Environmental Monitoring System Research Articles

Evaluation of Autonomous Navigation and Path Accuracy for Unmanned Surface Vehicles Using IMU Sensor and GPS Data

The development of autonomous systems for environmental monitoring is becoming increasingly important. This project focuses on creating a robotic marine vessel, Aqua Sense, for efficient water quality monitoring. Existing methods are often labour-intensive, time-consuming, and lack real-time data capability. The objective is to develop a robotic vessel with autonomous navigation for water quality applications. A comprehensive design approach, including a literature review and careful component selection, was employed. Key components include the Arduino Mega, Blue Robotics T200 thruster, GlobalSat BU-353N5 GPS sensor, BNO055 Inertial Measurement Unit (IMU), and a Li-po 11.1v battery. In this paper, several field trials data collection is presented to evaluate the navigation algorithm. These findings validate the feasibility of Aqua Sense for real-world applications. The varying distance errors at points B and C demonstrate an error range, with a maximum error of approximately 1.130m at point B (about 0.11% of the target location) and a significant variation at point C, reaching up to 1.660m (approximately 0.15%).

An IoT Based Real-Time Environmental Monitoring System for Developing Areas

Rapid urbanization and industrialization have raised concerns about environmental quality and sustainability in recent years. The Internet of Things (IoT) has played an important role in monitoring physical phenomena by generating data that can be sent and preserved in the cloud. This work explores an IoT-based environmental monitoring system's potential, using an Arduino-based device for real-time tracking of environmental parameters including sound levels, humidity, dust concentration, total volatile organic compounds (TVOC), carbon dioxide (CO2), and carbon monoxide (CO). Real-time data are collected from various semi-residential and marketplace locations named in Pach raster More, Tomaltola, DowamoyiMore, Fojdarimore, and station road in Jamalpur district of Mymensingh Division, Bangladesh on non-holiday days, providing a representative snapshot of typical environmental conditions. The collected data is stored in a cloud server named firebase database. The implemented monitoring system offers several key features including accuracy and reliability, real-time monitoring data analytics alerts and notifications historical data as well as it can lead to various benefits and impacts of Improved Air and Water Quality Healthier Urban Environment (IAWUE) to enable local authorities and individuals to make educated decisions for a healthier and more sustainable urban environment. Graphical representations of the data revealed distinct patterns and trends, offering valuable insights into air quality variations across different areas. Interestingly, the results showed sound levels slightly below the standard range, indicating a relative control of noise pollution in the sampled areas. The findings of the work will serve as a vital resource for further research and guide policy-making for environmental improvement and sustainable practices in urban settings.

Artificial Intelligence-Assisted Environmental DNA Metabarcoding and High-Resolution Underwater Optical Imaging for Noninvasive and Innovative Marine Environmental Monitoring

To effectively protect the marine environment, it is crucial to establish effective environ mental monitoring platforms. Traditional marine environmental monitoring methods heavily rely on morphological identification and field expertise, with the sampling process being disruptive and potentially destructive to vulnerable marine environments. In light of emerging biomonitoring needs and biodiversity declines, we reviewed the urgently needed, ongoing advances in developing effective, noninvasive, and innovative monitoring methods and systems to examine the complex marine environment for better strategic conservation and protection, using the coral ecosystem as one of the representative forefront examples in marine protection. This review summarizes current trends and efforts in transitioning into more standardizable and automatable utilizations of environmental DNA metabarcoding-based monitoring strategies and high-resolution underwater optical imaging monitoring systems as two of the promising pillars for the next generation of noninvasive biomonitoring and associated applications. The assistance of artificial intelligence for environmental DNA metabarcoding and high-resolution underwater optical imaging into an empowered, all-rounded monitoring platform for enhanced monitoring capacity is discussed as a highly potent direction for future research exploration. This review will be a cornerstone reference for the future development of artificial intelligence-assisted, noninvasive, and innovative marine environmental monitoring systems.

REAL-TIME DETECTION AND CLASSIFICATION OF FISH IN UNDERWATER ENVIRONMENT USING YOLOV5: A COMPARATIVE STUDY OF DEEP LEARNING ARCHITECTURES

This article explores techniques for the detection and classification of fish as an integral part of underwater environmental monitoring systems. Employing an innovative approach, the study focuses on developing real-time methods for high-precision fish detection and classification. The implementation of cutting-edge technologies, such as YOLO (You Only Look Once) V5, forms the basis for an efficient and responsive system. The study also evaluates various approaches in the context of deep learning to compare the performance and accuracy of fish detection and classification. The results of this research are expected to contribute to the development of more advanced and effective aquatic monitoring systems for understanding underwater ecosystems and conservation efforts.

