scholarly journals Research and Design of Distributed IoT Water Environment Monitoring System Based on LoRa

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wei Chen ◽  
Xiao Hao ◽  
JianRong Lu ◽  
Kui Yan ◽  
Jin Liu ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Real Time ◽  
Monitoring System ◽  
Water Environment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Environment Monitoring ◽  
Long Distance ◽  
Internet Of Things Technology

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.

scholarly journals Establishment of an Automatic Real-Time Monitoring System for Irrigation Water Quality Management

2020 ◽  
Vol 17 (3) ◽  
pp. 737 ◽  
Author(s):  
Wei-Jhan Syu ◽  
Tsun-Kuo Chang ◽  
Shu-Yuan Pan
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Quality Management ◽  
Real Time ◽  
Monitoring System ◽  
Irrigation Water ◽  
Water Quality Management ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Irrigation Water Quality

In order to provide the real-time monitoring for identifying the sources of pollution and improving the irrigation water quality management, the integration of continuous automatic sampling techniques and cloud technologies is essential. In this study, we have established an automatic real-time monitoring system for improving the irrigation water quality management, especially for heavy metals such as Cd, Pb, Cu, Ni, Zn, and Cr. As a part of this work, we have first provided several examples on the basic water quality parameters (e.g., pH and electrical conductance) to demonstrate the capacity of data correction by the smart monitoring system, and then evaluated the trend and variance of water quality parameters for different types of monitoring stations. By doing so, the threshold (to initiate early warming) of different water quality parameters could be dynamically determined by the system, and the authorities could be immediately notified for follow-up actions. We have also provided and discussed the representative results from the real-time automatic monitoring system of heavy metals from different monitoring stations. Finally, we have illustrated the implications of the developed smart monitoring system for ensuring the safety of irrigation water in the near future, including integration with automatic sampling for establishing information exchange platform, estimating fluxes of heavy metals to paddy fields, and combining with green technologies for nonpoint source pollution control.

scholarly journals Comparison of Forecasting Models for Real-Time Monitoring of Water Quality Parameters Based on Hybrid Deep Learning Neural Networks

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1547
Author(s):  
Jian Sha ◽  
Xue Li ◽  
Man Zhang ◽  
Zhong-Liang Wang
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Deep Learning ◽  
Real Time ◽  
Best Management Practices ◽  
Input Data ◽  
Management Practices ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Real Time Monitoring

Accurate real-time water quality prediction is of great significance for local environmental managers to deal with upcoming events and emergencies to develop best management practices. In this study, the performances in real-time water quality forecasting based on different deep learning (DL) models with different input data pre-processing methods were compared. There were three popular DL models concerned, including the convolutional neural network (CNN), long short-term memory neural network (LSTM), and hybrid CNN–LSTM. Two types of input data were applied, including the original one-dimensional time series and the two-dimensional grey image based on the complete ensemble empirical mode decomposition algorithm with adaptive noise (CEEMDAN) decomposition. Each type of input data was used in each DL model to forecast the real-time monitoring water quality parameters of dissolved oxygen (DO) and total nitrogen (TN). The results showed that (1) the performances of CNN–LSTM were superior to the standalone model CNN and LSTM; (2) the models used CEEMDAN-based input data performed much better than the models used the original input data, while the improvements for non-periodic parameter TN were much greater than that for periodic parameter DO; and (3) the model accuracies gradually decreased with the increase of prediction steps, while the original input data decayed faster than the CEEMDAN-based input data and the non-periodic parameter TN decayed faster than the periodic parameter DO. Overall, the input data preprocessed by the CEEMDAN method could effectively improve the forecasting performances of deep learning models, and this improvement was especially significant for non-periodic parameters of TN.

A Design of the Environment Monitoring System

2015 ◽  
Vol 730 ◽  
pp. 195-198
Author(s):  
Chun Yan Xie
Keyword(s):  
Data Collection ◽  
Environmental Monitoring ◽  
Real Time ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Environment Monitoring ◽  
Long Distance ◽  
Distance Control ◽  
Environmental Monitoring System ◽  
Gsm Network

In order to improve the deficiency of environmental monitoring system in real-time, remote monitoring and other aspects, this paper designs an environmental monitoring system based on MCU and GSM network. It designs the struture diagram of the system and analyzes the procedure of data collection and transmission. This system achieves net control and long-distance control of the environmental monitoring.

