About Some Aspects of Use of Optical Sensors for Monitoring the Aquatic Environment

Multi-channel polarization optical technology is increasingly used for prompt monitoring of water systems.Optical devices during the assessment of water quality determine the intensity of light through the studied aquatic environment.Spectrophotometric devices measure the spectrum of weakening of light through the aquatic environment.Spectroellipsometric devices receive spectra in vertical and horizontal polarizations.The presented article develops an adaptive optical hardware and image system for monitoring water bodies.The system is combined.It consists of 2 parts:1)automated spectrophotometer-refractometer,and 2)adaptive spectroellipsometer.The system is equipped with a corresponding algorithmic and software,including algorithms for identifying spectral curves,databases and knowledge of spectral curves algorithms for solving reverse problems.The presented system is original since it differs from modern foreign systems by a new method of spectrophotometric and spectroellipsometric measurements,an original elemental base of polarization optics and a comprehensive mathematical approach to assessing the quality of a water body.There are no rotating polarization elements in the system.Therefore,this makes it possible to increase the signal-to-noise ratio and,as a result,improve measurement stability and simplify multichannel spectrophotometers and spectroellipsometers.The proposed system can be used in various water systems where it is necessary to assess water quality or identify the presence of a certain set of chemical elements.

Improving autoencoder-based unsupervised damage detection in uncontrolled structural health monitoring under noisy conditions

Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enhance the performance of guided wave damage detection in noisy environments is crucial.This paper introduces a local temporal principal component analysis(PCA)reconstruction approach for denoising guided waves prior to implementing unsupervised damage detection,achieved through novel autoencoder-based reconstruction.Experimental results demonstrate that the proposed denoising method significantly enhances damage detection performance when guided waves are contaminated by noise,with SNR values ranging from 10 to-5 dB.Following the implementation of the proposed denoising approach,the AUC score can elevate from 0.65 to 0.96 when dealing with guided waves corrputed by noise at a level of-5 dB.Additionally,the paper provides guidance on selecting the appropriate number of components used in the denoising PCA reconstruction,aiding in the optimization of the damage detection in noisy conditions.

Key Environmental Factors Monitoring System of Low-power Greenhouse Based on WSN Technology

A low-power environmental monitoring system based on WSN technology is proposed to effectively monitor the environmental status and ensure the healthy growth of greenhouse crops in the greenhouse. The system performs dynamic mon- itoring on the environmental data of temperature, humidity, illumination, soil tempera- ture and humidity of the greenhouse, and it reduces the energy consumption by us- ing solar energy and lithium battery as the power supply mode and dynamic power management algorithm combined with improved routing protocol. Stable and reliable, the system could effectively monitor the key environmental factors in the green- house, making it of certain promotion value.

Design of IoT-based Volatile Organic Compounds Monitoring System

Volatile organic compounds(VOC)gas detection devices based on semiconductor sensors have become a common method due to their low cost,simple principle,and small size.However,with the continuous development of materials science,various new materials have been applied in the fabrication of gas sensors,but these new materials have more stringent requirements for operating temperature,which cannot be met by existing sensor modules on the market.Therefore,this paper proposes a temperature-adjustable sensor module and designs an environmental monitoring system based on the STM32F103RET6 microprocessor.This system primarily utilizes multiple semiconductor gas sensors to monitor and record the concentrations of various harmful gases in different environments.It can also monitor real-time temperature,humidity,and latitude and longitude in the current environment,and upload the data to the Internet of Things via 4G communication.This system has the advantages of small size,portability,and low cost.Experimental results show that the sensor module can achieve precise control of operating temperature to a certain extent,with an average temperature error of approximately 3%.The monitoring system demonstrates a certain level of accuracy in detecting target gases and can promptly upload the data to a cloud platform for storage and processing.A comparison with professional testing equipment shows that the sensitivity curves of each sensor exhibit similarity.This study provides engineering and technical references for the application of VOC gas sensors.

Optimal edge-cloud collaboration based strategies for minimizing valid latency of railway environment monitoring system

Response speed is vital for the railway environment monitoring system,especially for the sudden-onset disasters.The edge-cloud collaboration scheme is proved efficient to reduce the latency.However,the data characteristics and communication demand of the tasks in the railway environment monitoring system are all different and changeable,and the latency contribution of each task to the system is discrepant.Hence,two valid latency minimization strategies based on the edge-cloud collaboration scheme is developed in this paper.First,the processing resources are allocated to the tasks based on the priorities,and the tasks are processed parallly with the allocated resources to minimize the system valid latency.Furthermore,considering the differences in the data volume of the tasks,which will induce the waste of the resources for the tasks finished in advance.Thus,the tasks with similar priorities are graded into the same group,and the serial and parallel processing strategies are performed intra-group and inter-group simultaneously.Compared with the other four strategies in four railway monitoring scenarios,the proposed strategies proved latency efficiency to the high-priority tasks,and the system valid latency is reduced synchronously.The performance of the railway environment monitoring system in security and efficiency will be promoted greatly with the proposed scheme and strategies.

