Humidity Monitoring Research Articles

Effect Of Light Spectrum LED Lettuce on IOT-Based Indoor Farming

Lettuce (Lactuca sativa L.) is an economically important crop worldwide and one of the most popular species grown in indoor farming. Lettuce's fast growth and growing cycle make lettuce a model plant to study the interaction between plants and light. The influence of light is one of the fundamental environmental factors for plant growth and development. Light-emitting diodes (LEDs) have higher light efficiency and higher wear efficacy, leading to a reduction in associated heating compared to other artificial lighting sources, such as fluorescent lamps or sodium vapor lamps. This research aimed to determine different responses of the morphological response of lettuce by giving LED light spectrum with a single color spectrum difference and IOT-based temperature and humidity monitoring. This research used a t-student test with a level of 5% on the mean value of the white light spectrum with a yellow light on lettuce plants. The addition of the LED light spectrum produces a different response to the morphological parameters. The addition of the LED spectrum gave a response to the plant height variable, where the provision of a yellow LED light spectrum resulted in plant height which affected lettuce plants

Preparation and performance of NaTaO3/TiO2 humidity sensors with high responsivity

In this study, a high-performance nanocomposite NaTaO3/TiO2 humidity sensor was prepared using the hot solvent method, and its humidity sensitivity was analysed. Structural analysis indicated that the NaTaO3/TiO2 composite had a greater surface area than pristine NaTaO3. Consequently, the surface of the NaTaO3/TiO2 composite adsorbed more water molecules, resulting in enhanced humidity response. During the preparation of the composite, Ti3+ and oxygen vacancy defects formed in the NaTaO3/TiO2 composites, which contributed to the adsorption and desorption of water molecules. The Ti3+ and oxygen vacancies promoted the generation of H3O+ ions and shortened the response and recovery time of the NaTaO3/TiO2 sensor. Compared with the NaTaO3 or TiO2 individually, the aforementioned properties of the composite materials endow the sensor with superior humidity sensitivity performance. The NaTaO3/TiO2 humidity sensor exhibited impedance change over 4.5 orders of magnitude, high responsiveness (4011588%), lower hysteresis (8.5%), long-term stability, and response and recovery time (13 s and 9 s, respectively) in the relative humidity range of 11 to 95%. In addition, the complex impedance spectrum was analysed to elucidate the sensing mechanism. The preparation of the NaTaO3/TiO2 composite material provides a new direction for designing a high-sensitivity humidity monitoring resistance sensor based on NaTaO3.

Indoor air quality in Hungarian Passive Houses

The indoor air quality (IAQ) was investigated in 15 Passive Houses in the heating and non-heating seasons between 2019 and 2021 in Hungary. The concentrations of volatile organic compounds (VOCs), aldehydes, ozone, nitrogen dioxide, PM2.5 mass, carbon dioxide, bacteria, fungi, and pollen were measured together with the monitoring of temperature, relative humidity and air change rate (ACR). The IAQ varied considerably among the investigated buildings. Significant seasonal differences were obtained for all physical parameters (temperature, relative humidity, ACR), certain VOCs (benzene, α-pinene, limonene), acetaldehyde, and airborne fungi. Considerable health concern was associated with the indoor concentrations of PM2.5 mass and nitrogen dioxide in many cases based on the evaluation of IAQ in relation to potential adverse health effects, while the peak concentrations of other pollutants (e.g. trichloroethylene, α-pinene, certain aldehydes, fungi) were also of concern in a couple of cases. The median indoor/outdoor concentration ratios of benzene, PM2.5 mass, nitrogen dioxide, ozone and fungi indicated that these pollutants are mainly of outdoor origin, while the other VOCs, aldehydes and bacteria showed higher concentration indoors. Overheating, the lack of proper particle filters in the mechanical ventilation system, and low ACR and relative humidity were identified as frequent problems related to the building characteristics. The emissions from building materials and furniture, the proximity of construction works and unpaved roads, and the allergenic vegetation might considerably influence IAQ. The results highlight that risk reduction measures are needed to create healthier indoor environment in the Passive Houses.

The Monitoring and Management of an Operating Environment to Enhance the Safety of a Container-Type Energy Storage System.

