Potential Readings of Water Turbidity Values Based on Optical Sensors on Fish-Rearing Biofloc Media

IF 0.5 Q4 OPTICS Photonics Letters of Poland Pub Date : 2023-04-02 DOI:10.4302/plp.v15i1.1176
R. Siskandar, Wiyoto Wiyoto, Sesar Husen Santosa, Julie Eka Sari, Giri Maruto Darmawangsa, A. Hidayat, Derry Dardanella, B. R. Kusumah
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Abstract

An optical sensor-based water turbidity value reader has been made with an IR-emitting light source, a red LED, and a laser. The tool is made as a solution for reading water turbidity values that are impermeable to light-intensity disturbances. In principle, each light emitter will always shoot toward the sensor. The position of the transmitter and sensor is right between the flowing water pipes. When the water flows, the sensor will read the hardness value of the water (in analog value). Of course, pipes, sensors, transmitting sources, and electronic devices are protected by a casing that is impermeable to light intensity. The casing can be placed outside the pool to facilitate the process of tool maintenance. The tool was made in the SV-IPB University hardware laboratory and tested in the SV-IPB University fish pond from April 2022 to October 2022. Tests for all emitting light sources were carried out on aqueous media which has a flock of 6 ml/l. The results show that the three transmitter sources have analog readings in the same range, namely 2200 to 2300. However, of the three, the red LED transmitter sources have consistent reading values for three replications. Thus, the red LED light emitting source has good potential to be used as an optical sensor to read the value of water turbidity in biofloc media. This was proven again in measurements using variations in flock values (5 ml/l, 6 ml/l, 12 ml/l, and 17 ml/l), indicating that the higher the flock value, the greater the resistance value, so the output voltage value is higher. small. The output voltage value can be calculated from the analog value measured by the device. Full Text: PDF References S.-K. Kim et al., "Different maturation of gut microbiome in Korean children", Front. Microbiol. 13, 1 (2022) CrossRef S. Configuration, "Production of Marine Shrimp Integrated with Tilapia at High Densities and in a Biofloc System: Choosing the Best Spatial Configuration", fishes, 7, 283 (2022). CrossRef H.-H. Huang et al., "FinBERT: A Large Language Model for Extracting Information from Financial Text", Int. Conf., 1 (2022). CrossRef N. H. Sadi, D. Agustiyani, F. Ali, M. Badjoeri, Triyanto, "Application of Biofloc Technology in Indonesian Eel Anguilla bicolor bicolor Fish Culture: Water Quality Profile", IOP Conf. Ser. Earth Environ. Sci., 1062, 1 (2022). CrossRef M. M. Rashid, A. A. Nayan, M. O. Rahman, S. A. Simi, J. Saha, M. G. Kibria, "IoT based Smart Water Quality Prediction