scholarly journals Perancangan Sistem Kontrol dan Monitoring Kualitas Air dan Suhu Air Pada Kolam Budidaya Ikan

2018 ◽  
Vol 7 (1) ◽  
pp. 13-23 ◽  
Author(s):  
Rozeff Pramana
Keyword(s):  
Water Quality ◽  
Control System ◽  
Real Time ◽  
Temperature Sensor ◽  
Temperature Drop ◽  
Pond Water ◽  
Web Based ◽  
Sensor Reading ◽  
Sensor Temperature

The quality and the temperature of pond water is an important parameter that need to get attention in fish cultivation. Every type of fish has their own characteristic towards water condition and pond temperature. The monitoring of water quality in cultivation pond is done manually and it takes a lot of time. The purpose of this research is to design web-based control system device and monitoring the quality of the water of fish cultivation pond including salinity, temperature and the hardness in real time using special application. This device design consists of salinity sensor, hardness sensor, and temperature sensor. Temperature can be controlled and monitored automatically on the application via computer/laptop. The result of this research is temperature drop by 0,1 oC on a 10 liters pond that takes 18 seconds, and to decrease the temperature of 1 oC takes 180 seconds (3 minutes). To raise the temperature of 0,1 oC takes 264 seconds or 4,4 minutes, and to raise the temperature of 1 oC takes 2640 seconds or 44 minutes. The percentage of error for sensor reading is ranged 2,4% - 3,9%.

scholarly journals Real-time water quality monitoring through Internet of Things and ANOVA-based analysis: a case study on river Krishna

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Prasad M. Pujar ◽  
Harish H. Kenchannavar ◽  
Raviraj M. Kulkarni ◽  
Umakant P. Kulkarni
Keyword(s):  
Water Quality ◽  
Internet Of Things ◽  
Real Time ◽  
River Basin ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Quality Monitoring ◽  
Quality Analysis ◽  
Water Quality Analysis

AbstractIn this paper, an attempt has been made to develop a statistical model based on Internet of Things (IoT) for water quality analysis of river Krishna using different water quality parameters such as pH, conductivity, dissolved oxygen, temperature, biochemical oxygen demand, total dissolved solids and conductivity. These parameters are very important to assess the water quality of the river. The water quality data were collected from six stations of river Krishna in the state of Karnataka. River Krishna is the fourth largest river in India with approximately 1400 km of length and flows from its origin toward Bay of Bengal. In our study, we have considered only stretch of river Krishna flowing in state of Karnataka, i.e., length of about 483 km. In recent years, the mineral-rich river basin is subjected to rapid industrialization, thus polluting the river basin. The river water is bound to get polluted from various pollutants such as the urban waste water, agricultural waste and industrial waste, thus making it unusable for anthropogenic activities. The traditional manual technique that is under use is a very slow process. It requires staff to collect the water samples from the site and take them to the laboratory and then perform the analysis on various water parameters which is costly and time-consuming process. The timely information about water quality is thus unavailable to the people in the river basin area. This creates a perfect opportunity for swift real-time water quality check through analysis of water samples collected from the river Krishna. IoT is one of the ways with which real-time monitoring of water quality of river Krishna can be done in quick time. In this paper, we have emphasized on IoT-based water quality monitoring by applying the statistical analysis for the data collected from the river Krishna. One-way analysis of variance (ANOVA) and two-way ANOVA were applied for the data collected, and found that one-way ANOVA was more effective in carrying out water quality analysis. The hypotheses that are drawn using ANOVA were used for water quality analysis. Further, these analyses can be used to train the IoT system so that it can take the decision whenever there is abnormal change in the reading of any of the water quality parameters.

Physicochemical and heavy metal analysis of pond water quality of Mau-aima vicinity, Allahabad (India)

2017 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Mohammad Rehan ◽  
Dhirendra Kumar Bharati ◽  
Sushmita Banerjee ◽  
Ravindra Kumar Gautam ◽  
Mahesh Chandra Chattopadhyaya
Keyword(s):  
Water Quality ◽  
Heavy Metal ◽  
Pond Water ◽  
Metal Analysis ◽  
Heavy Metal Analysis

Pengaruh Penggunaan Limbah Feses Sapi Dan Probiotik Sebagai Bahan Pakan PeletTerhadap Kandungan Protein Ikan Nila

2017 ◽  
Vol 2 (4) ◽  
Author(s):  
Munadia Munadia
Keyword(s):  
Water Quality ◽  
Protein Content ◽  
Pond Water ◽  
Research Station ◽  
Highest Weight ◽  
Randomized Design ◽  
Commercial Feed ◽  
The Cost ◽  
Pellet Feed

