Environmental Monitoring System Research Articles

Development and Validation of Low-Cost Indoor Air Quality Monitoring System for Swine Buildings

The optimal indoor environment is associated with comfortable temperatures along with favorable indoor air quality. One of the air pollutants, particulate matter (PM), is potentially harmful to animals and humans. Most farms have monitoring systems to identify other hazardous gases rather than PM due to the sensor cost. In recent decades, the application of environmental monitoring systems based on Internet of Things (IoT) devices that incorporate low-cost sensors has elevated extensively. The current study develops a low-cost air quality monitoring system for swine buildings based on Raspberry Pi single-board computers along with a sensor array. The system collects data using 11 types of environmental variables along with temperature, humidity, CO2, light, pressure, and different types of gases, namely PM1, PM2.5, and PM10. The system is designed with a central web server that provides real-time data visualization and data availability through the Internet. It was tested in actual pig barns to ensure stability and functionality. In addition, there was a collocation test conducted by placing the system in two different pig barns to validate the sensor data. The Wilcoxon rank sum test demonstrates that there are no significant differences between the two sensor datasets, as all variables have a p-value greater than 0.05. However, except for carbon monoxide (CO), none of the variables exhibit correlation exceeding 0.5 with PM concentrations. Overall, a scalable, portable, non-complex, low-cost air quality monitoring system was successfully developed within a cost of USD 94.

Lora Based Industrial Environment Monitoring System

With the advent of automation, the concept of protecting the business environment has become popular and recognized in the business world. As the factory scale grows and the complexity of the process increases, advanced technology must be used in the device to measure and control many business processes simultaneously. Today, the trend is towards miniaturization of instruments and greater precision and accuracy. Reliable equipment and controls are crucial to the safety and efficiency of any process. The goal of this project is to gain knowledge about the most important aspects of the job to improve safety. The system includes the use of LORA to monitor the business environment. In this project, we use Lora communication to send data, and the receiving end of the monitoring station receives the data from the sending end. In an emergency, when you press the emergency button on the monitoring station, a message is sent to the work unit by LORA. Since LORA is a transceiver, two- way communication is possible in the project. Temperature sensors, gas sensors and fire sensors are used to monitor the environment of business units. Temperature sensors are used in industry to calculate temperature and provide information to microcontrollers. Gas sensors are used in industry to detect gas leaks. Fire sensors are used to detect fire and send the information to the monitoring station. This product is delivered by LORA.

Triboelectric power generation performance of polyvinyl alcohol using ZnO–CuO–AgO trimetallic nanoparticles

AbstractTriboelectric nanogenerators (TENGs), a new technology for gathering sustainable energy, have attracted much scientific interest. In this study, we describe a unique method for modifying the triboelectric power generation performance of Polyvinyl Alcohol (PVA) by adding ZnO–CuO–AgO (ZCA) trimetallic nanoparticles to improve the performance of TENGs and answer the requirement for ecologically benign and biodegradable materials. Hydrothermal synthesis adopted to create ZnO–CuO–AgO trimetallic nanoparticles ensures a distinctive structure with a large surface area, essential for enhancing triboelectric power generation. From the AFM results, it is evident that 1% PVA/ZCA showed the highest output voltage of 0.27V. Despite following the general trend, at higher concentrations of ZCA nanofiller in the PVA matrix, the enhancement of output voltage is not observed, which can be attributed to the non-uniform distribution. The effect of spin-coated film thickness and nanoparticle concentration on the triboelectric performance of the PVA nanogenerator is studied by monitoring the open-circuit voltage in response to various mechanical stimuli. Finally, the developed biodegradable nanogenerators in this study can be used for sustainable energy harvesting applications such as wearable electronics, self-powered sensors, and environmental monitoring systems.