Internet based environmental monitoring information system and its application in Yili Prefecture

With the development of Internet technologies, Internet Based Information System (IBIS) arises with more advantages: Firstly, it is convenient for users to use owing to the introduction of Internet technologies. Secondly, it benefits greatly the data dissemination and data sharing based on Internet. The most important but not the last is that we can establish the information service network supported by its technologies and the facilities of information highway. So, it would be significant to design IBIS to realize the data collection, sharing and dissemination on Internet. There are many factors affecting regional environment. So it is not easy to realize the integrated environmental monitoring. Given this, we designed the Internet based environmental monitoring information system. By the virtue of the Internet based environmental monitoring information system, the management and storage of environmental monitoring data would be easier, which lays the foundation to actualize the environmental monitoring efficiently.

Environmental monitoring and fuzzy synthetic evaluation of municipal solid waste transfer stations in Beijing in 2001-2006

Transfer station(TS)is an integral part of present-day municipal solid waste(MSW)management systems.To provide information for the incorporation of waste facilities within the current integrated waste management system,the authors measured the existing environmental quality at five MSW TSs.Discharged wastewater,air,and noise were monitored and assayed at the five TSs in Beijing in 2001-2006 during rainy seasons(RSs)and dry seasons(DSs).Except Ammonia(NH_3)and hydrogen sulfide(H_2S),the analytical results of...

Environmental monitoring of the Zhujiang Estuary and its coastal waters

The Zhujiang (Pearl River) Estuary is a complex water system whose catchments basincovers a very large part of southern China. The large quantity of fresh water carried by the river system flows into the northern coast of the South China Sea through its eight inlets. The Zhujiang River Delta has experienced the fastest economic growth in China during the past two decades. Rapid population expansion and increased industrial development coupled with insufficient waste management turned the Zhujiang Estuary into waste disposal channels just before entering the coastal waters. The water quality of the estuaries and the coastal oceans has become polluted. During the past two years, an intensive study and monitoring efforts of the pollutions of these waters have been made. A systematic and integrated monitoring task including shore-based measurements, shipboard in-situ measurements, and satellite and radar remote sensing surveys has been completed. Comprehensive collection of physical, chemical and biological parameters has been accomplished and a database has been established. Unlike the previous large scale-monitoring task in which the various pollutant concentrations were the objective, the present study aims to understand the process of the pollution from their initial disposal to their final states. The understanding of the processes makes it possible to evaluate the severity of the pollution with respect to the sustainability. Also the objective is to incorporate these processes into the mathematical models from which a predictive capability of the pollution situation can be realized. The present presentation will describe the planning, methodology and the results of this effort.

Monitoring and Assessment of Current Situation of Environmental Quality in Yueqing Bay

Based on the monitoring results of environmental quality in Yueqing Bay during 2007-2014,the current situation of environmental quality in the bay was analyzed and assessed. The results show that pH,DO,CODMn,petroleum,and heavy metals( Cu,Pb,Zn,Cd,Hg,As and Cr)in the seawater of Yueqing Bay did not exceed the second class standard of Seawater Quality Standard( GB 3097-1997),but inorganic nitrogen and reactive phosphate in the seawater of Yueqing Bay exceeded the second class standard seriously,and the water quality of the bay was in an eutrophic state; the standard index of evaluation factors of sediment quality was smaller than 1,meeting the demands of sediment quality for environmental protection.

Monitoring and Evaluation of Present Situation of Environmental Quality in the Sea Area near the Aojiang Estuary in Wenzou

Based on the monitoring results of environmental quality in the sea area near the Aojiang estuary in Wenzou during 2010-2012,the present situation of environmental quality in the sea area was analyzed and evaluated. The results show that p H,DO,CODMn,petroleum,and heavy metals( Cu,Pb,Zn,Cd,Hg,As and Cr) in the sea area near the Aojiang estuary did not exceed the second-class standard of Seawater Quality Standard( GB 3097-1997),but both inorganic nitrogen and reactive phosphate in the sea area exceeded the second-class standard seriously,and the water quality of the sea area was in an eutrophic state; domestic sewage and fertilizer loss were the main sources of nitrogen and phosphorus. The standard index of most evaluation factors of sediment quality except for Zn was smaller than 1,meeting the demands of sediment quality for environmental protection.