The implementation of an energy storage system (ESS) as a container-type package is common due to its ease of installation, management, and safety. The control of the operating environment of an ESS mainly considers the temperature rise due to the heat generated through the battery operation. However, the relative humidity of the container often increases by over 75% in many cases because of the operation of the air conditioner which pursues temperature-first control. Humidity is a major factor which can cause safety issues such as fires owing to insulation breakdown caused by condensation. However, the importance of humidity control in ESS is underestimated compared to temperature control. In this study, temperature and humidity monitoring and management issues were addressed for a container-type ESS by building sensor-based monitoring and control systems. Furthermore, a rule-based air conditioner control algorithm was proposed for temperature and humidity management. A case study was conducted to compare the conventional and proposed control algorithms and verify the feasibility of the proposed algorithm. The results showed that the proposed algorithm reduced the average humidity by 11.4% compared to the value achieved with the existing temperature control method while also maintaining the temperature.

Role of polyaniline/molybdenum trioxide nanocomposites in tuning the characteristics of humidity sensors

AbstractReal time humidity monitoring is crucial in several fields such as pharmaceuticals, electronic device manufacturing, in agricultural irrigation system due to drastic changing climates and so forth. In this work, we studied humidity sensing behavior of molybdenum trioxide (MoO3) in composition with conductive polyaniline (PAni). The conductive PAni used in the present study was in the emeraldine salt (ES) form and was doped with amino tris‐methylene phosphonic acid (PAni‐ATMPA) as a potential candidate for humidity sensors. PAni‐ATMPA is synthesized by oxidative polymerization of aniline monomers and ATMPA in the ratio of 1:1. Thus synthesized PAni and hydrothermally synthesized MoO3 were mixed together to form nanocomposites. The synthesized composites were then used to fabricate planar sensors on alumina substrate with pre‐deposited silver electrodes. XRD analysis of synthesized MoO3 shows an orthorhombic crystal structure whereas synthesized PAni shows amorphous nature. FESEM analysis of synthesized MoO3 shows sheet‐type morphology. Different compositions of MoO3:PAni were prepared by varying MoO3 and PAni wt%. The fabricated sensors were then tested over the range of 20%–90% RH and concluded that the sensitivity of the composite is seen to be higher for the composite with 20% PANi and 80% MoO3 with response time, recovery time and the linearity 7 s, 4 s, 13–62 RH% respectively. The above mentioned parameters are found to be improved in the composites as a result of PAni addition to MoO3 than the pristine MoO3. The experimental knowledge demonstrates that the films showed good repeatability (with and reproducibility (with uncertainty). Altogether, these results indicate that it is possible to tune the humidity sensing characteristics by optimizing the amount of MoO3 and PAni in MoO3:PAni composite.

Monitoring of intergranular variables for predicting technical breakage of wheat grains stored in vertical silos

The increase in the silos temperature and intergranular relative humidity can alter the equilibrium moisture content of the grains mass causing losses. Thus, the objective was to evaluate the temporal monitoring of temperature, relative humidity, and intergranular carbon dioxide for the prediction of dry matter loss in wheat grains stored in vertical silos, using a mathematical model and machine learning algorithms. Under these conditions, wheat grains had a slight increase in metabolic activity, causing a dry matter loss of 0.035–0.041%. The intergranular temperature, relative humidity, and carbon dioxide results were similar to the measurements on the surface of the grain mass. It was concluded that the monitoring of temperature, relative humidity, and the concentration of carbon dioxide in the intergranular air indirectly and early determined the changes in the quality of wheat grains during storage. Although the metabolic activity of wheat grains was low, as the lots remained in hygroscopic equilibrium with moisture contents close to 12% (w.b.), the temporal detection characterized the loss of dry matter and the reduction of grain weight stored. Finally, the Artificial Neural Networks and Multiple Linear Regression model satisfactorily predicted the dry matter loss of stored wheat grain mass.

Design of intelligent temperature and humidity monitoring system based on STM32

In the closed warehouse environment, this paper designed an intelligent temperature and humidity monitoring system based on the modular design method to solve the problem that the product is easy to damage. Based on the interaction between the STM32 Main control chip and the upper computer, the warehouse temperature, humidity dual control, and other functions can be realized. Experimental results show that the design can timely control the temperature and humidity in the warehouse. Moreover, the system has the function of data broadcasting. Consequently, product quality can be guaranteed to a great extent.