Design and Application of Intelligent Building Environment Monitoring System Based on Wireless Sensor Network

Design and Application of Intelligent Building Environment Monitoring System Based on Wireless Sensor Network

Integrating radiological technology in environmental health surveillance to enhance public safety

The integration of radiological technology into environmental health surveillance represents a significant advancement in enhancing public safety. Radiological technologies, including advanced imaging and monitoring systems, offer powerful tools for detecting and assessing environmental hazards that impact public health. This review explores the potential benefits, methodologies, and challenges associated with integrating radiological technology into environmental health surveillance. Recent advancements in radiological technology, such as high-resolution imaging systems and portable radiation detectors, have greatly improved the ability to monitor and analyze environmental radiation levels with precision. These technologies enable real-time detection of radiation exposure, providing critical data for assessing risks associated with radiation sources, such as industrial activities, nuclear power plants, and natural radioactive materials. By integrating these tools into environmental health surveillance frameworks, public health agencies can enhance their capacity to identify and address radiation-related hazards more effectively. The application of radiological technology in environmental health surveillance facilitates comprehensive monitoring of radiation levels across various environments, including urban, rural, and industrial areas. This data is crucial for identifying contamination hotspots, tracking changes in radiation levels over time, and evaluating the effectiveness of radiation control measures. Additionally, the integration of radiological technology supports the development of predictive models for assessing potential health impacts and guiding emergency response strategies in the event of radiation incidents. Despite its advantages, integrating radiological technology into environmental health surveillance presents several challenges. These include the high costs of advanced equipment, the need for specialized training for personnel, and the management of large volumes of data generated by monitoring systems. Addressing these challenges requires a coordinated approach involving government agencies, research institutions, and industry stakeholders to ensure effective implementation and sustainability. In conclusion, integrating radiological technology into environmental health surveillance has the potential to significantly enhance public safety by providing accurate and timely data on radiation exposure. Continued innovation and collaboration in this field will be essential for optimizing the benefits of radiological technology and addressing the challenges associated with its integration into environmental health monitoring systems. Keywords: Integrating; Radiological Technology; Environmental Health Surveillance; Enhance; Public Safety

Integrated Approach for Human Wellbeing and Environmental Assessment Based on a Wearable IoT System: A Pilot Case Study in Singapore.

This study presents the results of the practical application of the first prototype of WEMoS, the Wearable Environmental Monitoring System, in a real case study in Singapore, along with two other wearables, a smart wristband to monitor physiological data and a smartwatch with an application (Cozie) used to acquire users' feedback. The main objective of this study is to present a new procedure to assess users' perceptions of the environmental quality by taking into account a multi-domain approach, considering all four environmental domains (thermal, visual, acoustic, and air quality) through a complete wearable system when users are immersed in their familiar environment. This enables an alternative to laboratory tests where the participants are in unfamiliar spaces. We analysed seven-day data in Singapore using a descriptive and predictive approach. We have found that it is possible to use a complete wearable system and apply it in real-world contexts. The WEMoS data, combined with physiology and user feedback, identify the key comfort features. The transition from short-term laboratory analysis to long-term real-world context using wearables enables the prediction of overall comfort perception in a new way that considers all potentially influential factors of the environment in which the user is immersed. This system could help us understand the effects of exposure to different environmental stimuli thus allowing us to consider the complex interaction of multi-domains on the user's perception and find out how various spaces, both indoor and outdoor, can affect our perception of IEQ.

Environmental noise monitoring using distributed hierarchical wireless acoustic sensor network

Acoustic noise pollution is one of many problems people face as cities grow. Long-term noise exposure can result in a series of physical and mental health diseases that are highly harmful to foetuses and newborns. Hence, many IoT-based wireless sensor network systems have been proposed for automated monitoring for long-term operation. However, these systems suffer from weaknesses in functionality, power consumption, costs, and scalability, which hinder large-scale deployment. In this study, we propose a distributed hierarchical wireless acoustic sensor network for environmental noise monitoring to do sound classification and A-weighted sound-pressure-level measurement to address the shortcomings of existing systems. A series of tests and comparisons are performed in diagnosing the performance with respect to recording continuity, packet loss, recording quality, accuracy on A-weighted sound pressure level calculations, and costs. Results show that this proposed network structure is feasible as a part of hardware implementation in a large-scale, low-cost, and high-scalable environmental noise monitoring system to classify sound.

