Environmental Monitoring System Research Articles

Machine Learning-Based Morel Mushroom Environmental Monitoring System

As living standards improve, the demand for edible fungi increases, making their efficient cultivation crucial for food supply and agricultural productivity. Traditional manual monitoring has limited accuracy, but the introduction of IoT and embedded technology enhances the intelligence and precision of agricultural monitoring, saving both labor and resources. This study designs a machine learning-based environmental monitoring and prediction system for edible fungi, utilizing low-power ZigBee networks and Kalman filtering to improve data accuracy. The system ensures real-time data transmission via the MQTT protocol and enhances security and scalability through cloud storage. By comparing Transformer, LSTM, and LSTM-Attention models, it was found that the Transformer model performed best in predicting environmental parameters, enabling proactive regulation, boosting yield and quality, and promoting the development of intelligent agriculture.

AI-Based Environmental Monitoring System with Farm Automation

This project presents an innovative approach to environmental monitoring in agricultural settings using AI-based solutions integrated with IoT technology. The system leverages data collected from various sensors such as soil moisture, gas sensors, and other environmental indicators to monitor the conditions in real-time. By utilizing an Arduino microcontroller, ESP module, and ThingSpeak server, the project is able to capture, store, and transmit sensor data effectively. The highlight of the project is the AI-based weather prediction module implemented using a Convolutional Neural Network (CNN) in Python, providing critical insights into weather conditions and allowing for data-driven decision-making. The system also includes a user-friendly web interface to display real-time monitoring and predictions, enabling farmers to better manage their resources and plan ahead for changes in environmental conditions

Development And Testing of Arduino Based Autonomous Environmental Monitoring System

This paper presents the development of an Autonomous Environmental Monitoring System (AEMS) designed to track various environmental parameters. With the growing demand for autonomous monitoring systems in today’s modern era, we propose an Arduino-based real-time hardware solution to measure parameters such as flame, temperature, humidity, and distance. The system leverages advanced and cost-effective electronic sensors and hardware to monitor these environmental factors. We developed individual sensor modules for each parameter and integrated them into a unified multi-sensor system through sensor fusion. The collected data is then displayed on a 16 × 2 LCD module. The result is a fully functional autonomous monitoring system, tested under laboratory environmental conditions using a compact, handheld device.

REGENERATIVE TOURISM DEVELOPMENT: A PRELIMINARY STUDY OF CIRCUMSTANCES IN PHUKET

The concept of sustainable tourism has long been a focal point in tourism literature. However, the increasing complexity of global challenges, such as climate change and over-tourism, suggests that sustainability alone may no longer be sufficient. This is where regenerative tourism emerges, shifting the focus from merely minimizing harm to actively restoring and enhancing ecosystems, communities, and economies through tourism activities. This preliminary research aims to investigate the current state of regenerative tourism development in the context of Phuket, Thailand. A qualitative research approach was employed, utilizing semi-structured in-depth interviews with six key informants, including local community members, public and business representatives in tourism organizations, and local government officials. The iterative analysis of the interviews revealed several critical themes: waste management issues, insufficient enforcement of laws and regulations, the need for improved stakeholder collaboration, and growing environmental concerns. Additionally, the study highlighted various regenerative tourism practices currently being implemented. This preliminary study reveals four critical challenges in Phuket's regenerative tourism development: systemic waste management failures, insufficient law enforcement and regulations, lack of stakeholder collaboration, and escalating environmental concerns. The findings indicate that transitioning to regenerative tourism requires enhanced infrastructure and waste management systems, strengthened regulatory frameworks and enforcement mechanisms, improved stakeholder engagement processes, and comprehensive environmental monitoring systems. This research supports the need for a balanced approach to tourism development that considers environmental and social impacts alongside economic benefits. The implications of this research are significant, emphasizing the need for increased awareness and the optimization of collaboration among relevant tourism stakeholders to foster regenerative tourism in Phuket.

Real-Time Wireless Detection of Heavy Metal Ions Using a Self-Powered Triboelectric Nanosensor Integrated with an Autonomous Thermoelectric Generator-Powered Robotic System.

