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Journal articles on the topic 'Water Environment Monitoring'

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Author: Grafiati

Published: 14 March 2023

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1

Aswin Kumer, S. V., P. Kanakaraja, V. Mounika, D. Abhishek, and B. Praneeth Reddy. "Environment water quality monitoring system." Materials Today: Proceedings 46 (2021): 4137–41. http://dx.doi.org/10.1016/j.matpr.2021.02.674.

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2

Lychak, O. V. "Speckle correlation method for monitoring of localized corrosion degree in water environment." Information extraction and processing 2019, no. 47 (December 26, 2019): 59–72. http://dx.doi.org/10.15407/vidbir2019.47.059.

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3

Mashevska, Marta, Roman Shchur, and Aleksander Ostenda. "GLOBAL ENVIRONMENTAL MONITORING SYSTEM." Measuring Equipment and Metrology 82, no. 4 (2021): 26–31. http://dx.doi.org/10.23939/istcmtm2021.04.026.

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This article reveals the problems of creating a monitoring system to assess the ecological state of the environment of the selected area. An information model of the system has been developed, which takes into account the parameters of air, surface water, and soil pollution. The main components of the system, including the logical model of the database, have been designed and implemented. To assess the state of the environment according to the selected pollution parameters, the fuzzy logic model is constructed.

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4

He, Ping, Xueya Chen, Yuanxing Cai, Yue Zhou, and Yan Chen. "Research Progress of Remote Sensing Technology in Lake Water Environment Monitoring in China." International Journal of Engineering and Technology 14, no. 2 (May 2022): 15–18. http://dx.doi.org/10.7763/ijet.2022.v14.1195.

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This paper analyzes the research progress of remote sensing technology in lake water environment monitoring in China in recent years, including the research progress of suspended matter concentration in water, the research progress of bloom characteristics and the research status of chlorophyll concentration A.Although great progress has been made in lake water environment monitoring, the use of remote sensing to capture the spectral characteristics of water remains to be strengthened. It is necessary to improve the lake remote sensing algorithm for long time series and large range.

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5

Li, Chun Long, Xian Xiang Chen, Zhen Fang, Jian Hua Tong, Hong Zhang, and Shan Hong Xia. "A Software Platform for Water Environment Monitoring." Advanced Materials Research 898 (February 2014): 743–46. http://dx.doi.org/10.4028/www.scientific.net/amr.898.743.

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This paper describes a software platform for water environment monitoring. The main monitored parameters are temperature, turbidity, PH, dissolved oxygen, chemical oxygen demand (COD), total phosphorus, total nitrogen, nitrogen ammonia (NH) and heavy metal such as Pb, Zn and Cu etc. This platform was designed using java language and java web technology, which are widely used in many software platforms including water environment monitoring. Low cost and lightweight framework are the major aspects of the software platform because free software (Tomcat and MySQL) and SSH framework are adopted in this software platform. People can view water quality data in a computer or a smart phone browser in the form of table and chart. The water quality data transmitted from General Packet Radio Service (GPRS) wireless network are stored into the MySQL database automatically once the software platform is started. Data collected by this platform is real-time, once a record is out of limits, a message will be sent to mobile phone. Through data collected, environment protection administrators can predict and get the conclusion whether the water is polluted or not.

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6

Hodgson, Kelly, and Andrew S. Fraser. "The Global Environment Monitoring System Water Web Site." Water International 24, no. 2 (June 1999): 164–67. http://dx.doi.org/10.1080/02508069908692154.

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7

Zhu, Shan Hong, and Pei Tang. "A Design and Implementation of Water Surveillance System Based on Wireless Sensor Networks." Applied Mechanics and Materials 602-605 (August 2014): 2305–7. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2305.

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A water environmental monitoring system based on a wireless sensor network is proposed. It consists of three parts: data monitoring nodes, data base station and remote monitoring center. This system is suitable for the complex and large-scale water environment monitoring, such as for reservoirs, lakes, rivers, swamps, and shallow or deep ground waters. This paper is devoted to the explanation and illustration for our new water environment monitoring system design. The system had successfully accomplished the online auto-monitoring of the water temperature and pH value environment of an artificial lake. The monitoring system thus promises broad applicability prospects. The system's measurement capacity ranges from 0 to 90 °C for water temperature, with an accuracy of ±0.5 °C; from 0 to 16 on pH value, with an accuracy of ±0.05 pH units. Sensors applicable to different water quality scenarios should be installed at the nodes to meet the monitoring demands for a variety of water environments and to obtain different parameters.

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8

HARA, Toshiaki, Kouji NISIJIMA, and Masanori KATO. "Water Environment Monitoring at Lake Biwa and Fluctuations in Water Level." ENVIRONMENTAL SYSTEMS RESEARCH 23 (1995): 632–37. http://dx.doi.org/10.2208/proer1988.23.632.