Design of Real-Time Monitoring System for Surface Water Pollution Based on GPRS

2011 ◽  
Vol 383-390 ◽  
pp. 213-217 ◽  
Author(s):  
Guang Jian Chen ◽  
Jin Ling Jia
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Surface Water ◽  
Real Time ◽  
Remote Monitoring ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Wireless Transmission ◽  
Surface Water Pollution ◽  
Monitoring Center

To implement the remote and real-time monitoring of surface water pollution, a design scheme of water quality monitoring system based on GPRS technology is put forward, which is composed of monitoring terminal, monitoring center and communication network. The various parameters of surface water are acquired using water quality detection sensor terminal and uploaded to the remote monitoring center via GPRS module by monitoring, and then the water quality parameters acquisition, processing and wireless transmission are realized. Water quality parameters are received through the internet network by the monitoring center, to realize its remote monitoring and management. According to the practice result, the system has materialized functions on GPRS service platform, such as real-time water quality parameters acquisition, procession, wireless transmission, remote monitoring and management, which is suitable for surface water pollution continuous monitoring and has the good application in the future.

scholarly journals Monitoring Water Quality of the Haihe River Based on Ground-Based Hyperspectral Remote Sensing

Water ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 22
Author(s):  
Qi Cao ◽  
Gongliang Yu ◽  
Shengjie Sun ◽  
Yong Dou ◽  
Hua Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Real Time ◽  
Training Model ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Hyperspectral Remote Sensing ◽  
Water Quality Parameters ◽  
Quality Monitoring ◽  
Haihe River

The Haihe River is a typical sluice-controlled river in the north of China. The construction and operation of sluice dams change the flow and other hydrological factors of rivers, which have adverse effects on water, making it difficult to study the characteristics of water quality change and water environment control in northern rivers. In recent years, remote sensing has been widely used in water quality monitoring. However, due to the low signal-to-noise ratio (SNR) and the limitation of instrument resolution, satellite remote sensing is still a challenge to inland water quality monitoring. Ground-based hyperspectral remote sensing has a high temporal-spatial resolution and can be simply fixed in the water edge to achieve real-time continuous detection. A combination of hyperspectral remote sensing devices and BP neural networks is used in the current research to invert water quality parameters. The measured values and remote sensing reflectance of eight water quality parameters (chlorophyll-a (Chl-a), phycocyanin (PC), total suspended sediments (TSS), total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH4-N), nitrate-nitrogen (NO3-N), and pH) were modeled and verified. The results show that the performance R2 of the training model is above 80%, and the performance R2 of the verification model is above 70%. In the training model, the highest fitting degree is TN (R2 = 1, RMSE = 0.0012 mg/L), and the lowest fitting degree is PC (R2 = 0.87, RMSE = 0.0011 mg/L). Therefore, the application of hyperspectral remote sensing technology to water quality detection in the Haihe River is a feasible method. The model built in the hyperspectral remote sensing equipment can help decision-makers to easily understand the real-time changes of water quality parameters.

scholarly journals Variation in palladium and water quality parameters and their relationship in the urban water environment

2020 ◽  
Author(s):  
Yuyan Liu ◽  
Fangfang Ding ◽  
Caiye Ji ◽  
Dan Wu ◽  
Lin Wang ◽  
...  
Keyword(s):  
Water Quality ◽  
Correlation Coefficient ◽  
Water Body ◽  
Wet Deposition ◽  
Water Environment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Urban Water ◽  
Rainfall Runoff ◽  
Receiving Water