Environmental monitoring system design based on STM32 platform

This study addresses the current societal demand for environmental monitoring by designing an environmental monitoring system based on the STM32 platform. This system assesses and monitors environmental conditions in real-time by tracking parameters such as CO, PM2.5, temperature, humidity, and light intensity. It holds significant value in preventing air pollution and improving indoor air quality. The system employs four types of sensors: the DHT11 digital temperature and humidity sensor, the BH1750FV light sensor, the GP2Y1010AUOF optical dust sensor, and the MQ-7 CO sensor to collect environmental data, which is then processed by the STM32F103C8T6 controller. This system is characterized by its real-time capabilities, high precision, and low power consumption, making it highly practical and valuable for widespread application. The paper provides a detailed discussion of sensor selection, measurement algorithms, and system design and implementation, offering valuable insights for research and applications in related fields.

Environmental monitoring system design based on STM32 platform

Environmental monitoring system design based on STM32 platform

Graphene-Liquid Crystal Synergy: Advancing Sensor Technologies across Multiple Domains.

This review explores the integration of graphene and liquid crystals to advance sensor technologies across multiple domains, with a focus on recent developments in thermal and infrared sensing, flexible actuators, chemical and biological detection, and environmental monitoring systems. The synergy between graphene's exceptional electrical, optical, and thermal properties and the dynamic behavior of liquid crystals leads to sensors with significantly enhanced sensitivity, selectivity, and versatility. Notable contributions of this review include highlighting key advancements such as graphene-doped liquid crystal IR detectors, shape-memory polymers for flexible actuators, and composite hydrogels for environmental pollutant detection. Additionally, this review addresses ongoing challenges in scalability and integration, providing insights into current research efforts aimed at overcoming these obstacles. The potential for multi-modal sensing, self-powered devices, and AI integration is discussed, suggesting a transformative impact of these composite sensors on various sectors, including health, environmental monitoring, and technology. This review demonstrates how the fusion of graphene and liquid crystals is pushing the boundaries of sensor technology, offering more sensitive, adaptable, and innovative solutions to global challenges.

Development of an Internet of Things-based Environmental Information System for Realtime Monitoring of Air Conditions

This study aims to develop an environmental information system called the Environmental Monitoring System (EENNOS) to monitor air environmental conditions. ENNOS is an Internet of Things (IoT) based system that monitors air environmental conditions in the form of temperature, humidity and carbon dioxide. The research was conducted using the 4D development method which consisted of the Define, Design, Develop, and Disseminate stages. EENNOS was developed using a DHT 22 sensor for DHT 22 temperature and humidity and a carbon dioxide sensor with MQ-135. The controller used is Arduino uno ESP8266 with output sending using the internet to the database and presented on the dashboard and displayed on a 16x2 liquid crystal screen. The output is in the form of dashboard innovations that are registered with copyrights and scientific publications in the form of articles in the Journal of Environmental Sciences.

Performances of halide scintillators for the dosimetry based on gamma-ray spectrometry for environmental monitoring systems

High pressure ion chambers (HPIC) and NaI(Tl) scintillation detectors are widely used to monitor the ambient dose equivalent rate H*(10) within and around the Korean nuclear facilities. However, HPIC cannot provide spectrometric information and NaI(Tl) detector is limited in identifying nuclides, such as 131I, 134Cs, and 137Cs, released from nuclear facilities owing to its insufficient energy resolution. This study employed four halide scintillators – LaBr3(Ce), CeBr3, and SrI2(Eu) – to measure the ambient dose equivalent rate and detect gamma nuclides from measured energy spectrum. First, the pulse–shaping time in the signal processing unit was optimized for each scintillator. Second, energy resolution and counting efficiency were estimated for 137Cs and 60Co. Finally, an irradiation test was performed to estimate the dose rate. Based on these results, LaBr3(Ce) and NaI(Tl) were selected as in situ gamma spectrometry system for measuring environmental radiation, and field experiments were conducted near the Fukushima Daiichi nuclear power plant to measure the dose rate.