The integration of the Internet of Things (IoT) with advanced sensing technologies is transforming environmental monitoring and public health protection. In this study, a fully self-powered and automated chemical sensing system is developed and integrated with a robotic hand for "touch and sense" detection of toxic heavy metal ions (Pb2⁺, Cr⁶⁺, As3⁺) in aquatic environments. The system combines a self-powered solid-liquid triboelectric nanosensor (SL-TENS) with a thermoelectric generator (TEG), which harnesses ambient heat to power the robotic hand, eliminating the need for external power sources. The robotic hand is controlled wirelessly via an exo-hand, minimizing the risk of exposure during remote monitoring. The sensing component uses copper oxide nanowires (CuO NWs) coated with ion-selective membranes (ISMs) to enhance triboelectric output and enable highly selective ion detection. The system demonstrates effective real-time, on-site detection in lake water and data transmitted wirelessly to the user. This innovative approach provides a highly safe and efficient method for detecting hazardous pollutants in difficult-to-access areas, offering significant potential for wireless and real-time environmental monitoring and hazard prevention, thus contributing to the safeguarding of human health. This study presents a novel advancement in the field of IoT-enabled environmental monitoring systems.

Fractal Analysis of Mining Wastewater Time Series Parameters: Balkhash Urban Region and Sayak Ore District

The population life and health quality are significantly reduced due to water resources pollution caused by heavy metals, especially in urban agglomerations located close to metal ore mining and processing facilities. The greatest environmental pollution occurs during the extraction of Cu, Zn, and Pb. In this study, a fractal R/S analysis of wastewater discharge indicators time series from a metal ore mining facility located in the Sayak ore district in the Republic of Kazakhstan (turbidity, electrical conductivity, flow magnitude, and pH level) was carried out. A sharp increase in the flow rate was recorded from 10 to 15 July 2024 and an increase in the electrical conductivity from 4 to 26 July 2024. However, the latest type of indicator assessment does not exceed the critical level for life. The presence of electrical conductivity indicators time series long-term memory and persistence was also recorded (the Hurst exponent for the electrical conductivity time series is fixed in the 0.56 to 0.59 range and does not go below the threshold value for randomness according to the Anis-Lloyd formula). Thus, the value-changing process is controlled and stable, and minor changes in turbidity indicate that these releases do not significantly harm the environment. Despite this, the results obtained do not allow for a comprehensive analysis of the state of releases as the data from all deposits is not available. Therefore, due to the time constraints of the data provided for analysis, it is difficult to fully assess the impact of specific metal ore mining facilities on the environmental safety of the Balkhash urban region. In addition, many studies indicate very high risks of chronic diseases for the population living in this region. The findings of this study enable us to conclude that the application of fractal analysis and the calculation of fractal characteristics for time series of emissions can serve as an indicator of the environmental status within the given area. This information can be used by environmental services to build reliable environmental pollution monitoring systems.

Air quality monitoring system based on low power wide area network technology at public transport stops

<span>Mass migration from rural areas to urban areas has caused problems of traffic congestion, high industrial concentration and inequity in the distribution of housing in the world's capitals, generating a significant threat to sustainable development and public health due to air pollution air. In the Peruvian context, the importance of real-time monitoring of air quality is highlighted according to the standards established by the government. Several studies propose real-time environmental monitoring systems using internet of thing (IoT) technologies, electrochemical and optical sensors to measure pollutants, highlighting the need for data analysis. The objective of the paper is to show the implementation of IoT devices called sensor nodes, with long range wide area network (LoRaWAN) transmission technology for continuous monitoring of polluting gas concentrations. In addition, they are integrated into a central node called gateway to perform real-time monitoring through a web application. As an initial result, IoT devices demonstrated their effectiveness for real-time monitoring. Despite being a prototype-level result, the next stage involves its deployment at public transport stops in Lima. Overcoming the limitations of the solution, this paper establishes the foundation for future research on pollution and public health.</span>

Observational study on the surface radiation budget and energy balance closure of grassland in the eastern arid region of Northwest China