Abstract Palladium (Pd) is widely used in vehicle exhaust catalysts (VECs) to reduce toxic emissions from motor vehicles. The study aimed to quantitatively determine Pd content and water quality parameters, to analyze the variation differences and to explore the effect of water quality parameters on Pd content in the urban water environment system (wet deposition–rainfall runoff–receiving water body–estuary) of the city of Haikou, Hainan Island, China. The method used in this study included microwave digestion under high pressure and temperature, analysis by inductively coupled plasma mass spectrometry, quality control of the experimental procedure and guaranteed recovery (85% −125%). The results showed that the dissolved Pd average content in the urban water environment system was the highest in rainfall runoff (4.93 ng/L), followed by that in the receiving water body (4.56 ng/L), and it was the lowest in wet deposition (0.1 ng/L). The suspended Pd average content was the highest in the estuary (2.83 ng/L), followed by that in rainfall runoff (1.26 ng/L), and it was the lowest in wet deposition (6 × 10−4 ng/L). The particle–water partition ratio of the estuary Pd was the highest (1.26), followed by that of Pd in rainfall runoff (0.26). The particle–water partition ratio of the wet deposition Pd was the lowest (6 × 10−3). The dissolved Pd was correlated with the pH, Cl−, and total suspended solids (TSS) (correlation coefficient = 0.52, −0.68, 0.39, p < 0.05; regression coefficient = 1.27, −1.39, 0.01). The suspended Pd was only correlated with Cl− and TSS (correlation coefficient = −0.36, 0.76, p < 0.05; regression coefficient = −1.45, 0.01). Cl− and TSS were the most closely related to Pd in the water environment system. Although individual factors such as pH, Cl−, and TSS had certain migration and transformation effects on Pd in the wet deposition–rainfall runoff–receiving water body–estuary system, the probability of strong correlations was not high. In particular, Eh was not related to the dissolved nor suspended Pd content (correlation coefficient = 0.14, 0.13), which may be due to the synergistic effect of the multiple physical factors on Pd. This study was helpful to better understand the environmental behavior of Pd and provided important theoretical support for the prevention and protection against urban water environmental pollution.

Design of Monitoring System Based on Android Platform and GPRS

2013 ◽  
Vol 433-435 ◽  
pp. 1188-1191
Author(s):  
Xing Qiao Liu ◽  
Qing Feng Chong ◽  
Xiao Song Lu
Keyword(s):  
Water Quality ◽  
Mobile Phone ◽  
Monitoring System ◽  
Measurement Accuracy ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Remote Monitoring System ◽  
Control Precision ◽  
Dissolved Oxygen Control ◽  
Android Platform

This paper presents a wireless remote monitoring system of water quality parameters based on Android platform and GPRS communication technology. This system realizes the remote collection, storage and management of water quality parameters, and also realize the remote control of the control nodes. In acquisition part, sensors collect data which is sent to the remote server through GPRS module, and water quality parameters from the server is sent to the Android mobile phone. In the control part, the control commands from the android mobile phone is sent to the server, and the server again send it to the lower machine to control the control nodes. After practical testing to the system in Liyang, Jiangsu province, temperature measurement accuracy reaches 0.5°C, PH measurement accuracy reaches 0.3, water level control precision can be controlled within ± 3cm, dissolved oxygen control precision can be controlled within ±0.3 mg/L, all the indexes can meet the requirements.

scholarly journals Hubungan Kemelimpahan Chlorella sp Dengan Kualitas Lingkungan Perairan Pada Skala Semi Masal di BBBPBAP Jepara

2016 ◽  
Vol 14 (2) ◽  
pp. 77 ◽  
Author(s):  
Siska Aprilliyanti ◽  
Tri Retnaningsih Soeprobowati ◽  
Bambang Yulianto
Keyword(s):  
Water Quality ◽  
Environmental Quality ◽  
Water Environment ◽  
Quality Parameters ◽  
Mass Scale ◽  
Regression Equation ◽  
Water Quality Parameters ◽  
Coefficient Of Determination ◽  
Culture Vessel ◽  
Chlorella Sp