Solar powered Air Purification and Environmental Monitoring System

Solar powered Air Purification and Environmental Monitoring System

WSN-Based Data Acquisition System for Collecting Environmental Pollution Factors for Green City

Implementation with a portable, intelligent weather station is to upgrade the system for environmental management and monitoring. This gadget measures and assesses meteorological and air quality data by real-time implementation through the Internet of Things technology to provide important environmental condition insights. The monitoring station's hardware parts include the ESP32 board, MQ2, MQ3, and MQ135 sensors for gas detection. Such an intelligent weather monitoring station can easily be deployed in different environments due to its portability and versatility. This small station size and its wireless link will enable effective data collection and transfer and integration into other systems of the present day. The existing environmental monitoring system takes the temperature and humidity and measures ammonia, benzene, alcohol, smoke, and carbon monoxide. Therefore, data is brought to the monitoring station, where it communicates in real time for the users to review and analyse on the online platform Blynk. It enables users to easily make data presentations and create notifications and dashboards using a mobile app of Blynk and the web platform, enabling them to create interfaces that meet their satisfaction easily. Users may also upload the uploaded data to a web server for remote access and analysis, which eases scalability and flexibility. Portable intelligent weather monitoring station has significant areas of influence on applications like public health, urban planning, and environmental monitoring, among others. It thus provides decision-makers with information on pollution management and climate resilience. This provides a sustainable and resilient future; it is approachable since the interface used in the system is accessible, befitting the two settings: urban and rural. The Intelligent Portable Weather Monitoring Station provides great usefulness in the disclosure, development, innovation of technology, and practice in the quest for meeting challenges of the environment with the promotion of sustainability. This not only allows smarter and more sustainable city development with effective environmental monitoring and management that includes IoT technologies but can also allow flexible data transmission facilities.

Progress in Advanced Infrared Optoelectronic Sensors.

Infrared optoelectronic sensors have attracted considerable research interest over the past few decades due to their wide-ranging applications in military, healthcare, environmental monitoring, industrial inspection, and human-computer interaction systems. A comprehensive understanding of infrared optoelectronic sensors is of great importance for achieving their future optimization. This paper comprehensively reviews the recent advancements in infrared optoelectronic sensors. Firstly, their working mechanisms are elucidated. Then, the key metrics for evaluating an infrared optoelectronic sensor are introduced. Subsequently, an overview of promising materials and nanostructures for high-performance infrared optoelectronic sensors, along with the performances of state-of-the-art devices, is presented. Finally, the challenges facing infrared optoelectronic sensors are posed, and some perspectives for the optimization of infrared optoelectronic sensors are discussed, thereby paving the way for the development of future infrared optoelectronic sensors.

3D position deployment and performance optimization of mmWave UAV-assisted HetIoT under jamming condition

Heterogeneous Internet of Things (HetIoT) has received widespread attention due to its provision of various convenient services in fields such as smart cities, intelligent transportation, environmental monitoring and security systems. Due to HetIoT inherently demands high data rates, bandwidth, and low latency, the application of millimeter-wave (mmWave) unmanned aerial vehicle (UAV) as emergency aerial base station (ABS) providing services to HetIoT users has become a low-cost and efficient means. However, due to the sensitivity of mmWave to obstacles and jamming, guaranteeing network performance has become a pressing issue. This paper considers a mmWave UAV-assisted HetIoT under jamming conditions, where auxiliary ABSs serve multiple ground users (GUs) who generate a large amount of sensor data. We establish a coverage maximization problem under the constraints of signal-to-interference ratio (SIR) threshold, maximum power of ABSs and maximum number of GUs that the base station can serve, and propose a novel ABS hovering deployment algorithm M-HiAPSO that combines the artificial potential field (APF) method and the improved particle swarm optimization (PSO) algorithm in a hierarchical manner. Specifically, the multi-element APF method is used to characterize the horizontal force between nodes, combined with the improved hierarchical adaptive PSO algorithm to adjust the horizontal position of the ABS to obtain the optimal UAV hovering position and power allocation strategy. Numerical results show that the coverage rate reached 96.2% when the number of iterations was 283, and it can reach up to 99.6%.