Based on the observation data of the meteorological environment monitoring system (QT-1010) and the open vorticity correlation system (LI-7500DS), we used the block aerodynamics and energy balance ratio method to analyze the surface radiation budget and energy balance closure characteristics of the grassland in the eastern arid region of Northwest China at different time scales.We found that (1) The daily variation curve of the surface radiation flux is unimodal, and the variation amplitude of each component is as follows: Rs↓> RL↑> RL↓> Rs↑. (2) The monthly peak of each radiation component occurs in summer, and the time of reaching the peak of different components has a lag. The changes of radiation components in sunny and cloudy days are multi-modal. In the precipitation weather, the fluctuation of each radiation flux is unimodal.The average annual surface albedo () is 0.24, which is higher in winter than in summer. There is a linear relationship between surface albedo and soil moisture. (3) The Net radiation (Rnet) dominates the sensible heat in spring and the latent heat in summer. H/Rnet and Gn/Rnet are both positive in a day, H/Rnet and LE/Rnet fluctuate wildly before and after sunrise, and Gn is dominant at night. (4) The energy closure is manifested as summer > winter > Autumn > spring, and the energy closure is good throughout the year.

Development of Self-generated and LPWA-based Crop Growth Environment Monitoring and Bigdata Analysis System

Development of Self-generated and LPWA-based Crop Growth Environment Monitoring and Bigdata Analysis System

The INPHET- a global approach to Environmental Public Health Tracking

Abstract Environment and health monitoring and information systems are fundamental infrastructure for evidence provision for policy making. The International Network for Public Health and Environment Tracking (INPHET) was formed by a community of environmental public health practitioners to address common interests and activities that advance environmental public health surveillance (EPHS) and data systems, and their uses to inform public health actions. Its main goal is to address the vast inequalities across countries and communities in their ability to monitor, assess, inform and mitigate environmental and health issues. INPHET supports the relevant role of environmental epidemiology as the pillar science providing evidence for decision making and interventions aiming at reducing and preventing environmental related diseases and contributes to an overall vision for public health. As a “Community of Practice”, INPHET focuses on sharing experiences and expertise; addressing common challenges for implementing and enhancing the science of EPHS/tracking; improving understanding of the link between the environment and health; and providing the appropriate evidence that informs public policy. The network, initiated in conference meetings in 2012-13 and formally launched in Modena, Italy in 2014, has carried out several activities which aim at sharing expertise and learning from different models of environmental and health data integration and surveillance systems that directly inform policy. These include Twinning cooperation with Euro-Asian and Balkan countries and sharing of expertise with African Public Health Agencies. Some experiences are presented in this workshop and highlight the EPHS/EPHT model adopted by several national public health agencies. It promotes that such integration and uses of environmental and health data is key for EPHS, including their accessibility and usability for communities of public health researchers, practitioners and policy makers.

IoT-Based Connected Environmental Monitoring System Using NodeMCU

The Connected Environmental Monitoring System leverages the NodeMCU ESP8266 microcontroller in conjunction with various sensors, including the MQ-135, DHT22, BMP280, and a sound sensor, to enable real-time monitoring of critical environmental parameters. This project aims to provide comprehensive insights into air quality, temperature, humidity, atmospheric pressure, and noise levels, fostering awareness and informed decision-making regarding environmental conditions. Data collected by the sensors is transmitted wirelessly to the ThingSpeak cloud platform, where it is stored and visualized through user-friendly dashboards. The system also incorporates alert mechanisms to notify users when specific parameters exceed predefined thresholds, facilitating timely interventions. The modular architecture of the system allows for scalability and flexibility, making it adaptable for various applications, including urban management and smart city initiatives. Overall, this project demonstrates the efficacy of IoT solutions in addressing environmental monitoring challenges, contributing to the development of sustainable practices and enhanced community well-being.

Hybrid Triboelectric‐Electromagnetic‐Electric Field Energy Harvester for Simultaneous Wind and Electric Field Energy Capture in High‐Voltage Transmission System

AbstractWith the development of smart grids, efficient condition monitoring of high voltage transmission system has become crucial, necessitating reliable power supplies for distributed sensors. Traditional energy harvesters often focus on either internal or external sources, limiting overall efficiency. This study introduces a triboelectric‐electromagnetic‐electric field hybrid energy harvester (TEE‐HEH) that synergistically integrates triboelectric nanogenerators (TENGs), electromagnetic generators (EMGs), and electric field energy harvesters (EEHs) to simultaneously capture electric field and wind energy. Electric field energy is harvested via displacement currents between transmission lines and the ground, while TENGs and EMGs efficiently capture low‐ and high‐speed wind energy, respectively, enabling broadband harvesting (2.3–10 m s−1). The synergistic combination of TENG, EMG, and EEH within the TEE‐HEH leads to significantly enhanced energy capture efficiency from multiple sources. At a wind speed of 5 m s−1, a transmission line voltage of 25 kV, and a distance of 1.5 m, the TEE‐HEH achieved peak power outputs of 18.5 mW (TENG), 262 mW (EMG), and 1.85 mW (EEH), demonstrating enhanced energy collection efficiency. An environmental monitoring system has been powered, demonstrating the TEE‐HEH's practicality for dual‐source energy harvesting in smart grid applications.