Intelligent Multifunctional Sensing Systems based on Ordered Macro-Microporous Metal Organic Framework and Its Derivatives.

Compared with nanomaterials-based sensors with single function, the development of multifunctional sensors shows high potential in comprehensive monitoring of personal health and environment, intelligent human-machine interfaces, and realistic imitation of human skin in prosthetics. Ordered macro-microporous metal-organic frameworks (MOFs)-enabled flexible and stretchable electronics are promising candidates for integrated multifunctional sensing systems. Herein, a three-dimensional ordered macro-microporous zeolite imidazolate framework-8 (3DOM ZIF-8) for humidity sensing and the derived ZnO within a hierarchically ordered macroporous-mesoporous-microporous carbon matrix (ZnO@HOMC) for gas sensor is constructed. Benefit from hierarchically ordered macroporous-mesoporous-microporous structure, the active site is fully exposed, and the charge transfer is accelerated. As a result, the multifunctional sensing systems show ultrafast response and recovery speed (10 s and 34 s), high sensitivity (Rair /Rgas = 38.6@50ppm) to acetone, rapid humidity response speed (0.23 s) within changing humidity (RH 21%-99%), excellent stability and repeatability. Furthermore, in order to realize real-time monitoring of gas concentrations and humidity on mobile devices, an intelligent and portable sensor module is fabricated and wirelessly connected to a smartphone to effectively detect acetone concentration and humidity. This sensing technology shows fascinating applications in personal health, fitness tracking, electronic skins, artificial nervous systems, and human-machine interactions.

Freeze-drying Cannabis sativa L. using real-time relative humidity monitoring and mathematical modeling for the cannabis industry

Pre-freezing has an impact on the drying time and physiochemical properties of cannabis. This study investigated the relationship between sample mass reduction and relative humidity during freeze-drying and the effects of pre-freezing and freeze-drying temperature on cannabis drying kinetics, trichome structure, and color, in addition to cannabinoid and terpene concentrations. Three cannabis accessions, Qrazy Train, Qrazy Apple, and Qrazy Angel, were dried at 10°C, and 20°C, with different pre-freezing conditions (−20°C and −40°C). Pre-freezing rates of 0.13°C min−1 for both Qrazy Train and Qrazy Angel and 0.15°C min−1 for Qrazy Apple were recorded for pre-freezing at − 20°C and significantly (p < 0.05) increased by 73.5%, 71.2%, and 72.9% for Qrazy Train, Qrazy Apple, and Qrazy Angel, respectively, when inflorescence was pre-frozen at − 40°C. Rational regression model best explains the relationship between mass reduction and relative humidity during drying, while drying kinetics can be described using the Page and Logarithmic models. Total color changes ranged from 1.16 to 9.69 total color changes measured for all dried samples compared to respective fresh, undried samples were not significantly (p < 0.05) different. THCA concentrations for fresh, undried Cannabis sativa L. accessions ranged from 214.4 mg g−1 to 257.5 mg g−1; this was higher than their CBDA concentrations, ranging from 0.03 mg g−1 to 0.1 mg g−1. Freeze-drying increased [CBDA], [CBGA], and [CBG] in dried samples ranging from 0.45 mg g−1 to 0.38 mg g−1, 2.87 mg g−1 to 4.91 mg g−1, and 0.57 mg g−1 to 1.33 mg g−1, respectively. Mean terpene concentration ranged from 17.7 mg g−1 to 40.3 mg g−1. Irrespective of the pre-freezing condition or cannabis accession, drying at 20°C reduced drying time by 10.4–31.9%. Findings could be of industrial relevance for improving post-harvest processes while maintaining quality of this regulated crop.

Design and Implementation of A Simple Pot Watering Control System

People who like to care for plants need to take care of plants in addition to the work pressure, which consumes people's time and energy. To solve this problem, an intelligent pouring system based on STM32 and WiFi module ESP8266 was designed. The system took STM32F103 development board as the main control core, combined with ESP8266, soil moisture sensor, temperature and humidity sensor DHT11, photosensitive resistance and other sensors to carry out data transmission to realize temperature and humidity monitoring of flowers. The system can carry out local control through the terminal, realize manual mode control based on MQTT platform and Java language, and set alarm threshold of each parameter. The results show that the system can be applied to different types of plants, which provides convenience for people to conserve plants.