Power improvement of triboelectric nanogenerator by morphological transformation strategy for harvesting irregular wave energy

Wave is inherently characterized by disorder and randomness, which is a great challenge for the conventional wave-based triboelectric nanogenerator (W-TENG) and necessitates conducting adaptability research on the device. Therefore, we proposed a morphological transformation strategy, that is, W-TENG can actively transform the motion patterns of self-structure to accommodate the variations in waves and achieve power improvement. And a morphological transformation TENG (MT-TENG) with multi-mode operation is developed for harvesting irregular wave energy. Furthermore, the disorder wave motion is transformed into a bidirectional continuous rotation of power generation units, which realizes the continuous waveform output. Experimental results demonstrate that the wave power grows by 9.22 times with frequency increase, and the device's performance increases by 114.136 times utilizing this strategy. MT-TENG can output 39.67 mA through the energy management circuit (EMC) and a peak power density of 30.62 W/m3 under the wave excitation of 1.1 Hz. Finally, the self-powered environmental monitoring system is constructed, which can illuminate ten 30 W LEDs in series and provide a continuous energy supply to the wireless sensor module. This work presents a research paradigm for the design of wave-environment adaptability, holding significant implications for improving performance and constructing self-powered sensing systems.

Research on design strategy of public space service of commercial complex based on internet of things

The purpose of this study is to explore the design strategy of public space service of commercial complex based on the Internet of Things. By constructing a three-tier model of environmental energy consumption monitoring and management system for commercial complex, the application of network sensor technology is analyzed, and a data access interface based on Windows Communication Foundation (WCF) service is designed to realize batch hosting of WCF services and reduce the complexity of large-scale publishing services. In addition, this paper proposes a clustering method based on probabilistic topics (PTCM), which divides the service search space into probabilistic topics and effectively narrows the service search scope. The simulation results show that the algorithm shortens the shortest distance between mobile nodes and the average network distance, and improves the perceived service quality of the Internet of Things. This study not only provides new ideas and methods for the design of public space services in commercial complexes, but also provides useful reference for the application and promotion of Internet of Things technology in the field of public services.

High versatility of polyethylene terephthalate (PET) waste for the development of batteries, biosensing and gas sensing devices

Continuously growing adoption of electronic devices in energy storage, human health and environmental monitoring systems increases demand for cost-effective, lightweight, comfortable, and highly efficient functional structures. In this regard, the recycling and reuse of polyethylene terephthalate (PET) waste in the aforementioned fields due to its excellent mechanical properties and chemical resistance is an effective solution to reduce plastic waste. Herein, we review recent advances in synthesis procedures and research studies on the integration of PET into energy storage (Li-ion batteries) and the detection of gaseous and biological species. The operating principles of such systems are described and the role of recycled PET for various types of architectures is discussed. Modifying the composition, crystallinity, surface porosity, and polar surface functional groups of PET are important factors for tuning its features as the active or substrate material in biological and gas sensors. The findings indicate that conceptually new pathways to the study are opened up for the effective application of recycled PET in the design of Li-ion batteries, as well as biochemical and catalytic detection systems. The current challenges in these fields are also presented with perspectives on the opportunities that may enable a circular economy in PET use.

CuO nanoparticles passivated 2D MXene-based voltammetric sensor for detecting environmental hazardous pollutant

This research explores a novel method for electrochemical sensing of the organic pollutant diclofenac sodium. Glassy carbon electrodes (GCEs) were modified with ultrasonically prepared MXene/CuO nanoparticle composites, demonstrating a wide linear detection range of 0.34 µM–31.67 µM for the contaminant. The study involved synthesizing 2D MXene via HF etching and DMSO delamination, and CuO nanoparticles through a hydrothermal process. Powder XRD, FE-SEM, EDAX, HR-TEM, and SAED techniques characterized the synthesized materials and composites. Cyclic voltammetry (CV), differential pulse voltammetry (DPV), square wave voltammetry (SWV), and electrochemical impedance spectroscopy (EIS) were employed to analyze the electrochemical behaviour of the nanocomposites. Furthermore, the binding interaction between the MXene/CuO composite and diclofenac sodium was investigated using molecular modelling and semi-empirical approaches. The results revealed that CuO nanoparticle incorporation significantly enhances the sensitivity of MXene towards diclofenac. This novel sensor exhibited satisfactory performance, suggesting its potential application as a robust platform for environmental monitoring systems.