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9

Alekseev, V. A., V. P. Usoltcev, S. I. Yuran, and D. N. Shulmin. "COMPLEX FOR MONITORING OF SEWAGE OPTICAL DENSITY CHANGES." Devices and Methods of Measurements 9, no. 1 (March 20, 2018): 7–16. http://dx.doi.org/10.21122/2220-9506-2018-9-1-7-16.

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Article contains theoretical and practical technical sentences on creation of an optoelectronic complex of monitoring of emergency discharge of pollution in sewage of the enterprises.The relevance of the task of monitoring of sewage on existence of emergency clots in sewage for saving water sources is shown. The structural scheme of a complex of monitoring of the water environment is provided. The mathematical model of a complex of optoelectronic monitoring over the water environment on the example of sewage of the enterprise is considered. The complex of monitoring is described by the random impulse transition function containing two independent components, one of which defines dynamic properties, another considers stochasticity of conversion.The example of implementation of an optoelectronic complex of monitoring of the water environment in the system of sewage of the enterprise is given. Experimentally the efficiency of a complex in case of measurement of changes of optical density of the analysable environments is shown. For carrying out an experiment water pollution is selected by vegetable oil. The analysis of absorption spectra of water and vegetable oil showed that as a source of radiation it is expedient to use lasers with lengths of waves in the range of 0,4–0,5 μm which have the minimum absorption of radiation in the water environment and the considerable absorption in the environment of impurity, for example, the violet STLL-MM-405-200-52-A laser with wavelength of 0,405 μm and 200 mW. As the photo-sensor element, it is possible to use, for example, the PDV-V400-46 photodiode.Results of an experiment of a research of optical density of the liquid environment containing clots from vegetable oil are given. They show the functional connection of pollution of sewage with change of optical density of the water environment with certain lengths of waves of a probing laser radiation.

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10

SAVKOVA, E. O., O. V. CHENGAR, and V. I. SHEVCHENKO. "THE MONITORING SYSTEM OF THE WATER ENVIRONMENT HYDROPHYSICAL FIELDS." Fundamental and Applied Problems of Engineering and Technology 5 (2020): 153–64. http://dx.doi.org/10.33979/2073-7408-2020-343-5-153-164.

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The article considers the functions performed by the system for monitoring the fine structure of the water environment hydrophysical fields, starting from initialization the system parameters to visualization the received information. As a result of a detailed analysis the selected functions, which consists in determining the input information flows, their representation and transformation, a functional diagram of the measuring system for monitoring the fine structure of the water environment hydrophysical fields was developed, which allows reducing the cost of conducting sounding and ensuring the necessary measurement accuracy, thanks to the chosen sensing strategy and the use of a database of simulated parameters of turbulated layers .

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11

Chensky, D. A., B. B. Aisuev, A. G. Chensky, A. P. Fedotov, and A. S. Poletaev. "Water environment monitoring with an autonomous unmanned surface vessel." Journal of Physics: Conference Series 1728 (January 2021): 012002. http://dx.doi.org/10.1088/1742-6596/1728/1/012002.

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12

赵, 鹏泽. "Design and Implementation of Intelligent Water Environment Monitoring Platform." Software Engineering and Applications 09, no. 01 (2020): 72–81. http://dx.doi.org/10.12677/sea.2020.91009.

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13

杜, 茹男. "Analysis on Quality Assurance of Water Environment Monitoring System." Advances in Environmental Protection 07, no. 02 (2017): 122–26. http://dx.doi.org/10.12677/aep.2017.72018.

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14

Liu, Rei, Tao Xie, Qiao Wang, and Honghua Li. "Space-earth based Integrated Monitoring System for Water Environment." Procedia Environmental Sciences 2 (2010): 1307–14. http://dx.doi.org/10.1016/j.proenv.2010.10.141.

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15

Merry, Jill. "Reference materials for monitoring nutrients in sea water environment." Fresenius' Journal of Analytical Chemistry 352, no. 1-2 (1995): 148–51. http://dx.doi.org/10.1007/bf00322315.

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16

Ma, Huanchun, Ying Xiong, Xin Hou, and Qiaosheng Shu. "Application of Big Data in Water Ecological Environment Monitoring." IOP Conference Series: Materials Science and Engineering 750 (March 24, 2020): 012044. http://dx.doi.org/10.1088/1757-899x/750/1/012044.

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17

Wang, Yong, Xufan Zhang, Jun Chen, Zhuo Cheng, and Dianhong Wang. "Camera sensor-based contamination detection for water environment monitoring." Environmental Science and Pollution Research 26, no. 3 (November 27, 2018): 2722–33. http://dx.doi.org/10.1007/s11356-018-3645-z.

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18

T, Anuradha, Shweta Jadhav, and Sridevi Mahamani. "Smart Water Dispenser and Monitoring Water Level in IoT and Android Environment." International Journal of Computer Sciences and Engineering 7, no. 5 (May 31, 2019): 810–14. http://dx.doi.org/10.26438/ijcse/v7i5.810814.