Development of IoT-Based Temperature and Relative Humidity Monitoring System for Mushroom Cultivation House

Mushrooms are one of the agricultural products that are in great demand because of their high nutritional content, healthy and delicious taste. Nowadays, mushroom cultivation is increasingly widespread and focuses on understanding the optimal environmental conditions for good mushroom production. The main parameters that affect the growth of fungi are the temperature and humidity of the environment, where the fungus will grow optimally at a temperature of 20 to 30°C and at a humidity of 60 to 90%RH. But unfortunately, mushroom farmers often find it difficult to monitor at any time the environmental conditions where the mushrooms grow. For this reason, an iot-based temperature and humidity monitoring system was developed for use in mushroom cultivation rooms. This system is assembled using a DHT11 temperature and humidity sensor, a NodeMCU ESP3866 microcontroller and WiFi module, and an LCD screen. IoT development is carried out using the Thinger.io platform which allows mushroom farmers as users to monitor room conditions directly through a web page.

Application of Internet of Things (IoT) Technology to KWT “Sido Makmur” Oyster Mushroom Cultivation

Ngaran Hamlet, an area in Gilangharjo Village, Pandak District, Bantul Regency, DIY, has a Women Farmers Group (KWT), "Sido Makmur," which is engaged in oyster mushroom cultivation. One of the challenges KWT "Sido Makmur" faces is the fluctuation and instability of oyster mushroom production due to environmental conditions around the mushroom barn, which are not always ideal. To overcome this, the Community Service Team from Universitas Muhammadiyah Yogyakarta (UMY), in collaboration with Singapore Polytechnic (SP), carried out Community Service activities under the Community Partnership (PKM) scheme. This service aims to assist KWT "Sido Makmur" in facing the challenges of oyster mushroom production by designing and implementing Appropriate Technology in the form of a temperature and humidity monitoring system in mushroom barns based on the Internet of Things (IoT). The service team's programs and activities include planning, designing, implementing, testing, and analyzing the IoT technology-based mushroom monitoring system for temperature and humidity. This system allows oyster mushroom farmers in Ngaran Hamlet to monitor the condition of the mushroom coop in real-time and remotely via the IoT platform to increase the productivity of oyster mushrooms optimally. The results of the implementation and testing of the system show that the monitoring tool for temperature and humidity in the IoT-based mushroom barn has been proven to function properly in accordance with the design planning and expectations of oyster mushroom farmers in Ngaran Hamlet.

Sensor-cable-probe and sampler for early detection and prediction of dry matter loss and real-time corn grain quality in transport and storage

Taking into account that the transport of grains can be carried out over long distances and that the mass of grains during transport often has high moisture content, there may be risks of heat and moisture transfer and heating of the grains mass, proving quanti-qualitative losses. Thus, this study aimed to validate a method with probe system for real-time monitoring of temperature, relative humidity and carbon dioxide in the grain mass of corn during transport and storage to detect early dry matter losses and predict possible changes on the grain physical quality. The equipment consisted of a microcontroller, system's hardware, digital sensors to detect air temperature and relative humidity, a non-destructive infrared sensor to detect CO2 concentration. Real-time monitoring system determined early and satisfactorily in an indirect way the changes in the physical quality of the grains confirming by the physical analyses of electrical conductivity and germination. The equipment in real-time monitoring and the application of Machine Learning was effective to predict dry matter loss, due to the high equilibrium moisture content and respiration of the grain mass on the 2-h period. All machine learning models, except support vector machine, obtained satisfactory results, equaling the multiple linear regression analysis.