Fishes Associated with a Vulnerable Marine Ecosystem Network in the Central Mediterranean Sea

In order to collect information on ichthyofauna of a deep-sea vulnerable marine ecosystem (VME) network along the Apulian margin (central Mediterranean Sea), two low-impact sampling tools were used in three VMEs characterized by cold-water corals (CWC), namely Bari Canyon (BC), off Monopoli (Mn), and off Santa Maria di Leuca (SML). Using an experimental longline, 53 deployments were carried out between a 314 and 650 m depth for a total of 217 fishing hours, whereas when using the baited lander MEMO (Marine Environment MOnitoring system), 31 deployments were carried out between 427 and 792 m, for a total of 223 h of video recordings. A total of 37 taxa were recorded, comprising 13 Chondrichthyes and 24 Osteichthyes. The similarities in species observed among the VMEs confirm the presence of a network of CWC-VMEs along the Apulian margin, whereas some differences detected are due to the different abundance of some species, such as Galeus melastomus, Helicolenus dactylopterus, and Phycis blennoides. The presence of commercial species, vulnerable/endangered cartilaginous fishes, and large and sexually mature individuals of G. melastomus, H. dactylopterus, and Pagellus bogaraveo in all the VMEs confirms that the network of CWC-VMEs along the Apulian margin can act as a network of refuge areas and an essential fish habitat (EFH) for species threatened by fishing activities.

Machine learning for base transceiver stations power failure prediction: A multivariate approach

The widespread deployment of cellular networks has improved communication access, driving economic growth and enhancing social connections across diverse regions. Base Transceiver Stations (BTSs), are foundational to mobile networks but are vulnerable to power failures, disrupting service delivery and causing user inconvenience. This paper proposes a machine-learning-based framework for preemptive BTS power failure prediction using multivariate time-series data from power and environmental monitoring systems. We employ a combination of deep learning architectures, including Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and hybrid CNN-LSTM models, to achieve accurate and timely predictions of BTS power failures. CNNs were selected for extracting dependencies among features of a multivariate time-series data, while LSTMs effectively capture temporal dependencies, making them suitable for predicting power failures.The proposed models exhibit noteworthy predictive performance, with the LSTM network emerging as the most accurate model (MSE: 0.001, MAPE: 2.528), followed by the hybrid CNN-LSTM (MSE: 0.001, MAPE: 2.843) and the CNN (MSE: 0.223, MAPE: 2.843). This work demonstrates deep learning’s effectiveness in preemptive BTS failure prediction, enabling proactive maintenance and improved network resilience.

Design an Agricultural Soil and Environment Monitoring System Based on IoT

One of the problems farmers face is the inability to make complete, real-time, and accurate observations of their farmland. The system proposed in this paper helps farmers to know the condition of farmland from anywhere and anytime by using a web-based application. The main objective of this prototype is to reduce the failure of the growth process of farming commodities by knowing the conditions inside and outside the soil with a total of 14 parameters. Internet of Things (IoT) technology is used to implement the prototype, which consists of Sensor Panels, Controllers, Message Broker, and Backend Service. All obtained data, created and tested in real-time, are displayed on the application. In addition to real-time data display, the system also includes monitoring history, alerts, and site location management.