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19

Ana-Maria, Budu, and Sandu Ion. "Monitoring Of Pollutants In Museum Environment." Present Environment and Sustainable Development 9, no. 2 (October 1, 2015): 173–80. http://dx.doi.org/10.1515/pesd-2015-0034.

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Abstract Art works are affected by environmental factors as light, temperature, humidity. Air pollutants are also implicated in their degradation. The pollution in museums has two sources: the air from outside, which brings usually dust and inorganic particles, and the inside sources – the materials used for casings (sealants, textiles placed on the display cases, varnishes, wood) that emanate organic compounds. The dust is composed of particles with a diameter of approximately 2µm or higher, which come from soil (silica) or animal and vegetal residues (skin cells, pollen). They facilitate water condensation on objects surface and biologic attack. The inorganic compounds are a result of materials combustion (SO2, NO2, NO) and in presence of water they form acidic compounds which affect the museum objects. The organic compounds are usually peroxides, acids, phthalates, formaldehyde. The effects of these pollutants are: soiling, surface discolouration, embrittlement, corrosion. Therefore, conservators are interested in monitoring the pollution degree in the display cases or in the museum air and in analyzing the effects of pollutants on the exhibited objects. They use different methods for pollutants identification, like direct reading devices based on colorimetry, that can be read after few minutes and hours (they interact with the pollutants in atmosphere), or indirect reading samples that require a laboratory. The information gathered is used for the identification of pollution source and to analyze the concentration of pollutants needed to provoke damages on the surfaces of art objects. This paper is a review of pollutants that affect the art objects and of the monitoring systems used for their identification and measuring.

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20

Tolba, Mostafa K. "Water and the Environment." Water International 10, no. 2 (January 1985): 49–50. http://dx.doi.org/10.1080/02508068508686304.

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21

Sunjka, Dragana, and Sanja Lazic. "Water sampling techniques for continous monitoring of pesticides in water." Pesticidi i fitomedicina 32, no. 2 (2017): 85–93. http://dx.doi.org/10.2298/pif1702085s.

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Good ecological and chemical status of water represents the most important aim of the Water Framework Directive 2000/60/EC, which implies respect of water quality standards at the level of entire river basin (2008/105/EC and 2013/39/EC). This especially refers to the control of pesticide residues in surface waters. In order to achieve the set goals, a continuous monitoring program that should provide a comprehensive and interrelated overview of water status should be implemented. However, it demands the use of appropriate analysis techniques. Until now, the procedure for sampling and quantification of residual pesticide quantities in aquatic environment was based on the use of traditional sampling techniques that imply periodical collecting of individual samples. However, this type of sampling provides only a snapshot of the situation in regard to the presence of pollutants in water. As an alternative, the technique of passive sampling of pollutants in water, including pesticides has been introduced. Different samplers are available for pesticide sampling in surface water, depending on compounds. The technique itself is based on keeping a device in water over a longer period of time which varies from several days to several weeks, depending on the kind of compound. In this manner, the average concentrations of pollutants dissolved in water during a time period (time-weighted average concentrations, TWA) are obtained, which enables monitoring of trends in areal and seasonal variations. The use of these techniques also leads to an increase in sensitivity of analytical methods, considering that pre-concentration of analytes takes place within the sorption medium. However, the use of these techniques for determination of pesticide concentrations in real water environments requires calibration studies for the estimation of sampling rates (Rs). Rs is a volume of water per time, calculated as the product of overall mass transfer coefficient and area of the receiving phase exposed to the external environment, and it is substance specific.

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22

Li, Hui, and Yan Zheng. "Herbal Materials Warehouse Environment Monitoring System." Applied Mechanics and Materials 329 (June 2013): 8–12. http://dx.doi.org/10.4028/www.scientific.net/amm.329.8.

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In recent years, the efficacy of Chinese herbal medicines decreases often because of bad storage. It carries huge economic losses, furthermore, it endangers the safety of people's lives. Therefore, it is an urgent need for a new monitoring concepts and monitoring system for medicine warehouse to overcome many shortcomings. Combining the wireless sensor network technology, we researched environment parameter detection system of Chinese herbal medicine storage with a reasonable structure. It can monitor the air temperature, humidity, light, and water content parameters of herbs storage environment. We designed the hardware, software and interactive interface of the monitoring system. The proposed system has a better real-time and more accurate compared with the traditional manual monitoring system.

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23

Xiao, Xiao, and Zi Kang Zhou. "The Application of RS in Protecting Environment." Advanced Materials Research 573-574 (October 2012): 400–403. http://dx.doi.org/10.4028/www.scientific.net/amr.573-574.400.

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The environment problem is becoming increasingly significant in the world. Besides, the technology of RS has been widely used in the field of regional environment monitoring and the global study of environmental problems. This paper mainly introduce the RS’s application in air pollution monitoring, water environment monitoring, ecological environmental monitoring, and the natural disasters monitoring and so on.