Smart Infant Incubator

We propose a solution called "Smart Infant Incubator" which aims at enhancing the maintenance of new born in various hospitals to make it much better and safer. The main idea of the project is to implement an ESP32-based intelligent environment monitoring system in the incubator from which it measures the humidity and temperature data on the spot where the incubator is placed. The system uses sensors like DHT11 for live temperature and humidity readings, an intelligent alert system and it is integrated with the Rainmaker platform for remote monitoring. The power system is given special attention which includes a Li-ion cell and a charging module to charge the cell. Safety features such as overcharge protection for the battery are also added. The report gives a clear picture of the steps that were performed in the project to accomplish the goals and also the results and analysis of the project. The prototype can be very useful in improving the nursery wards where we will consider this technology to be integrated with the incubators which will be very useful in maintaining the newborns safely.

Comprehensive Security for IoT Devices with Kubernetes and Raspberry Pi Cluster

Environmental monitoring systems have gained prominence across diverse applications, necessitating the integration of cutting-edge technologies. This article comprehensively explores such a system, emphasizing the integration of a Raspberry Pi cluster with the BME680 environmental sensor within a Kubernetes framework. This study encompasses the technical aspects of hardware configuration and places a significant focus on security benchmarks and robustness validation. The environmental monitoring infrastructure discussed in this article delves into the intricacies of the Raspberry Pi cluster’s hardware setup, including considerations for scalability and redundancy. This research addresses critical security gaps in contemporary environmental monitoring systems, particularly vulnerabilities linked to IoT deployments. Amidst increasing threats, this study introduces a robust framework that integrates advanced security tools—HashiCorp (San Francisco, CA, USA) Vault v1.16 for dynamic secret management and OpenID Connect for authentication processes—to enhance applications and system integrity and resilience within the Kubernetes environment. The approach involves a multi-layered security architecture that fortifies the storage and management of credentials and ensures authenticated and authorized interactions within IoT networks. Furthermore, our research incorporates a series of security benchmark tests, including vulnerability scanning, penetration testing, and access control assessments. Additionally, this article addresses crucial aspects related to data management and analysis, detailing the methodologies employed for storing, processing, and deriving insights from the collected environmental data. It further explores the integration of the monitoring system with existing infrastructure and systems, facilitating seamless data sharing and interoperability and offering valuable insights into the system’s ability to withstand potential threats and vulnerabilities. The integration of Raspberry Pi clusters with BME680 environmental sensors within a Kubernetes-managed framework significantly enhances the scalability and security of IoT systems. This study quantifies the improvements, demonstrating at least a 30% enhancement in system responsiveness and a minimum 40% reduction in vulnerability exposures, as verified by extensive security benchmarks, including penetration testing. These advancements facilitate robust, scalable IoT deployments, with potential applications extending beyond environmental monitoring to include industrial and urban settings. The incorporation of dynamic secret management with HashiCorp Vault and secure authentication with OpenID Connect provides a blueprint for developing resilient IoT architectures capable of supporting high-security and high-availability applications. In conclusion, this article contributes to the expanding body of knowledge in IoT and environmental monitoring and establishes a strong foundation for future work. These outcomes suggest promising directions for further research in secure IoT applications and present practical implications for the deployment of secure and scalable IoT solutions in critical infrastructures.