AI-based data mining approach to control the environmental impact of conventional energy technologies

Environmental pollution remains one of the foremost existential threats to human well-being, despite the concerted efforts and implementation of various programmes aimed at fostering cleaner air. The contemporary global economic and energy landscape, characterised by multifaceted challenges, has undeniably hindered the efficacy of efforts to kerb air pollutant emissions. Solid fuels persist as primary sources of energy production in numerous countries, serving both the residential and industrial sectors. However, combustion of such fuels, particularly within domestic heating units (DHUs), engenders the release of a diverse array of organic compounds characterised by intricate structures and potent mutagenic and environmentally hazardous properties.However, the combustion process, if properly regulated, can be carried out in an environmentally sustainable manner. The intricate interplay of myriad factors that influence the composition and quality of chimney flue gases underscores the complexity inherent in controlling the combustion process. Artificial intelligence (AI) has emerged as a versatile tool with applications that span various domains, including environmental monitoring systems. In this study, we posit the utilisation of artificial neural networks (ANNs) as a sophisticated data mining technique to control the emission of flue gases contingent on the specific boiler and fuel utilised. Feed forward predictive models with back propagation were utilized for AI-based data mining aiming at the prediction of the concentration of flue gas components. The highest coefficients of model fit goodness were obtained for CO2, NOx and SO2 with R2 equal to 0.99, 0.98 and 0.99, respectively. The study demonstrated the feasibility and effectiveness of using AI-based data mining to predict emissions from conventional energy technologies. By leveraging the predictive capabilities of ANNs, it is possible to significantly reduce the environmental impact of solid fuel combustion, contributing to cleaner air and improved public health.

An optical measurement method of DC total electric field with space charges based on probe self-rotation modulation

Researching the measurement of DC total electric field with space charges (Poisson field) can help establish a monitoring system for the electromagnetic environment of UHVDC transmission lines and protect the health of the ecological environment. This paper proposes a DC total electric field optical measurement method based on the Pockels effect and probe self-rotation modulation. It can address the issues of internal charge drift and external charge accumulation in traditional optical probes when measuring DC electric fields with space charges. Theoretical analysis was conducted on measurement under probe rotation, and the optical modulation system was integrated into a probe with dimensions of 60 mm × 30 mm × 20 mm. A self-rotating platform for the probe was designed, and the influence of rotation mode on the results was analyzed. It was found that the sensitivity was higher when using the horizontal-horizontal mode. The signal processing system was tested, showing that the probe retained around 50 % of its original output when rotating at low speeds (frequency 1–3 Hz), fully meeting the measurement requirements. The test platform has been constructed, and the probe’s sensitivity was assessed under an AC electric field and validated under a DC electric field. Finally, the optical method proposed in this paper was used to measure the DC total electric field with space charges under a small model of a unipolar HVDC transmission line. Five locations under the line were selected as measurement points, and the results were compared with those obtained from a field mill probe and numerical simulation. This comparison indicates that the proposed method agrees with experimental and simulation results. The average sensitivity of the self-rotating optical probe was 3.71 mV/(kV/m). The error did not exceed 5 % in high-field strength areas (above 20 kV/m) and was also controlled within 15 % in low-field strength areas (below 20 kV/m).

Environmental and legal aspects of the armed aggression of the Russian Federation against Ukraine

The article examines the environmental and legal aspects of the armed aggression of the Russian Federation against Ukraine. The problems of bringing the aggressor state to responsibility for ecocide are analyzed. Having found a legislative enshrinement in the national criminal law (Article 441 of the Criminal Code of Ukraine), ecocide has not been enshrined in international criminal law. It is not recognized as a crime either in the Rome Statute of the International Criminal Court or in any other international legal act. As of today, Russian crimes against the environment can be investigated by the International Criminal Court as war crimes. The author of the article supports the proposal regarding the need to include the crime of ecocide in the Rome Statute. The ecological and legal aspect of the formation of an international compensation mechanism is studied, the components of which are: 1) an international register of damages; 2) compensation commission (which will consider individual applications for compensation by the Russian Federation for losses from citizens, companies and the state); 3) compensation fund (which will accumulate funds to pay commission decisions, including at the expense of confiscated Russian assets). The mechanism of compensation for environmental damage caused as a result of the armed aggression of the Russian Federation against Ukraine is analyzed, and ways of its optimization are proposed. The future compensation mechanism should be based on the «ecosystem services approach», which will significantly increase the amount of environmental damage that the Russian Federation will pay to Ukraine. The international practice of compensation for environmental damage caused by the aggressor as a result of military actions and temporary occupation was studied and analyzed. The author emphasized the need to reform the state environmental monitoring system. Without reliable monitoring data, it is difficult to prove a causal relationship between the illegal actions of the aggressor state and the damage caused to the environment.