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24

Setiawan, Foni Agus, and Yuli Sudriani. "System Engineering for Online Monitoring and Early Warning of Water Environment." Jurnal INKOM 9, no. 2 (May 30, 2016): 49. http://dx.doi.org/10.14203/j.inkom.422.

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Measurement activity usually performed at a time or in a certain time period. In the case of measurements at one time, measurements manually by visiting the location of measurements, take measurements and write them down, then left the location is not a problem. However, measurements made within a certain period of time or year would be verydraining, costly, and time consuming if perfomed manually. Thus, design and implementation of embedded system for online monitoring and early warning of water environment is proposed. The system consists of two parts i.e. monitoring stations (site) and monitoring center (server). A monitoring station is an embedded system that has interface with a logger. Monitoring center is a computer that runs the service that gets the data sent by the monitoring stations, process it and put it into the database. Monitoring center also runan http service to display data acquired from monitoring stations to end users both in tabular or graphical view . The system can perform continuous measurements and its results can be monitored remotely.

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25

Wei, Qing Jian, Jin Ning, Xi Zhong Lou, Ren Zhi Ma, and Jia Xu. "Software Design for Water Environment Remote Monitoring System Based on Mobile Devices." Applied Mechanics and Materials 58-60 (June 2011): 2027–32. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.2027.

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A mobile remote data monitoring center based on Android operating system is developed for the water environment monitoring system via wireless sensor network (WSN). The monitoring center collects the sensors data from the WSN based on C/S mode. The SQLite is adopted in database module to achieve high memory speed and efficient operation management. Dynamic graphical displays are accomplished to show the topology of the WSN, the state of the nodes and the real-time and historical water environment parameters of the sensor nodes. The experiments show that the software of water environment remote monitoring system, based on mobile devices of Android operating system, can conveniently satisfy the requirements of data collecting and monitoring for water environment monitoring system based on WSN.

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Watanabe, M., M. Sekine, E. Hamada, M. Ukita, and T. Imai. "Monitoring of shallow sea environment by using snapping shrimps." Water Science and Technology 46, no. 11-12 (December 1, 2002): 419–24. http://dx.doi.org/10.2166/wst.2002.0772.

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We examine the validity of pulse count of snapping shrimps for sea environmental monitoring. Snapping shrimps, which make a peculiar pulse sound, are found everywhere in the world. Pulse count can be achieved merely by recording their sounds for a few minutes by using a hydrophone without special biological knowledge. From field surveys and laboratory experiments, we found that the pulse count depends on water temperature when sea environment is normal, and it falls due to the occurrence of oxygen-deficient water. The results show that this method can be a useful index of the effect of water pollution on benthic animals in fixed-point observation.

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Gong, Yi Cheng, Yong Xiang Zhang, Fei Ding, Wei Chun Gao, and Yi Fan Wang. "Water Environment Monitoring System Based on Data Extraction - Transmission and Processing." Advanced Materials Research 779-780 (September 2013): 1592–95. http://dx.doi.org/10.4028/www.scientific.net/amr.779-780.1592.

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The current paper describes a water environment monitoring system, which is focused on the online monitoring techniques of groundwater detection, data process and transmission, a local experiment equipment is also developed. Besides, an integrated study, in terms of host computer of the groundwater monitoring system, programmable logic controller (PLC) control system and sensor technology is carried out. Moreover, the secondary data process of automatic detection instrumentation and display technology is integrated, as well as the visualized data platform is primarily established. The water environment monitoring system improves the standard of monitoring indicators from the surface water environment to groundwater environment. The detection interval of the system is less than 3min, and the pollution forecast scope surpasses 16 km2. A high accuracy of the forecasting and risk analysis can be obtained.

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28

Larmie, S. A., Rose A. Osafo, and Nii Boi Ayibotele. "Surface Water Quality Monitoring and Pollution Control in Ghana." Water Science and Technology 24, no. 1 (July 1, 1991): 35–41. http://dx.doi.org/10.2166/wst.1991.0007.

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Developing nations like Ghana, cannot afford to adopt a “wait to see” policy with their water environment. We must develop and/or strengthen infrastructure needed to maintain a healthy environment. In our eagerness to industrialize, care must be taken not to repeat mistakes of industrialized nations. Water quality monitoring activities should be streamlined and properly coordinated to develop good pollution control measures. We must research into and provide pollution control alternatives suitable for our particular environment.

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29

Naik, M. Renubabu. "Greenhouse Environment Monitoring and Controlling Through IoT." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 2412–17. http://dx.doi.org/10.22214/ijraset.2022.44318.