Environmental Monitoring and Control System of Green House with Microcontroller and GSM Using IoT Devices

Environmental Monitoring and Control System of Green House with Microcontroller and GSM Using IoT Devices

A Compact-Sized Fully Self-Powered Wireless Flowmeter Based on Triboelectric Discharge.

Flow sensing exhibits significant potential for monitoring, controlling, and optimizing processes in industries, resource management, and environmental protection. However, achieving wireless real-time and omnidirectional sensing of gas/liquid flow on a simple, self-contained device without external power support has remained a formidable challenge. In this study, a compact-sized, fully self-powered wireless sensing flowmeter (CSWF) is introduced with a small size diameter of down to less than 50mm, which can transmit real-time and omnidirectional wireless signals, as driven by a rotating triboelectric nanogenerator (R-TENG). The R-TENG triggers the breakdown discharge of a gas discharge tube (GDT), which enables flow rate wireless sensing through emitted electromagnetic waves. Importantly, the performance of the CSWF is not affected by the R-TENG's varied output, while the transmission distance is greater than 10m. Real-time wireless remote monitoring of wind speed and water flow rate is successfully demonstrated. This research introduces an approach to achieve a wireless, self-powered environmental monitoring system with a diverse range of potential applications, including prolonged meteorological observations, marine environment monitoring, early warning systems for natural disasters, and remote ecosystem monitoring.

Participatory Geomonitoring for Future Mining—Resilience Management in the Cavern Storage Epe (Germany)

Integrated geo- and environmental monitoring in mining represents a high-dimensional challenge (location, altitude/depth, time and sensors). This is challenging for experts but poses great problems for a multitude of participants and stakeholders in building up a complete process understanding. The Epe research cooperation aims to elucidate the ground movement at the Epe cavern storage facility with a public participation process. The research cooperation was founded by the city of Gronau, the citizens’ initiative cavern field Epe, the company EFTAS, Münster, and the Research Center of Post-Mining at the Technische Hochschule Georg Agricola, Bochum. This research cooperation is the first in Germany to involve direct collaboration between science and the public. In the cavern field, which has been in operation since the 1970s, brine is extracted, and at the same time natural gas, crude oil and helium, as well as hydrogen in the future, are stored in the subsurface. The technical focus of this work was the development of a high-resolution spatiotemporal analysis of ground movements. The area is monitored annually by the mining company’s mine surveyor. The complexity of the monitoring issue lies in the fact that the western part is a bog area and a former bog area. Furthermore, the soils in the eastern part are very humus-rich and show strong fluctuations in the groundwater and therefore complex hydraulic conditions. At the same time, there are few fixed scatterers or prominent points in the area that allow high-resolution spatiotemporal monitoring using simple radar interferometry methods. Therefore, the SBAS method (Small Baseline Subset), which is based on an aerial method, was used to analyze the radar interferometric datasets. Using an SBAS analysis, it was possible to evaluate a time series of 760 scenes over the period from 2015 to 2023. The results were integrated with the mine survey maps on the ground movement and other open geodata on the surface, the soil layers and the overburden. The results show complex forms of ground movement. The main influence is that of mining. Nevertheless, the influence of organic soils with drying out due to drought years and uplift in wet years is great. Thus, in dry years, ground subsidence accelerates, and in wet years, ground subsidence not only slows down but in some cases also causes uplift. This complexity of ground movements and the necessary understanding of the processes involved has been communicated to the interested public at several public information events as part of the research cooperation. In this way, an understanding of the mining process was built up, and transparency was created in the subsurface use, also as a part of the energy transition. In technical terms, the research cooperation also provides a workflow for developing the annual mine survey maps into an integrated geo- and environmental monitoring system with the development of a transparent participatory geomonitoring process to provide resilience management to a mining location.