Penelitian tentang pengaruh pengunaan limbah feses sapi dan probiotik sebagai bahan pakan pembuatan pelet terhadap kandungan protein ikan nila telah dilakukan Penelitian dilaksanakan di Station Riset II (dua) Ie Seum, UPT. University Farm, Universitas Syiah Kuala, Aceh Besar. Mulai tanggal 22 Mei sampai 14 Agustus 2016. Tujuan penelitian ini untuk memanfaatkan limbah feses sapi sebagai bahan pakan alternatif pengganti pakan komersil, agar mengurangi biaya pakan dalam budidaya ikan nila sehingga nilai gizi nya meningkat. Penelitian berlangsung selama 90 hari  menggunakan 4 keramba setiap keramba 100 ekor ikan nila. Perlakuan pakan adalah perbedaan persentase substitusi pakan pelet organik dengan ransum komersil yaitu substitusi  pakan pelet organik 0% (P0), substitusi pakan pelet organik 10% (P1), substitusi pakan pelet organik 20% (P2), dan substitusi pakan pelet organik 30% (P3). Parameter yang diamati adalah berat badan akhir, kandungan protein daging ikan dan kualitas air kolam. Rancangan yang digunakan adalah  Rancangan Acak Lengkap (RAL) yang terdiri dari 4 perlakuan dan 4 ulangan. Hasil penelitian menunjukkan bahwa substitusi pakan pelet organik dengan ransum komersil berpengaruh sangat nyata (P0,01) terhadap berat badan, namun tidak berpengaruh nyata (P0,05) terhadap kandungan protein dan kualitas air.  Pertambahan berat badan tertinggi diperoleh pada pemberian substitusi pakan pelet organik sebanyak 10%, yaitu menghasilkan berat badan akhir 24,43 gram dengan kandungan protein 15,31%.  Kualitas air kolam memenuhi standar yaitu suhu 30 ˚C dan pH 7.Effect of Waste Cattle Feces And Probiotics as Material Pellets on Tilapia Nutritional ContentThe research on the use of cow’s feces waste and probiotics as feed ingredients material of pellet making on protein content of Tilapia has been done. The research was conducted at Universitty Farm Research Station II (two) Ie Seum, Universitas Syiah Kuala, Aceh Besar. The begining of research from May 22 to August 14, 2016. The purpose of this study is to utilize the waste of cow's feces as an alternative feed material, replacement of commercial feed, in order to reduce the cost of feed in the growth of Tilapia. The study carried out for 90 days using 4 keramba and consinst of 100 Tilapias. The treatment is a  different percentage of organic  feed substitution with commercial feed. Each, the organic feed subsitussion of organic pellet 0, 10, 20, and 30%. Varialle measured ie: final wish, protein content of Tilapia flesh and pond water quality. The design used was Completely Randomized Design (RAL) consisting of 4 treatments and 4 replications. The results showed that the substitution of organic pellet feed with commercial ration had significant effect (P 0,01) on body weight, but no significant effect (P 0,05) on protein contain  and water quality. The highest weight gain was obtained in 10% organic pellet feeding substitution, which resulted in a final weight of 24.43 grams with a protein content of 15.31%. The quality of pond water was meets the standard temperature of 30 ˚C and pH 7.

scholarly journals SOFTWARE AND HARDWARE AUTOMATED SYSTEM OF CASTS DEFECTS NON-DESTRUCTIVE MONITORING

2019 ◽  
Vol 62 (2) ◽  
pp. 134-140 ◽  
Author(s):  
S. V. Knyazev ◽  
D. V. Skopich ◽  
E. A. Fat’yanova ◽  
A. A. Usol’tsev ◽  
A. I. Kutsenko
Keyword(s):  
Control System ◽  
Product Quality ◽  
Real Time ◽  
Production Control ◽  
Distributed Database ◽  
Data Block ◽  
Automated System ◽  
Quality Analysis ◽  
Technological Processes