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Abstract: Our project is based on IOT (Internet of things) which is very useful for monitoring and controlling the greenhouse environment, Agriculture under the greenhouse environment has more benefit of getting more crops by making proper climatic conditions for plants, fruits and vegetables. This greenhouse monitoring environment system have the transparent paper on the top and it contains the five main sensors they are temperature, humidity, rain, soil, LDR sensors. Most of the farmers are fail to get good crops by various reasons such as diseases due to temperature and humidity, if farmers really concerned about suitable temperature and humidity then they can get good crops and this can possible by providing greenhouse environment. The Arduino Nano is the heart of this project, and the five sensors are senses of their respective value and send to the Arduino Nano, through Wi-Fi module the respective detected value is monitored on the smart mobile where Wi-Fi controller app is there. Temperature sensor detects temperature, if temperature exceeds the threshold value then the fan is automatically on, there by temperature are decreases in the greenhouse environment. If LDR detects the sunlight then light will be off and when the sunlight not fall on the LDR then the light will be on in the greenhouse environment. If Rain sensor detects Rain then through the Wi-Fi controller we can open the top of the Greenhouse environment. The top is to be closed after the rain stop, by the Wi-Fi controller. If Soil sensor detects soil is to be dry then automatically the water pump is ON, and water pump is OFF automatically when soil becomes wet.

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Saxena, Gaurav, Ram Naresh Bharagava, Gaurav Kaithwas, and Abhay Raj. "Microbial indicators, pathogens and methods for their monitoring in water environment." Journal of Water and Health 13, no. 2 (October 13, 2014): 319–39. http://dx.doi.org/10.2166/wh.2014.275.

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Water is critical for life, but many people do not have access to clean and safe drinking water and die because of waterborne diseases. The analysis of drinking water for the presence of indicator microorganisms is key to determining microbiological quality and public health safety. However, drinking water-related illness outbreaks are still occurring worldwide. Moreover, different indicator microorganisms are being used in different countries as a tool for the microbiological examination of drinking water. Therefore, it becomes very important to understand the potentials and limitations of indicator microorganisms before implementing the guidelines and regulations designed by various regulatory agencies. This review provides updated information on traditional and alternative indicator microorganisms with merits and demerits in view of their role in managing the waterborne health risks as well as conventional and molecular methods proposed for monitoring of indicator and pathogenic microorganisms in the water environment. Further, the World Health Organization (WHO) water safety plan is emphasized in order to develop the better approaches designed to meet the requirements of safe drinking water supply for all mankind, which is one of the major challenges of the 21st century.

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31

. Golushkov, Nikolay Aleksandrovich, and Andrey Gennadievich Kokuev. "Integrated platform for monitoring fish farm aquatic environment." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2023, no. 1 (January 31, 2023): 57–63. http://dx.doi.org/10.24143/2073-5529-2023-1-57-63.

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The article highlights the problem of integrated monitoring of the aquatic environment, which is technical part of monitoring the aquatic environment. It includes the information management module, a module for analyzing and evaluating the aquatic environment, a module for early warning and forecasting the state of the aquatic environment, a module for integrated monitoring of the aquatic environment, a geographic information system (GIS) and a module of data monitoring. The above problem includes preventing the spread of pollution in areas and elements with potential safety hazards by periodically collecting information about each sub-area (information about pollution sources around each monitoring point). The quality of water at monitoring points is assessed, the trend of water quality deterioration is analyzed, a forecasting model is built that allows preventing dangerous processes in advance, identifying the area of pollution of the aquatic environment and the level of pollution, as well as accurately assessing the scale of the accident, timely processing the incoming information and taking the effective measures against the emergency consequences. Due to using the proposed platform integrated monitoring of the aquatic environment is improved.

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32

Yermolenko, Volodymyr, Olena Hafurova, Maryna Deineha, Tamara Novak, Alena Temnikova, and Erdene Naidansuren. "Quality of drinking water in rural areas: problems of legal environment." E3S Web of Conferences 280 (2021): 09022. http://dx.doi.org/10.1051/e3sconf/202128009022.

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The article is devoted to the scientific and theoretical analysis of the current state of legal provision of drinking water quality in rural areas. It was stated that in recent years there has been a steady trend of deteriorating quality of water used for drinking in rural areas, including due to increasing levels of nitrate pollution. Proposals have been made for: further implementation of Council Directive 98/83 / EU on the quality of water intended for human consumption and Council Directive 91/676/ EEC on the protection of waters against pollution caused by nitrates from agricultural sources in national legislation; elimination of substantive inconsistencies between State sanitary norms and rules 2.2.4-171-10 “Hygienic requirements for drinking water intended for human consumption” and National Standards of Ukraine 7525: 2014 “Drinking water. Requirements and methods of quality control “in terms of drinking water quality indicators; inclusion in the subjects of state water monitoring of the central executive body that implements the state policy in the field of health care (regarding the monitoring of drinking water); development of the Procedure for state monitoring of nitrate content in surface and groundwater as a component of state water monitoring; forecasting at the level of the National Target Program “Drinking Water of Ukraine” for 2021-2025 “development and operation of a single state information resource - Interactive map of drinking water quality in Ukraine.