Water Pollution Detection Using Video Surveillance and Deep Learning

Aiming at the problems that the traditional water quality prediction model is generally not high in prediction accuracy and robustness, a water pollution prediction using deep learning in water environment monitoring big data is proposed. Objective. To optimize and improve the prediction accuracy of the water quality prediction model. Firstly, in the water environment monitoring system, the Internet of Things big data technology is used to accurately sense and monitor the real-time data of sewage treatment equipment and sewage quality. Then, the deep belief network (DBN) is used to build the water pollution prediction model, and the collected sewage treatment data is analyzed to predict the water quality status. Finally, particle swarm optimization algorithm is used to dynamically optimize the number of hidden layer neural units and learning rate in the DBN prediction model, which makes the prediction results more scientific and accurate. Based on the sampling data of Shanghai Jinze Reservoir, the proposed model is experimentally analyzed. The results show that the probability of accurate location of the pollution source is not less than70%. And under the two indicators of chemical oxygen demand and biological oxygen demand, the root mean square error and correlation coefficient are 3.073, 0.9892 and 1.958, 0.9565, respectively, which are better than other comparison models.

Self-powered wireless environmental monitoring system for in-service bridges by galloping piezoelectric-triboelectric hybridized energy harvester

Self-powered wireless environmental monitoring system for in-service bridges by galloping piezoelectric-triboelectric hybridized energy harvester

Strategic Planning and Ecological Safety Evaluation of University Campuses on Green Marketing Principles

Strategic planning of university campuses (UC) aims to harmonize nature, humans, and architectural complexes, enhancing the positive university image through specialized green and recreation zones. Highly urbanized UC areas, particularly with nearby roads, encounter increased technogenic load and pose additional health hazards. The purpose of the paper is the evaluation of the environmental safety level of the UC recreational territories on the example of campuses of Kyiv universities, located nearby highly loaded roads, using a complex of express methods of analysis, mathematical modeling and criterion-based approach, considering the main green economy principles. The scientific novelty of the paper and the authors’ contribution is in the assessment of the environmental safety level of city-type UC recreational territories being under the significant technogenic load from vehicle emissions. Such express analysis methods as densimetry, viscometry, stalagmometry, conductometry, potentiometry and optical methods, and in particular, refractometric studies have been used to assess the impact of vehicle emissions. The mathematical modeling and computational experiment have been carried out for dispersion fields of the main vehicle emissions pollutants. Ecologically acceptable distances from the road considering the specifics of recreational territory have been determined using the integral index of technogenic load. Propositions for minimizing human health hazards and improving the system of environmental monitoring of such territories have been provided and substantiated. The study also confirms the positive effects of environmental management and green marketing principles synergy, benefiting both nature and humans as well as the university image. Obtained results can be used for the design and reconstruction of UC and their recreational areas, as well as for planning roads located nearby the campuses, improving traffic on them. It is also convenient to foresee the enhancement of the environmental activities in the student research work and create student communities for monitoring the UC environmental state and the development of eco-startup projects.

Smart Irrigation and Pesticides System for Enhancing Harvesting in Agriculture Using IoT

Agriculture plays a vital role in the economy of many countries, serving as a primary source of food. However, traditional farming practices often face challenges such as inefficient water usage, over-reliance on pesticides, and inconsistent monitoring of crop conditions. In recent years, the Internet of Things (IoT) has emerged as a promising technology to address these challenges by providing real-time monitoring and control of agricultural processes. This leads in excessive water use, which has an impact on agricultural output. This integrated system means that farmers only need to perform little manual monitoring. The opening and closing of the reservoir and field gates, as well as the verification of the plant's age and the matching optimal water level necessary for that time of plant age, are all automated. Farmers may use their mobile phones to check the water level in the field since they are continually receiving updates on the field work. The most labour-intensive and time consuming activity in agriculture is water management. In our project, the water level in the agriculture harvest sting is measured, and if it is lower than the required level, the paddy field is automatically irrigated for the water source or tank using a water pump. It can comprehensively monitor air temperature and humidity, light intensity, ultraviolet light and other environmental elements. In specific use, the agricultural production environment monitoring system starts from the actual needs of the plantation zone and is assembled according to the environmental elements it needs to monitor.