Remote sensing-based dynamic monitoring and environmental change of wetlands in southern Mongolian Plateau in 2000‒2018

The environmental change in the wetlands in the southern Mongolian Plateau has important impacts on the environment of North China and even the entire Northeast Asia,from which the global climate change can be understood on a large scale,especially the climate change in the Mongolian Plateau.This study extracted the information on the wetlands from three stages of remote sensing images(also referred to as RS images)of the study area,including Enhanced Thematic Mapper Plus(ETM+)images of 2000,TM images of 2010,and Landsat 8 Operational Land Imager(OLI)images of 2018.As indicated by the extraction results,the area of wetlands decreased from 796.90 km^(2) of 2000 to 666.24 km^(2) of 2018 at a rate of 7.26 km^(2)/a.The reduced area is 130.66 km^(2),which is about 16.4%reduction.And the patch number of wetlands decreased from 731 of 2000 to 316 of 2018 in the study area,approximately 56.8%reduction(415 patches),and the decrease in the area of the wetlands mainly occurred in the northwest endorheic region.In terms of wetland types,the change of the wetlands was dominated by the decrease of lacustrine wetlands,of which the area and patch number decreased by 106.2 km^(2) and 242,respectively.Furthermore,the area of the lacustrine wetlands decreased at the highest rate of 8.70 km^(2)/a in 2010‒2018.From the perspective of spatial distribution,the wetlands in the western part shrunk more notably than those in the eastern part as a whole in the study area.According to local meteorological data,the precipitation gently decreased and the temperature increased(about 1.7℃)from 1975-2018.Overall,the decrease in the area of the wetlands and the temperature rises in the study area were mainly driven by the Mongolian monsoon climate,reduction in precipitation,and human activities.

A Multi-Agent System for Environmental Monitoring Using Boolean Networks and Reinforcement Learning

Distributed wireless sensor networks have been shown to be effective for environmental monitoring tasks,in which multiple sensors are deployed in a wide range of the environments to collect information or monitor a particular event,Wireless sensor networks,consisting of a large number of interacting sensors,have been successful in a variety of applications where they are able to share information using different transmission protocols through the communication network.However,the irregular and dynamic environment requires traditional wireless sensor networks to have frequent communications to exchange the most recent information,which can easily generate high communication cost through the collaborative data collection and data transmission.High frequency communication also has high probability of failure because of long distance data transmission.In this paper,we developed a novel approach to multi-sensor environment monitoring network using the idea of distributed system.Its communication network can overcome the difficulties of high communication cost and Single Point of Failure(SPOF)through the decentralized approach,which performs in-network computation.Our approach makes use of Boolean networks that allows for a non-complex method of corroboration and retains meaningful information regarding the dynamics of the communication network.Our approach also reduces the complexity of data aggregation process and employee a reinforcement learning algorithm to predict future event inside the environment through the pattern recognition.

Study on the System of Aquatic Environmental Monitoring Methods in China

The development of Chinese system of aquatic environmental monitoring methods was summarized. The existing problem of the system of aquatic environmental monitoring methods was analyzed. At last, some suggestions were made on setting and implementing the system of aquat- ic environmental monitoring methods in China.

Big Data Analytics with Artificial Intelligence Enabled Environmental Air Pollution Monitoring Framework

Environmental sustainability is the rate of renewable resourceharvesting, pollution control, and non-renewable resource exhaustion. Airpollution is a significant issue confronted by the environment particularlyby highly populated countries like India. Due to increased population, thenumber of vehicles also continues to increase. Each vehicle has its individualemission rate;however, the issue arises when the emission rate crosses thestandard value and the quality of the air gets degraded. Owing to the technological advances in machine learning (ML), it is possible to develop predictionapproaches to monitor and control pollution using real time data. With thedevelopment of the Internet of Things (IoT) and Big Data Analytics (BDA),there is a huge paradigm shift in how environmental data are employed forsustainable cities and societies, especially by applying intelligent algorithms.In this view, this study develops an optimal AI based air quality prediction andclassification (OAI-AQPC) model in big data environment. For handling bigdata from environmental monitoring, Hadoop MapReduce tool is employed.In addition, a predictive model is built using the hybridization of ARIMAand neural network (NN) called ARIMA-NN to predict the pollution level.For improving the performance of the ARIMA-NN algorithm, the parametertuning process takes place using oppositional swallow swarm optimization(OSSO) algorithm. Finally, Adaptive neuro-fuzzy inference system (ANFIS)classifier is used to classify the air quality into pollutant and non-pollutant.A detailed experimental analysis is performed for highlighting the betterprediction performance of the proposed ARIMA-NN method. The obtainedoutcomes pointed out the enhanced outcomes of the proposed OAI-AQPCtechnique over the recent state of art techniques.