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33

Wang, Xiao, Dong Zhang, and Huan Liu. "Water environment protection and monitoring management during bridge construction in water source conservation areas." IOP Conference Series: Earth and Environmental Science 371 (December 13, 2019): 022035. http://dx.doi.org/10.1088/1755-1315/371/2/022035.

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34

S, Anasica. "Research on Smart Environment Monitoring Systems based on Secure Internet of Things (IoT)." International Journal on Future Revolution in Computer Science & Communication Engineering 8, no. 1 (March 31, 2022): 48–55. http://dx.doi.org/10.17762/ijfrcsce.v8i1.2090.

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Significant environmental threats include poor air quality, water contamination, and radiation pollution. A healthy society must be maintained for the planet to experience sustained growth. Environmental monitoring has transformed into smart environment monitoring (SEM) systems in recent years due to the growth of an internet of things (IoT). The Internet of Things (IoT) concept has developed into technology for creating smart environments and also has its disadvantage. To collect, evaluate, and recommend specific actions in smart environments for various purposes, a secure IoT-based platform is proposed. The proposed method follows the flow outlined here: data collection, normalization technique is used for data preprocessing, Linear Discriminant Analysis (LDA) is used for feature extraction, then data stored in IoT, Advanced Twofish encryption algorithm is proposed for securing the data, then user decryption, and finally performance is analyzed for smart environment monitoring using secure IoT. The proposed work aims to complete a critical evaluation of significant contributions to SEM that focus on the monitoring of water quality, air quality, radiation contamination, and agricultural systems. Secure IoT is based on the optimal integration and use of data gathered from several sources. This algorithm provides smart environment monitoring and also exhibits optimal integration.

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Anderson, S. A., S. J. Turner, and G. D. Lewis. "Enterococci in the New Zealand environment: implications for water quality monitoring." Water Science and Technology 35, no. 11-12 (June 1, 1997): 325–31. http://dx.doi.org/10.2166/wst.1997.0754.

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Faecal enterococci ecology outside the host is of great relevance when using these organisms as indicators of water quality. As a complement to New Zealand epidemiological studies of bathing water quality and health risk, a study of the environmental occurrence of these organisms has been undertaken. Specific concerns over the use of enterococci derive from the unique situation in New Zealand which has few chlorinated sewage effluents, a high ratio of grazing animals to humans, and significant inputs of animal processing effluents into the environment. Human and animal faecal wastes are the main sources, with 106–107cfu/100ml found in human sewage. Analysis of domestic and feral animal faeces found enterococci in the range of 101–106cfu/g with considerable variation between species. The latter observations support the notion that a considerable proportion of the load in urban/rural catchments and waterways (typically 102–103 enterococci cfu/100ml) is derived from non-human sources. Previous studies of enterococci quiescence in marine/fresh waters indicate that they enter a non-growth phase, exposure to sunlight markedly reducing culturability on selective and non-selective media. Enterococci were also found to survive/multiply within specific non-faecal environments. Enterococci on degrading drift seaweed at recreational beaches exceeded seawater levels by 2–4 orders of magnitude, suggesting that expansion had occurred in this permissive environment with resultant potential to contaminate adjacent sand and water. These studies suggest that multiple sources, environmental persistence, and environmental expansion of enterococci within selected niches add considerable complexity to the interpretation of water quality data.

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Lei, Feng, You Yu, Daijun Zhang, Li Feng, Jinsong Guo, Yong Zhang, and Fang Fang. "Water remote sensing eutrophication inversion algorithm based on multilayer convolutional neural network." Journal of Intelligent & Fuzzy Systems 39, no. 4 (October 21, 2020): 5319–27. http://dx.doi.org/10.3233/jifs-189017.

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In recent years, with the rapid development of satellite technology, remote sensing inversion has been used as an important part of environmental monitoring. Remote sensing inversion has been prepared for large-scale water environment monitoring in the watershed that is difficult for the traditional water environment monitoring methods. This paper will discuss some shortcomings of traditional remote sensing inversion methods, and proposes a remote sensing inversion method based on convolutional neural network, which realizes large-scale remote sensing smart and automatic inversion monitoring of the water environment. The results show that the method is practical and effective, and can achieve high recognition accuracy for water blooms.

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Chen, Wei, Xiao Hao, JianRong Lu, Kui Yan, Jin Liu, ChenYu He, and Xin Xu. "Research and Design of Distributed IoT Water Environment Monitoring System Based on LoRa." Wireless Communications and Mobile Computing 2021 (October 13, 2021): 1–13. http://dx.doi.org/10.1155/2021/9403963.