РАДІАЦІЙНИЙ СТАН ЗОНИ ВІДЧУЖЕННЯ В 2023 РОЦІ ЗА РЕЗУЛЬТАТАМИ РАДІАЦІЙНО-ЕКОЛОГІЧНОГО МОНІТОРИНГУ

The article presents results of radiation and environmental monitoring in the Exclusion Zone for the year 2023, after de-occupation of the territory, which was carried out in accordance with the current regulation of work, with the exception of objects on which it is temporarily impossible to carry out work due to the lack of safe access. In 2022, due to the full-scale invasion of russian federation, radiation monitoring of the environment was interrupted, monitoring of radiation-hazardous objects and environmental components of the Exclusion Zone was not carried out. Implementation of priority measures to restore the radiation and environmental monitoring system in the Exclusion Zone, after occupation by russian troops, made it possible to resume the work of the automated radiation monitoring system points, to create an additional network of measurement of gamma radiation indicators in the Exclusion Zone, to restore work of the central analytical laboratory and to restore the work of aspiration units. Thus, the enterprise resumed obtaining the necessary data on the dose rate of gamma radiation, information on the radiation state of the surface layer of the atmosphere, radiation state of surface and underground waters, radiation state of landscapes and places of residence of self-settlers. According to the results of radiation and environmental monitoring in the Exclusion Zone in 2023, important analytical data were obtained: - Maximum power values of the ambient dose equivalent of gamma radiation are characteristic of the territories in the northern and western 'traces' of radioactive fallout; - Radiation state of the Exclusion Zone air environment and its dynamics during 2023 were determined by the nature of surface contamination of the territory, man-made and biological factors, as well as meteorological conditions. Control levels exceeding by 2.5 times of 137Cs volumetric activity in the air was recorded in Chornobyl; - Surface waters remain an important route of radionuclide removal beyond the Exclusion Zone. Removal of 90Sr from Pripyat River in the area of Chornobyl in 2023 was at a level that was 2.4 times higher than the average value for the last 5 years; - As a result of observations of the radiation state of underground waters, it was determined that the average value of radionuclide contamination of eocene and cenomanian-lower cretaceous water-bearing complexes does not exceed 1 Bq/m3 for 137Cs and 5.7 Bq/m3 for 90Sr; - Monitoring results at landscape landfills indicate that the most contaminated component of the environment is the top layer of soil cover; - Radiation survey results of unauthorized residence places of the population in the Exclusion Zone showed that over the years there is an increase in the intake of 90Sr in the food products of 'self-settlers'.

A polydiacetylene (PDA)-based colorimetric sensor for on-site cyanide anion monitoring integrated with a lateral flow assay platform

An advanced sensing platform for the on-site and real-time monitoring of cyanide (CN−) pollution was developed, addressing the key challenges of enhancing the selectivity and sensitivity, whilst simplifying the sensing process. This platform features a novel colorimetric sensor (PDA-BMN) created by incorporating a receptor for CN− recognition within a polydiacetylene (PDA) conjugated polymer system. The interaction of CN− with the receptor distorted the π-conjugated backbone, causing a distinct color change from blue to orange, with a limit of detection (LOD) of 0.55 µM, thereby highlighting its high sensitivity. The PDA-BMN system was integrated into a lateral flow assay (LFA) strip to facilitate on-site monitoring. The LFA strip was strategically designed with a partially pressed zone to reduce the fluid flow rate, enhance the reaction time, and increase the probability of interaction with the PDA-BMN sensor. This innovation resulted in a significant colorimetric transition, enabling the rapid and sensitive detection of CN− without the requirement for analytical instruments. This study demonstrates the effectiveness of combining PDA and LFA systems for real-time environmental monitoring, offering a robust, efficient, and user-friendly solution for detecting CN− pollution.