Monitoring and Environmental Assessment of Seawater in West Central Africa: Case of the Kribi Industrial and Urban Port Complex in Cameroon, Guinea Gulf

This study is the first of a series of a project on the development and implementation of environmental protection policies, before, during and after the construction of the Kribi Industrial and Urban Port Complex (KIPC). The results will equip the State and scientific structures concerned with the protection of people, water resources and the environment as a whole. This includes reference data on the state of marine pollution in the region dating from the end of realization of the first phase of KIPC known as Kribi Deep-Water Harbor (KDWH). Accordingly, the aim of this work is to assess the current state of KIPC and its surrounding by quantifying the preliminary parameters of suspended matter (SM);to analyze the physical and chemical parameters, chemical pollution indicators for anions and major cations and organic pollution indicators of four water samples taken from four different sites in the project area by filtration and weighing, pH meter, turbid meter, titration, colorimetry and titrimetric methods. The analysis of these samples and these parameters provides results which are slightly similar to international standards. This suggests that the environment remains relatively healthy. Hence, continuous management and monitoring of the parameters and pollution factors is strongly recommended.

A Design of Modern Greenhouse Environmental Monitoring System

Based on the problems in the current greenhouse environmental monitoring system such as difficult connection layout,low flexibility and high costs,this paper builds the greenhouse environmental monitoring system based on wireless sensor network,and designs the sensor nodes and gateway nodes. The sensor nodes of this system are responsible for collecting environmental parameters and sending the data to gateway nodes via wireless sensor network. And the gateway nodes transmit the data to the remote monitoring platform. The microprocessor module of node hardware uses MSP430F149 microprocessor for data processing and control; wireless communication module consists of nRF905 RF chip and peripheral circuit,responsible for transmitting and receiving data; sensor module uses AM2301 sensor for data measurement; the power supply module uses the circuit consisting of LT1129-3. 3,LT1129-5 and Max660 to provide 3. 3 and ± 5V power. The C language development is employed for wireless routing protocol of node and time synchronization algorithm,to achieve node data acquisition and processing,rule forwarding and remote transmission. Remote monitoring software uses NET. ASP,HTML and C# development to provide visual WEB mode remote data management platform for users. The system goes through networking testing in greenhouse in Xining City,and test results show that the system operation is stable and reliable,and the average network packet loss rate is 2. 4%,effectively solving the problems in greenhouse environmental monitoring system and meeting the application requirements of greenhouse cultivation environmental monitoring.

PEAT GEOCHEMICAL MONITORING FORENVIRONMENTAL CHANGES

High peat is a good message carrier of atmospheric geochemical environment .The distribution of heavy metals monitored in vertical vertion of high peat is the reflection of sequence atmospheric chemical composition. It can record and remain thenatural geochemical background of the atmosphere. The changes of heavy metal contets in sections of the Da Hinggan Mountainsmanifest that the influence of human human on atmosphere is continuously becoming heavier. Compared with other areas inEurasia, the atmospheric geochemical anomaly of this area is not obvious. By monitoring high peats in different geographic areas,the character of anthropologic geochemical anomaly in atmosphere could be ascertained.

Marine environmental quality, pollution monitoring and environmental management

Chinese government has adopted a series of management measures to prevent and manage marine pollution and to protect ocean bio resources and ecosystem. The key points of Chinese marine environmental quality status, pollution monitoring and environmental management since 1980' were discussed in this paper. Those included the investigations of Chinese coast environmental quality, monitoring techniques and standards, as well as the marine environmental management measures. Recent status of marine environmental pollution and the monitoring network in China were also introduced.

Self-Driving Algorithm and Location Estimation Method forSmall Environmental Monitoring Robot in Underground Mines

In underground mine environments where various hazards exist,such as tunnel collapse,toxic gases,the application of autonomous robots can improve the stability of exploration and efficiently perform repetitive exploratory operations.In this study,we developed a small autonomous driving robot for unmanned environmental monitoring in underground mines.The developed autonomous driving robot controls the steering according to the distance to the tunnel wall measured using the light detection and ranging sensor mounted on the robot to estimate its location by simultaneously considering the measured values of the inertial measurement unit and encoder sensors.In addition,the robot autonomously drives through the underground mine and performs environmental monitoring using the temperature/humidity,gas,and particle sensors mounted on the robot.As a result of testing the performance of the developed robot at an amethyst mine in Korea,the robot was found to be able to autonomously drive through tunnel sections with∼28 m length,∼2.5 m height,and∼3 m width successfully.The average error of location estimation was approximately 0.16 m.Using environmental monitoring sensors,temperature of 15–17◦C,humidity of 42%–43%,oxygen concentration of 15.6%–15.7%,and particle concentration of 0.008–0.38 mg/m3 were measured in the experimental area,and no harmful gases were detected.In addition,an environmental monitoring map could be created using the measured values of the robot’s location coordinates and environmental factors recorded during autonomous driving.