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In order to solve the problems of high labor cost, long detection period, and low degree of information in current water environment monitoring, this paper proposes a lake water environment monitoring system based on LoRa and Internet of Things technology. The system realizes remote collection, data storage, dynamic monitoring, and pollution alarm for the distributed deployment of multisensor node information (water temperature, pH, turbidity, conductivity, and other water quality parameters). Moreover, the system uses STM32L151C8T6 microprocessor and multiple types of water quality sensors to collect water quality parameters in real time, and the data is packaged and sent to the LoRa gateway remotely by LoRa technology. Then, the gateway completes the bridging of LoRa link to IP link and forwards the water quality information to the Alibaba Cloud server. Finally, end users can realize the water quality control of monitored water area by monitoring management platform. The experimental results show that the system has a good performance in terms of real-time data acquisition accuracy, data transmission reliability, and pollution alarm success rate. The average relative errors of water temperature, pH, turbidity, and conductivity are 0.31%, 0.28%, 3.96%, and 0.71%, respectively. In addition, the signal reception strength of the system within 2 km is better than -81 dBm, and the average packet loss rate is only 94%. In short, the system’s high accuracy, high reliability, and long distance characteristics meet the needs of large area water quality monitoring.

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Dilli Kumar V, Eshwar M, Manova Sam M, and Lavanya R. "Blynk based aquaculture monitoring system using IOT." World Journal of Advanced Engineering Technology and Sciences 8, no. 1 (February 28, 2023): 262–69. http://dx.doi.org/10.30574/wjaets.2023.8.1.0039.

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Internet of Things (IOT) is one of the development trends technologies reduces the amount of human labor and creates an economy ethnic. Currently, IoT is applied in many fields such as medicine, agriculture, traffic system, training, monitoring, etc. It is the most important because aquaculture is an outdated field of applied science. As similar to In other areas such as agriculture, it is essential to identify problems that arise this field with the help of technology. The term Aquaculture mainly refers to Aquaculture such as fish and plants takes place in many forms aquatic environments, including lakes, rivers, ponds, oceans, and artificially closed areas terrestrial environmental systems. Aqua culture plays an important role in economic development and food production in our country. adopt fish can quickly and easily using monitoring systems. Water quality can be a fundamental problem and it depends on various parameters like pH, turbidity, Temperature, dissolved oxygen, Ammonia etc. Suggestion system continuous monitoring of water quality parameters by various sensors. The detected information is transmitted to the mobile phone of the aquarist via the web cloud waiter. It will also notify the aquarist about the data through the app. This system will activate automated farming system to make appropriate adjustments to the environment of the self-contained artificial pond. So the water quality parameters keeping a balance, culture is the root of health and development of living organisms. This system will monitor the water quality parameters and regularly access water quality parameters.

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Lee, In-Seok, Minkyu Choi, and Jeong-Eun Oh. "Monitoring of PCBs in Marine Environment Using Passive Water Sampling Device." Journal of Environmental Analysis, Health and Toxicology 23, no. 4 (December 31, 2020): 194–203. http://dx.doi.org/10.36278/jeaht.23.4.194.

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Xiao, Qi. "Research on Monitoring and Protection of Water Environment in Rural Areas." Applied Mechanics and Materials 608-609 (October 2014): 1084–88. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.1084.

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This article first introduces the current situation of heavy metal pollution and heavy metal detection technology, and selected the voltammetry as the principle of detection system in electrochemical stripping. At the same time, introduces the related content of wireless sensor network. According to project requirements, design a set of heavy metal functional modularity, automation instrumentation, module power supply system which can meet the applicable to different working environment; for the need wireless sensor networks, proposes a design of wireless network node; finally, in the waterway system in laboratory environment test and heavy metal concentration detection test experiments show that the instrument, this system can meet the design requirements.

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41

Stupin, Vladimir. "Morphosystems mapping as the basis for monitoring water reservoirs’ geological environment." Proceedings of the Siberian Department of the Section of Earth Sciences of the Russian Academy of Natural Sciences. Geology, Exploration and Development of Mineral Deposits 42, no. 2 (June 2019): 209–20. http://dx.doi.org/10.21285/2541-9455-2019-42-2-209-220.

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Khatri, Punit, Karunesh Kumar Gupta, and Raj Kumar Gupta. "Real-time water quality monitoring for distribution networks in IoT environment." International Journal of Environment and Sustainable Development 21, no. 3 (2022): 346. http://dx.doi.org/10.1504/ijesd.2022.123939.

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Chen, Long, Yan Liu, Jing Lv, Xiangfeng Kong, and Jingru Wang. "Progress of On-line Biological Monitoring Technology in Different Water Environment." IOP Conference Series: Earth and Environmental Science 831, no. 1 (August 1, 2021): 012064. http://dx.doi.org/10.1088/1755-1315/831/1/012064.

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Khatri, Punit, Raj Kumar Gupta, and Karunesh Kumar Gupta. "Real-time water quality monitoring for distribution networks in IoT environment." International Journal of Environment and Sustainable Development 1, no. 1 (2022): 1. http://dx.doi.org/10.1504/ijesd.2022.10044904.

