of the concrete specimens exerted more considerable impacts on their relative humidity and shrinkage compared to their cumulative temperatures. Furthermore, the combination effects of the SAPs and WECs reduced the median pore diameters and increased the fractal dimensions of gel pores, thus triggered a reduce in capillary tension, and further mitigated the development of shrinkage strains. Overall, this study underscores the critical roles of evaporation, temperature, relative humidity, and pore-structure parameters on the shrinkage behavior of concrete. Additionally, it highlights the effectiveness of the combined application of SAP-based internal curing and WEC-based external curing, offering a feasible approach and technical support for reducing shrinkage in concrete structures.