Introduction of the “Automated system for operational control of casts production (OCCP AS)” makes the basis of an integrated automated production control system (APCS). It performs three main tasks: control and recording (production, products, materials, etc.), improving quality of casts and operational management of technological processes. Solution of these tasks was accomplished through automating data collection in real time for all production operations, recording material flows, creating operational communication channels, as well as centralized collection, processing and representation of data by the process information server. The next step in building an effective automated control system is to stabilize product quality in changing external conditions, for example, quality of materials, and to optimize production (technology change in order to reduce costs for constant or higher product quality). The second stage is based on mathematical processing and analysis of data coming from OCCP AS, it allows to determine optimal ranges of parameters of technological processes  – “Automated system for optimization and analysis of production progress (OAPP AS)”. OAPP AS consists of two subsystems: quality analysis and technology management. The first solves the problem of data analysis and modeling, the second – calculation of real-time optimal process parameters and real time prediction. The stages tasks compete for access to different hardware resources. The most critical parameter for OCCP AS is performance of server disk arrays, for OAPP AS it is processor performance. In either case, system scaling is effectively solved by parallelizing operations across different servers, forming a cluster, and across different processors (cores) on the same server. To process defect images and to obtain cause-and-effect characteristics, you can use OpenCV software package, which is an open source computer vision library. In course of processing, Sobel operator, Gauss filter and binarization were used. They are based on processing pixels using matrices. Operations on pixels are independent and can be performed in parallel. The task of clustering is reduced to definition of an expert method or using various mathematical algorithms for defects belonging to a specific cluster (data block) through a set of values of dependent factors. Thus, data blocks are formed by the criterion of the defect cause. Calculation of a data block to which a product defect belongs can be very resource-intensive operation. To increase efficiency of image recognition systems and parallelization ofsearch operations, it makes sense to place data clusters on different servers. As a result, there is a need for a distributed database. This is a special class of DBMS, which requires appropriate software. Generation of OAPPAS based on a multi-node cluster with ApacheCassandra DBMS installed and using Nvidia video cards supporting CUDA technology on each node will be the cheapest and most effective solution. Video card is selected based on required number of graphics processors on the node.

scholarly journals Analysis of Water Quality Around the Coast Based on Physical Parameters (Temperature, Salinity and Metal Content) using Wireless Network System

2020 ◽  
pp. 295-300
Author(s):  
Nuril Akhyar ◽  
Kerista Sebayang ◽  
Kurnia Sembiring
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Real Time ◽  
Wireless Network ◽  
Water Solution ◽  
Automation System ◽  
Physical Parameters ◽  
Network System ◽  
Sensor Temperature ◽  
Sea Area

Testing and analyzing the water quality had been conducted by combining several characteristics of sensors (temperature, turbidity and heavy metals) integrated in the wireless network system to determine the quality comparator parameters of water worth drinking in coastal areas. Using sensors made of chitosan compounds to detect heavy metals contained in water. Testing was also done using the DS18B20 sensor (temperature) and TDS (salt levels) by operating a wireless network to transmit data in real time to the web through the GPRS network with the automation system. The sampling used purposive sampling by seafront distance, ± 1 km distance and ± 3 km distance. Testing of copper chips with the addition of Chitosan showed a more stable reading result than without using copper plates (read: pure PCB). At Chitosan biosensors, the addition of CMC shows more varied readings compared to using chitosan biosensors alone. The Ds18b20 Sensor was able to work at high temperatures, with stable value readings. From Sensor readings TDS (EC meter), it’s obtained that the higher the water solution, the greater the reading from the TDS sensor. It was shown on a chart that describing the closer to the sea area, the higher the level of the dissolved substances. The tool was accessed in real time through the Thing Speak platform in accordance with the specified account.

scholarly journals Analisa Kualitas Air Budidaya Udang Vaname (Litopenaeus vannamei) di Tambak Rakyat Kontruksi Dinding Semen Dan Dasar Tambak Semen Di Pantai Konang, Kecamatan Panggul Kabupaten Trenggalek

2021 ◽  
Vol 12 (1) ◽  
pp. 80-85
Author(s):  
Musyaffa Rafiqie
Keyword(s):  
Water Quality ◽  
Smallholder Farmers ◽  
Pond Water ◽  
Quality Analysis ◽  
Optimal Temperature ◽  
Water Quality Analysis ◽  
Simple Tool ◽  
Measurement Results ◽  
Ph Range

The water quality analysis activities carried out by smallholder farmers with the construction of cement walls and cement pond bases on the Konang beach, Panggul District, Trenggalek Regency, have not met the standard standards in the analysis of pond water quality. Pond farmers only analyze the pH, brightness and temperature of the pond water. The research objective was to obtain information and describe the analysis of water quality in the community pond construction of cement walls and the bottom of cement ponds at Konang beach, Panggul District, Trenggalek Regency. The activity of analyzing the water quality of the community plots of construction of cement walls and the bottom of the cement ponds on the Konang beach, Panggul District, Trenggalek Regency, was observed in the form of temperature, brightness and pH, with a pond area of ​​250 m2. Water quality observation activities for 30 days, in one day water quality observations are made twice, namely in the morning and evening. The pH measurement results were obtained, ranging from 7.4 to 8.5, so that the results of measuring the pH of the water in the people's ponds in Koneng Beach were still normal or normal. According to Boyd (2001) in Andi S and Sahabuddin (2014), it is said that water organisms (fish or shrimp) require a pH range of 6.8 - 8.5. the results of measuring the brightness with a simple tool, the measurement results are between 25-40 cm. Badrudin et al (2014) stated that the optimum brightness level of pond water which is influenced by plankton density is around 20 - 40 cm. So that the level of brightness can be concluded that it is still in rational or optimal. The temperature in the ponds was 24 ᴼC - 28 ᴼC, still within normal or optimal. According to Supito (2017), the pond temperature in the range of 28 ᴼ C to 32 ᴼ C is the optimal temperature forcultivating vaname shrimp.