ABSTRAKChlorella   sp merupakan salah satu mikroalga yang sering dibudidayakan untuk berbagai keperluan seperti obat-obatan, kosmetik, atau untuk alternatif  biodiesel Chlorella    sp  merupakan suatu agen bioremediasi yang baik, selain dapat hidup pada lingkungan yang tercemar juga dapat memakai logam berat sebagai logam esensial untuk metabolisme. Banyaknya manfaat yang akan dapat diambil apabila dapat mengembangkan Chlorella    sp pada skala masal. Dengan kemanfaatannya dari Chlorella    sp maka penulis melakukan penelitian dengan menggunakan Chlorella    sp sebagai objeknya. Tujuan dari penelitian ini adalah untuk mengetahui hubungan antara kemelimpahan Chlorella    sp dengan kualitas lingkungan perairan di Kabupaten Jepara. Chlorella      sp ini dikultivasi di luar ruangan dengan sumber cahaya berasal dari sinar matahari secara langsung, pengudaraan untuk pencampuran media menggunakan blower yang dialirkan melalui selang dan kran aerasi untuk mencampur media. Aerasi dalam penelitian ini digunakan dengan tujuan agar sel Chlorella   sp dapat memperoleh nutrisi dalam media kultivasi secara merata karena adanya sirkulasi air dalam wadah kultur (Amini, 2006). Dari hasil analisis data diperoleh nilai koefisien determinasi (R2) = 0,995. Hal ini memberikan gambaran bahwa terdapat hubungan yang sangat kuat antara variabel bebas yakni kelima parameter kualitas air (nitrat, fosfat, temperature, pH dan salinitas) dengan variabel terikat yakni kemelimpahan Chlorella   sp . Selanjutnya diperoleh persamaan regresi linier berganda sebagai berikut:Y =  -5323.54 -16.80 nitrat -60.78 fosfat   + 111.09 temperatur  + ; 997.26 pH -191.92 salinitas. Dari persamaan regresi tersebut memperlihatkan bahwa parameter kualitas air yang memiliki hubungan searah (berbanding lurus) adalah temperature  dan pH. Sedangkan parameter kualitas air yang memiliki hubungan berbanding terbalik yaitu; nitrat,fosfat dan salinitas. Hubungan kemelimpahan Chlorella   sp dengan kualitas lingkungan perairan skala semi masal kuat, hasil analisis regresi didapat nilai Adjusted R2 0,995, artinya persentase sumbangan pengaruh variabel nitrat ,fosfat,temperature, pH dan salinitas terhadap kemelimpahan Chlorella   adalah sebesar 99,5% dan sisanya dipengaruhi oleh faktor lain. Nilai koefisien / pengaruh tertinggi terdapat pada parameter pH yaitu (997,49).Kata kunci: Chlorella  sp, kualitas lingkungan, semi masal, Jepara ABSTRACTChlorella sp is one of the microalgae are often cultivated for various purposes such as pharmaceuticals, cosmetics, or for alternative biodiesel Chlorella sp an agent of bioremediation good, but can live in a polluted environment can also wear a heavy metal as the metal essential for metabolism. The many benefits that will be taken if it can develop Chlorella sp on a mass scale. With the emergence of Chlorella sp author conducted research using Chlorella sp as its object. The purpose of this study was to determine the relationship between the abundance of Chlorella sp with the quality of the water environment in the district of Jepara.Chlorella sp is cultivated outdoors with a light source coming from direct sunlight, aeration for mixing media using a blower that flowed through the hose and faucet aeration to mix media. Aeration used in this study with the aim of Chlorella sp cells can obtain nutrients evenly in cultivation media for their water circulation in the culture vessel (Amini, 2006). From the analysis of data obtained by the coefficient of determination (R2) = 0.995. This illustrates that there is a very strong relationship between the independent variables namely the five parameters of water quality (nitrates, phosphates, temperature, pH and salinity) with the dependent variable abundance of Chlorella sp. Furthermore, multiple linear regression equation as follows: Y = -5323.54 -16.80 -60.78 nitrate phosphate + 111.09 + temperature; 997.26 -191.92 pH salinity. From the regression equation shows that the water quality parameters that have a unidirectional relationship (proportional) is temperature and pH. While water quality parameters which have an inverse relationship, namely; nitrate, phosphate and salinity. Chlorella sp abundance relationships with water environmental quality semi massive scale strong, the results of the regression analysis obtained Adjusted R2 value of 0.995, meaning that the percentage contribution of variables influence nitrates, phosphates, temperature, pH and salinity of the abundance of Chlorella is 99.5% and the rest is influenced by factors other. The coefficient of impact / highest in pH parameters ie (997.49).Keywords:  Chlorella sp, environmental quality, semi-massive, JeparaCara sitasi: Apriliyanti, S., Soeprobowati, T. R., Yulianto, B. (2016). Hubungan Kemelimpahan Chlorella sp dengan Kualitas Lingkungan Perairan pada Skala Semi Masal di BBBPBAP Jepara. Jurnal Ilmu Lingkungan,14(2),77-81, doi:10.14710/jil.14.2.77-81

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