Humidity characteristics of a weak fiber Bragg grating array coated with polyimide

Real-time and online large-scale temperature and humidity monitoring is urgently needed in industrial and agricultural production, food and drug storage, and some engineering applications. Since it is difficult to use electrical sensors in building large-scale distributed sensing networks and they have poor stability in some complex and harsh environments, a polyimide-coated (PI-wFBG) weak fiber Bragg grating array based on a drawing tower integrated preparation method is proposed for large-scale distributed humidity sensors. An approximately 4 km-length PI-wFBG array with a coating thickness of 12 μm and grating spacing of 2 m was prepared, and six consecutive sensors were randomly selected for the determination of the relative humidity sensitivity and verification of the stability, repeatability and accuracy of the method. The experimental results showed that the relative humidity sensitivity of the prepared PI-wFBG array humidity sensor was concentrated at 1.4 ± 0.1 pm/%RH (the RH ranged from 21 %RH to 90 %RH) and the average sensitivity consistency deviation was within 3 %; the short-term stability fluctuation was within ± 2.5 %RH and the repeatability and accuracy deviations were ≤ 1.5 %RH and ≤ 2 %RH, respectively. Furthermore, the PI-wFBG array prepared by the drawing tower online method had features of adjustable grating spacing and customizable length, enabling it to be more adaptable and flexible in large-scale application scenarios.

SECHA: A Smart Energy-Efficient and Cost-Effective Home Automation System for Developing Countries

Home automation systems are gaining a lot of attraction globally and changing the way we live. They simplify our lives, reduce workloads, improve home safety and security, and pave the way for newer developments. It is no wonder why these systems are in such high demand and why modernization is needed to keep up with consumer needs. Nevertheless, utilizing home automation system technology can be energy-intensive and costly—especially for middle-class families in developing countries. In this article, we discuss SECHA, a smart, energy-efficient, and cost-effective home automation system. It empowers users to automate their homes with IoT regardless of the residence type. SECHA is developed with the goal of being energy-efficient, simple to use, and open-source for everyone’s benefit. SECHA has developed a low-cost smart home automation system that incorporates Wi-Fi and GSM technology, enabling remote monitoring and control of appliances through an Android application. This solution enables users to easily monitor and manage their homes. An automation system has been developed using an ESP32 microcontroller equipped with Wi-Fi and GSM SIM800. This impressive setup is further enhanced by the integration of several sensors that enable monitoring of temperature, humidity, movement, and other aspects at home.

PEDOT:PSS-Based Disposable Humidity Sensor for Skin Moisture Monitoring

This letter presents a flexible and disposable humidity sensor based on Poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT:PSS). The sensing layer is developed by drop casting PEDOT:PSS on screen printed graphene-carbon-ink-based interdigitated electrodes (IDEs) on paper substrate. The humidity sensing properties are investigated in a wide humidity range (25%RH–90%RH) at room temperature (RT; 27 °C ± 2 °C). The sensor exhibits substantial % response (118.5% at 90%RH) in the considered range with response/recovery time as 70/30 s. The applicability of the sensor has been demonstrated for skin moisture/humidity monitoring under normal and moist conditions. A read-out circuit is designed for demonstrating the real-time monitoring of skin moisture level. The obtained results indicate the suitability of the developed sensor for skin moisture monitoring, environmental humidity monitoring, and noncontact switching in areas such as healthcare and agriculture.

Prototype of Room Temperature and Humidity Monitoring Device in Shallot Storage Using Microcontroller Arduino

Allium ascalonicum L or commonly referred to as shallot is one type of horticultural plant that is important because it is widely used by humans as a mixture of spices in cooking. The need for shallots increasing every day accompanied by a large number of agricultural products, causing the stability of shallot availability in Merauke County to become unstable, To support the needs of consumers shallots imported from outside Merauke. Therefore the condition of the shallots in the storage area is cold and humid. While waiting to be sold in the storage area, it must be maintained temperature and humidity to reduce decay and shrinkage. This prototype monitoring device works to measure and maintain the temperature and humidity in the storage. The data collection method in this study is Literature Study, Observation, Interview, and Documentation. Microcontroller devices are designed or made to be able to control the state of temperature and humidity in the room where the onion is stored. The device also gives notifications via text message to users to be able to find out the state of the onion storage. The results of the study conducted using the DHT11 sensor obtained a temperature measurement accuracy rate of 93.848% and a humidity accuracy rate was 91.808%. This device can detect the temperature and humidity values in the shallot storage room.