scholarly journals Sistem Monitoring Dan Kontroling Kualitas Air Tambak Udang Vannamei Berbasis Arduino Menggunakan Teknologi Internet Of Things

2020 ◽  
pp. 105-108
Author(s):  
Nuris Dwi Setiawan ◽  
Indra Ava Dianta
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Salt Content ◽  
Ph Sensor ◽  
Pond Water ◽  
Storage Media ◽  
Quality Of Water ◽  
Water Quality Change ◽  
To Receive

Vannamei shrimp is a variety of shrimp that is very sensitive to changes in water quality, growth and life of vannamei shrimp which are directly affected by changes in temperature, salt content, dissolved oxygen, and pH (Hydrogen Potential) content in water. So far, vannamei shrimp cultivators know the quality of water by taking pond water samples with a certain period of time, uncertain natural conditions can make pond water quality change drastically if not maintained can inhibit growth or result in shrimp death.Making a monitoring system and controlling the quality of shrimp pond water using a water temperature sensor, salinity sensor, DO sensor and pH sensor installed on the Arduino Mega 2560 device, NodeMCU is used to receive and send data wirelessly, the system uses programming language c. This tool can be used to start the waterwheel automatically if it is within a certain threshold to maintain the temperature and dissolved oxygen in the pool water based on the value obtained from the sensor. The monitoring results obtained will be displayed to the user in real time through the interface and will be stored in the form of a text file on the storage media.

scholarly journals CONTROL SYSTEM FOR TEMPERATURE, HUMIDITY AND TIME PARAMETERS ON ZELIO SMART RELAY-BASED WATERING PROCEDURES

2019 ◽  
Vol 1 (1) ◽  
pp. 12-16
Author(s):  
Irfan Arif ◽  
Akbar Sujiwa
Keyword(s):  
Control System ◽  
Ambient Temperature ◽  
Temperature Sensor ◽  
Humidity Sensor ◽  
Ambient Air ◽  
Air Humidity ◽  
Human Power ◽  
Temperature And Humidity ◽  
Time Parameters

Watering plants usually done manually using human power. that has risk negligence and inaccuracy. also, in time and cost is not efficient. Another factor that can affect the quality of crops is a factor of humidity and temperature. For those reason, writers made a tool that can work according to the level of humidity and temperature automatically and continuously. This tool uses Zelio Smart Relay as automatic controller. The 808H5V5 humidity sensor and LM35 temperature sensor is used as input. The LM35 temperature sensor detect the ambient temperature, where as 808H5V5 humidity sensor detect ambient air humidity, and time of watering adapted to the Smart Relay timer. The entire sensor input is programmed using ZELIO SOFT 2. Setting the temperature and humidity when the detected 30oC and >70% as well as the timeshows at 08.30 – 09.00 am and 16.00 – 16.30 pm the pump will automatically ON.

Real time control of the integrated urban wastewater system using simultaneously simulating surrogate models

2002 ◽  
Vol 45 (3) ◽  
pp. 109-116 ◽  
Author(s):  
J. Meirlaen ◽  
J. Van Assel ◽  
P. A. Vanrolleghem
Keyword(s):  
Water Quality ◽  
Real Time ◽  
River Water ◽  
Control Strategy ◽  
Treatment Plant ◽  
River Water Quality ◽  
Urban Wastewater ◽  
Real Time Control ◽  
Time Control

The urban wastewater system (sewer and treatment plant) has a major impact on the river water quality of urban streams. To minimise this impact, real time control is a valuable option. Since the ultimate goal of any control strategy is to optimise the quality of the river system, it is useful to take pollutant immissions into account when determining the control strategy and/or the setpoints of the controller. However, a simultaneously simulating model of the complete system is needed in order to allow design and evaluation of such control strategies. In this work an integrated model of the urban wastewater system is created. This has been accomplished by implementing surrogate models of the three subsystems within a single software platform. The coupled submodels are subsequently used in a semi-hypothetical case study to optimise the resulting river water quality. An ammonia sensor in the river has been used to control the amount of water treated biologically in the treatment plant. It was shown that this integrated control could lower the peak ammonia concentration in the part of the river downstream of the treatment plant. Hence, a proof of principle has been given that the use of measurements in the river to perform control actions in the sewer system and the treatment plant is a promising option.

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