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Tang, Yankui, Maozhong Yin, Weiwei Yang, Huilan Li, Yaxuan Zhong, Lihong Mo, Yan Liang, Xiangmeng Ma, and Xiang Sun. "Emerging pollutants in water environment: Occurrence, monitoring, fate, and risk assessment." Water Environment Research 91, no. 10 (July 6, 2019): 984–91. http://dx.doi.org/10.1002/wer.1163.

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Zhou, Lihong. "The Monitoring and Early Warning System of Water Biological Environment Based on Machine Vision." Mathematical Problems in Engineering 2022 (June 24, 2022): 1–7. http://dx.doi.org/10.1155/2022/8280706.

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Water contaminated by microorganisms can lead to the outbreak and prevalence of various diseases, which seriously threaten the health of people. In the monitoring of the water biological environment, the traditional methods have low detection sensitivity and low efficiency, so it is urgent to design a water biological monitoring system with low cost and high monitoring efficiency. Machine vision has the advantages of fast speed, appropriate precision, and strong anti-interference ability, which has been greatly developed in recent years. In this paper, the monitoring and early warning system of the water biological environment is built, in which the SVM algorithm is applied to image processing and feature extraction, and each module of the system is designed. Finally, the computational complexity of the system algorithm and the detection accuracy of the system are tested, and the results show that the system has the advantages of low cost, low computational complexity, and high monitoring efficiency, which can provide a reference for water resources protection.

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Wang, Jing, and Qian Wu. "Unmanned Monitoring System of Three Gorges Basin for Water Environment Based on WSN." Advanced Materials Research 482-484 (February 2012): 1777–80. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.1777.

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Aimed at the puzzle of being difficult to actualize the monitoring of water quality resulted from massive land and complex terrain in three gorges basin of Changjiang River, In order to make monitoring of the water quality get more flexible, faster, easier and accurate, the paper designed a sort of monitoring system of three gorges basin in water environment based on WSN. In the paper, it researched the system architecture, analyzed the network design of system, built the wireless mesh network, designed the data acquisition monitoring module, and discussed the monitor center and software design. It took the parameter test of temperature, pH value and heavy metal irons etc in the river as an example, the data accepted by monitor center displayed that it could accurately reflect the actual field situation. The experiment result shows that the design of unmanned remote monitoring system is feasible and reasonable.

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Ma, Huanying, Ying Xiong, Xin Hou, and Qiaosheng Shu. "Application of Big Data in Monitoring and Evaluation of Water Ecological Environment." Journal of Physics: Conference Series 2023, no. 1 (September 1, 2021): 012007. http://dx.doi.org/10.1088/1742-6596/2023/1/012007.

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Abstract Under the influence of the current society into information, big data analysis has been applied in various fields, and is no exception in the monitoring and evaluation of water ecological environment. It uses its own advantages to collect relevant data. It has far-reaching application in water environment monitoring and evaluation.

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Li, Deng, Hu Fengjiao, and Chen Jingxing. "Design and Application of Automatic Monitoring System of Water Environment Using GIS." E3S Web of Conferences 233 (2021): 01061. http://dx.doi.org/10.1051/e3sconf/202123301061.

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in order to achieve more effective management and monitoring of water environment, an automatic monitoring system is designed for the water environment of Heihe River Basin in Zhangye through GIS (geographic information system). The EFDC (environmental fluid dynamics code) model is used to establish the automatic monitoring model of water environment, and the annual average data of permanganate index of Yingluoxia, Gaoya hydrological station, and Liubaqiao in Heihe River Basin from 2015 to 2019 are used to fit and verify the water quality model. The trend suggests that the simulated data of the three observation points are close to the measured data. The fitting degree reveals that the R index of fitting curve of Liubaqiao is 0.793, while that of Yingluoxia, and Gaoya hydrological station is higher than 0.8, with good fitting degree. The average relative error between the simulated value and the measured value of permanganate index (mg/L) is small, the change trend is basically consistent, and the prediction error is small. The model is successfully established and applied to the automatic monitoring and early warning system of total phosphorus index.

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Chaudhary, Gopal, Puneet Singh Lamba, and Deepali Virmani. "A Proposed Optimization Model for Water Quality Prediction in Internet of Things Environment." Journal of Intelligent Systems and Internet of Things 6, no. 2 (2022): 32–44. http://dx.doi.org/10.54216/jisiot.060203.

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The application of industrialization and urbanization strategies results in the proliferation of waste products in water resources which is a serious public challenge. They have resulted in calls for advanced technologies of water quality mitigation and monitoring, as emphasized in the sustainable development objectives. Now, environmental engineering researcher is looking for a more complex process of implementing practical assessments and of monitoring the quality of ground and surface water that is quantifiable to human beings over different locations. Many current techniques use the Internet of Things (IoT) for water quality assessment and monitoring. This paper explores the proposal of African Buffalo Optimization with Deep Belief Network for Water Quality Prediction (ABODBN-WQPR) model in an IoT environment. The presented proposed model majorly concentrates on the identification of water quality.

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