for Biofloc Aquaculture", Int. J. Adv. Comput. Sci. Appl., 12, 56, (2021). CrossRef D. Krummenauer, A. Freitas Silva, M. Xavier, L. H. Poersch, A. Cardozo, "Comparative analysis of the culture of pink shrimp Farfantepenaeus brasiliensis and Pacific white shrimp Litopenaeus vannamei in biofloc system", Aquac. Int., 1 (2022). CrossRef A. Suloma Mahmoud, A. H. Gomaa, M. A. A. Abo-Taleb, H. R. A. Mola, M. S. Khattab, R. S. Mabroke, "Heterotrophic biofloc as a promising system to enhance nutrients waste recycling, dry diet acceptance and intestinal health status of European eel (Anguilla anguilla)", AACL Bioflux, 14, 1021 (2021). DirectLink M. E. Ramadani, B. Raafi'u, M. Mursid, R. H. Ash-Shiddieqy, A. T. Zain, A. Fauzan Ladziimaa, "Design and Development of Monitoring System on Carp Farming Ponds As IoT- Based Water Quality Control", ICRACOS 2021 - 2021 3rd Int. Conf., 5, 148 (2021). CrossRef G. S. Carter, K. P. Kowalski, M. R. Eggleston, "Turbidity and Estimated Phosphorus Retention in a Reconnected Lake Erie Coastal Wetland", Water (Switzerland), 14, 1 (2022). CrossRef I. I. Mohamedd, N. Hikmah, B. Azizan, N. Elfadil, M. Pahang, "Design and Development of Microcontroller Based Automatic Fish Feeder System", Ijesc, 10, 25380 (2020). DirectLink
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基于光学传感器的鱼类养殖生物块体水体浊度值的电位读数
利用红外发光光源、红色LED和激光制成了一种基于光学传感器的水浑浊值读取器。该工具是作为读取水浊度值的解决方案,不受光强干扰。原则上,每个光发射器总是朝传感器发射。变送器和传感器的位置在流动水管之间。当水流动时,传感器将读取水的硬度值(模拟值)。当然,管道、传感器、传输源和电子设备都有不透光的外壳保护。套管可置于池外,方便工具维修过程。该工具由SV-IPB大学硬件实验室制造,并于2022年4月至2022年10月在SV-IPB大学鱼塘进行了测试。所有发射光源的测试都在6 ml/l的水介质上进行。结果表明,三种发射机源的模拟读数在相同的范围内,即2200 ~ 2300。然而,在这三个,红色LED发射机源有一致的读数值为三个复制。因此,红色LED发光光源具有良好的潜力,可以作为光学传感器来读取生物絮团介质中水的浊度值。在使用群值变化(5 ml/l、6 ml/l、12 ml/l和17 ml/l)的测量中再次证明了这一点,表明群值越高,电阻值越大,因此输出电压值也越高。小。输出电压值可由装置测量的模拟值计算得到。全文:PDFKim et al.,“韩国儿童肠道微生物群的不同成熟”,Front。交叉参考配置,“罗非鱼与海洋对虾在高密度生态系统中的融合:最佳空间配置选择”,水产学报,2017,28(2022)。CrossRef h。Huang et al.,“FinBERT:一种用于从金融文本中提取信息的大型语言模型”,英译。会议,1(2022)。参考文献N. H. Sadi, D. Agustiyani, F. Ali, M. Badjoeri, Triyanto,“生物絮团技术在印尼鳗鲡双色鱼养殖中的应用:水质概况”,国际水产科学院学报。地球环境。科学。生物医学工程学报,2012,1(2)。M. M. Rashid, A. A. Nayan, M. O. Rahman, S. A. Simi, J. Saha, M. G. Kibria,“基于物联网的生物群落水产养殖智能水质预测”,[j]。J. Adv.计算。科学。达成。, 12, 56,(2021)。CrossRef D. Krummenauer, A. Freitas Silva, M. Xavier, L. H. Poersch, A. Cardozo,“巴西法凡特对虾和凡纳滨对虾在生物群落系统中培养的比较分析”,水生生物学报。Int。, 1(2022)。引用本文:a . Suloma Mahmoud, a . H. Gomaa, M. a . abob - taleb, H. R. a . Mola, M. S. Khattab, R. S. Mabroke,“异养生物絮团对鳗鲡营养废物回收、干日粮接受和肠道健康状况的影响”,水产学报,14,21(2021)。M. E. Ramadani, B. Raafi'u, M. Mursid, R. H. Ash-Shiddieqy, A. T. Zain, A. Fauzan Ladziimaa,“基于物联网的鱼塘水质监测系统的设计与开发”,中国水产科学与工程学报,2021 - 2021第3期。会议,5,148(2021)。陈建军,张建军,张建军,“生态环境下湖泊生态系统的研究进展”,生态环境学报,2014,29(2)。引用本文:李建军,张建军,张建军,张建军。基于单片机的自动喂鱼系统的设计与实现[j] .中国机械工程,2016,33(6):559 - 564。DirectLink
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