ОБҐРУНТУВАННЯ РОЗШИРЕНОГО СКЛАДУ СПОСТЕРЕЖЕНЬ НА ВОДНО-БАЛАНСОВИХ СТАНЦІЯХ ТА ДОСЛІДНИЦЬКИХ ГІДРОГЕОФІЗИЧНИХ ПОЛІГОНАХ

The current level of understanding of the subordination and multifactorial dependence of the determining processes in the atmosphere, lithosphere and hydrosphere of the Earth requires a corresponding reorganization of the basic system of environmental monitoring, improvement and expansion of research on water these stations, which can become the supporting 'nodes' of the balance of this system. The appearance of fundamentally new theoretical developments, modern devices and equipment, a large number of software tools, etc., prompts a significant reorganization and strengthening of the environmental monitoring system. The article substantiates an additional set of studies, which should be included in the regulation of observations at already existing water balance stations, with their mandatory modernization. Spheres are subject to control - the atmosphere, surface and underground (subsurface) hydrospheres, which change over time at different rates and pedosphere. A certain inertia of hydrogeological processes implies the possibility of using meteorological indicators, which can be used to predict changes in the moisture regime in the aeration zone and shallow groundwater in the near future; based on the reliably predictable changes of the latter - to forecast changes in interlayer groundwater resources, etc. It is proposed to include in the monitoring regulations the following indicators of the state of the environment, which will allow to identify and analyze the causes of changes in the water situation, balance and resources, to determine the mechanisms of moisture transfer and accumulation, as well as to build models and perform predictive assessments. The results of comprehensive research at the «Lutiz» landfill demonstrate significant variability of hydrogeophysical indicators and changes in the intensity of natural signals depending on the landscape timing, the latest tectonics, the geological basis and the composition of the overlying sediments. Original devices are presented, which are used to determine indicators of electric and thermal fields, the ratio of positive and negative air ions, etc.

Advancements in Flexible and Stretchable Electronics for Resistive Hydrogen Sensing: A Comprehensive Review.

Flexible and stretchable electronics have emerged as a groundbreaking technology with wide-ranging applications, including wearable devices, medical implants, and environmental monitoring systems. Among their numerous applications, hydrogen sensing represents a critical area of research, particularly due to hydrogen's role as a clean energy carrier and its explosive nature at high concentrations. This review paper provides a comprehensive overview of the recent advancements in flexible and stretchable electronics tailored for resistive hydrogen sensing applications. It begins by introducing the fundamental principles underlying the operation of flexible and stretchable resistive sensors, highlighting the innovative materials and fabrication techniques that enable their exceptional mechanical resilience and adaptability. Following this, the paper delves into the specific strategies employed in the integration of these resistive sensors into hydrogen detection systems, discussing the merits and limitations of various sensor designs, from nanoscale transducers to fully integrated wearable devices. Special attention is paid to the sensitivity, selectivity, and operational stability of these resistive sensors, as well as their performance under real-world conditions. Furthermore, the review explores the challenges and opportunities in this rapidly evolving field, including the scalability of manufacturing processes, the integration of resistive sensor networks, and the development of standards for safety and performance. Finally, the review concludes with a forward-looking perspective on the potential impacts of flexible and stretchable resistive electronics in hydrogen energy systems and safety applications, underscoring the need for interdisciplinary collaboration to realize the full potential of this innovative technology.

Firm-Level Digitalization for Sustainability Performance: Evidence from Ningbo City of China

Climate change is a significant and urgent threat, gaining traction in the scientific community around the globe and requiring immediate action across many sectors. In this context, the digital economy could provide a mutually beneficial solution by utilizing innovation and technical breakthroughs to establish a sustainable future that addresses environmental deterioration, promotes economic growth, and encourages energy conservation. Against this background, this study examined the diffusion of innovation modeling-based factors affecting small and medium-sized firms’ (SMFs) adoption of the Internet of Things (IoT) technology and its impact on SMFs’ sustainability performance related to environmental, economic, innovation, and energy conservation perspectives. The key findings revealed that (i) the relative advantage, trialability, and observability drive IoT adoption. However, compatibility and complexity hinder IoT adoption. (ii) When prioritizing the adoption factors, the relative benefit is the strongest driver, and compatibility is the most significant barrier to IoT adoption. (iii) IoT technology adopter SMFs spent less on natural resources and more on renewable energy and environmental monitoring systems than non-adopter firms, boosting their environmental sustainability. (iv) IoT technology adopter firms had greater revenue, profits, and credit access than non-adopters and lower input costs, improving their economic sustainability. (v) IoT adopter firms spent more on innovative products than non-adopter enterprises, demonstrating innovation performance. (vi) Compared to non-adopter firms, IoT technology adopter SMFs had lower utility expenses and spent more on energy-efficient technologies. (vii) To realize the full potential of the IoT for a more sustainable and inventive future, authorities may pursue a variety of policy actions involving the strengthening and implementation of IoT technology standards and regulations, securing the incentivization of financial resources to SMFs, diverting the allocation of resources to research and development avenues, prioritizing the capacity development and environmental awareness, and focusing on IoT infrastructure development.