Digitalization as a guarantee of the right to environmental information

The article is devoted to the study of the legal framework for the use of information technologies as a component of the legal mechanism for realization of the right to environmental information. The author notes that in forming the legal framework for digitalization of environmental relations, the need to use digital technologies to create conditions for universal accessibility of environmental information and to raise environmental awareness is crucial. The author emphasizes that digitalization is at the same time a guarantee of the constitutional right of citizens to have access to information on the state of the environment. A systematic analysis of the legal provisions which form the basis for the digitalization of environmental impact assessment and strategic environmental assessment and which serve as guarantors of the right to environmental information is carried out. The author emphasizes the need to improve the State system of environmental monitoring and information support of public administration. The article examines the service of recording the facts of environmental damage caused by emergencies, events, and armed aggression of the Russian Federation “EcoThreat”, which aims at recording the facts of environmental damage to the environment not only for prompt response, forecasting, management decision-making, reporting and planning regarding the recorded facts of environmental damage, as well as to ensure that citizens can exercise their rights in terms of free access to up-to-date information on recorded facts of damage to the environment as a result of emergencies, events, and armed aggression of the russian federation. It is summarized that the significant potential of digital technologies for social development is important for ensuring public access to the environmental sphere, expanding cooperation of civil society with public authorities and business, opening up new opportunities for the realization of environmental rights and meeting the environmental needs of citizens, and ensuring an improvement in the quality of the environment and the range of public services.

Introducing PLEMS: the application of a low-cost, portable monitoring system in environmental walks.

The application of innovative systems using low-cost microcontrollers in human biometeorology studies is a promising alternative to conventional monitoring devices, which are usually cost-intensive and provide measurements at specific points, as in stationary meteorological stations. A Portable Low-cost Environmental Monitoring System (PLEMS) aimed at the pedestrian scale is introduced. The backpack-type equipment consists of a microcontroller with attached sensors that assess environmental conditions in a broad sense, integrating measurements of air quality, lighting and noise levels alongside variables typically measured at meteorological stations. The application of the system took place in altogether 12 environmental walks carried out with questionnaire-surveys with concurrent environmental monitoring with the PLEMS in Curitiba, Brazil, a subtropical location characterized by a Cfb climate type. Results allowed us to test the equipment and method of data gathering within a limited period (approximately 50 min) and for a short walking circuit of 800 m. The equipment was successfully able to capture even slightest differences in environmental conditions among points of interest, whereas subjective responses (n= 3843 responses to a total of 11 questions) showed consistency with measured data. From a multi-domain perspective, relevant insights could be obtained for the measured variables.

Nature management history and prospects for improving environmental monitoring in Galapagos Islands (Republic of Ecuador)

Background. The system of environmental monitoring in the Republic of Ecuador and its history is considered using the Galapagos Islands as an example. The need for its modification with the purpose of preventing the negative consequences of human activity is substantiated.Aim. To assess the environmental consequences of anthropogenic activity in the Galapagos Islands and to propose a unified environmental monitoring system for two protected natural areas of the Galapagos Islands.Materials and methods. The current laws and legislative acts related to the activity of the Republic of Ecuador state institutions in the field of environmental monitoring were analyzed. Statistical data and reports on monitoring programs in the Galapagos Islands were reviewed.Results. A unique environmental monitoring program for two protected natural areas of the Galapagos Islands was developed. It is recommended to complement the program with a system of stationary observations. This system is aimed at collecting data for assessing the impact of socioeconomic activity on the nature of the islands, monitoring the state of ecosystems, rare, endemic and invasive species, as well as for conducting scientific research to restore populations.

Ocean wave energy harvesting with high energy density and self-powered monitoring system

Constructing a ocean Internet of Things requires an essential ocean environment monitoring system. However, the widely distributed existing ocean monitoring sensors make it impractical to provide power and transmit monitored information through cables. Therefore, ocean environment monitoring systems particularly need a continuous power supply and wireless transmission capability for monitoring information. Consequently, a high-strength, environmentally multi-compatible, floatable metamaterial energy harvesting device has been designed through integrated dynamic matching optimization of materials, structures, and signal transmission. The self-powered monitoring system breaks through the limitations of cables and batteries in the ultra-low-frequency wave environment (1 to 2 Hz), enabling real-time monitoring of various ocean parameters and wirelessly transmitting the data to the cloud for post-processing. Compared with solar and wind energy in the ocean environment, the energy harvesting device based on the defective state characteristics of metamaterials achieves a high-energy density (99 W/m3). For the first time, a stable power supply for the monitoring system has been realized in various weather conditions (24 h).