Internet of Everything and Digital Twin enabled Service Platform for Cold Chain Logistics

The proliferation of the e-commerce market has posed challenges to staff safety, product quality, and operational efficiency, especially for cold chain logistics (CCL). Recently, the logistics of vaccine supply under the worldwide COVID-19 pandemic rearouses public attention and calls for innovative solutions to tackle the challenges remaining in CCL. Accordingly, this study proposes a cyber-physical platform framework applying the Internet of Everything (IoE) and Digital Twin (DT) technologies to promote information integration and provide smart services for different stakeholders in the CCL. In the platform, reams of data are generated, gathered, and leveraged to interconnect and digitalize physical things, people, and processes in cyberspace, paving the way for digital servitization. Deep learning techniques are used for accident identification and indoor localization based on Bluetooth Low Energy (BLE) to actualize real-time staff safety supervision in the cold warehouse. Both algorithms are designed to take advantage of the IoE infrastructure to achieve online self-adapting in response to surrounding evolutions. Besides, with the help of mobile and desktop applications, paperless operation for shipment, remote temperature and humidity (T&H) monitoring, anomaly detection and warning, and customer interaction are enabled. Thus, information traceability and visibility are highly fortified in this way. Finally, a real-life case study is conducted in a pharmaceutical distribution center to demonstrate the feasibility and practicality of the proposed platform and methods. The dedicated hardware and software are developed and deployed on site. As a result, the effectiveness of staff safety management, operational informatization, product quality assurance, and stakeholder loyalty maintenance shows a noticeable improvement. The insights and lessons harvested in this study may spark new ideas for researchers and inspire practitioners to meet similar needs in the industry.

P3HTandPEDOT:PSSprinted thin films on chemiresistors: An economic and versatile tool for ammonia and humidity monitoring applications

AbstractWe hereby present the fabrication of simple and efficient humidity and ammonia sensors based on a chemiresistor design employing a differential measurement technique. Interdigitated electrodes are connected via PEDOT:PSS or P3HT polymers and a reproducible and scalable fabrication procedure is presented. This procedure utilizes pneumatic nozzle printing instead of drop or spin‐based processes and includes an optimized encapsulation procedure and material for sealing the reference electrodes. The suitability of the NH3sensor for quantifying ammonia in a range of 2 to 100 ppm within a period of several months is furthermore presented. The developed humidity sensor is operational for several months in a humidity range between 10 and 60% RH. Once this range is exceeded, a sensor decay by irreversible saturation can be observed. Based on the low fabrication costs of the sensors (~0.5 $ when ordering 1000 pcs of the platform + printing work), they provide a very attractive tool for industrial humidity and ammonia sensing applications.

Spatiotemporal Variations in PM2.5 Concentration in Different Areas of Bus Cabin: A Case Study in Shenzhen, China

Inhalable particulate pollution has adverse effects on human health. Many studies have been conducted to investigate levels and risks of exposure to particulate pollution in public transit, but scant attention has been paid to variations in the pollution levels among different positions inside the cabin. Differences can be observed among different positions inside transit vehicles, like passenger density and activities, which may lead to differentiated exposure risks between different positions. Therefore, this study investigates the level of PM2.5 concentrations and the spatiotemporal variations among three different positions (front, middle, and rear) inside the cabin during bus travel. The three positions represent the three areas inside the bus cabin, i.e., front area (FA), middle area (MA), and rear area (RA). We developed a portable monitoring system for in-cabin measurements, which consists of a mobile device with the designated app, a PM2.5 collecting device, and a temperature-relative humidity monitor. Surveys were carried out on buses of a route in Shenzhen, China, which include inbound and outbound trips during both morning and evening peaks of two working days. Based on spatial and temporal information embedded in data collection devices, PM2.5 concentration data were spatially and temporally referenced. Comparative and descriptive statistical analyses were employed to examine the differences and variations in PM2.5 concentration among the areas inside the bus cabin. There are three major findings. First, for all of the surveyed trips, FA showed the highest and RA showed the lowest PM2.5 concentration. Second, concerning the average pollution level of route segments along the routes, the PM2.5 concentrations in the three cabin areas were higher during inbound trips than during outbound trips. Third, within route segments, PM2.5 concentrations in FA and MA increased rapidly after the bus stopped at stops, and then gradually decreased, while in RA they were relatively stable. In general, a higher level of passenger density increased in-cabin PM2.5 concentration. The findings of our study could provide insight into improving the bus in-cabin microenvironment, such as the seating arrangement for vulnerable passengers.