دورية أكاديمية
An internet of things labelled dataset for aquaponics fish pond water quality monitoring system.
| العنوان: | An internet of things labelled dataset for aquaponics fish pond water quality monitoring system. |
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| المؤلفون: | Udanor CN; Department of Computer Science, University of Nigeria Nsukka, Nigeria., Ossai NI; Department of Environmental Biology and Zoology, University of Nigeria Nsukka, Nigeria., Nweke EO; Department of Computer Science, University of Nigeria Nsukka, Nigeria., Ogbuokiri BO; Department of Computer Science, University of Nigeria Nsukka, Nigeria., Eneh AH; Department of Computer Science, University of Nigeria Nsukka, Nigeria., Ugwuishiwu CH; Department of Computer Science, University of Nigeria Nsukka, Nigeria., Aneke SO; Department of Computer Science, University of Nigeria Nsukka, Nigeria., Ezuwgu AO; Department of Computer Science, University of Nigeria Nsukka, Nigeria., Ugwoke PO; Department of Computer Science, University of Nigeria Nsukka, Nigeria., Christiana A; ICT Unit, University of Nigeria Nsukka, Nigeria. |
| المصدر: | Data in brief [Data Brief] 2022 Jun 20; Vol. 43, pp. 108400. Date of Electronic Publication: 2022 Jun 20 (Print Publication: 2022). |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier B.V Country of Publication: Netherlands NLM ID: 101654995 Publication Model: eCollection Cited Medium: Internet ISSN: 2352-3409 (Electronic) Linking ISSN: 23523409 NLM ISO Abbreviation: Data Brief Subsets: PubMed not MEDLINE |
| أسماء مطبوعة: | Original Publication: [Amsterdam] : Elsevier B.V., [2014]- |
| مستخلص: | Aquaculture, which is the breeding of fishes in artificial ponds, seems to be gaining popularity among urban and sub-urban dwellers in Sub-Saharan Africa and Asia. Tenant aquaculture enables individuals irrespective of their profession to grow fishes locally in a little space. However, there are challenges facing aquaculture such as the availability of water, how to monitor and manage water quality, and more seriously, the problem of absence of dataset with which the farmer can use as a guide for fish breeding. Aquaponics is a system that combines conventional aquaculture with hydroponics (the method of growing plants in water i.e. soilless farming of crops). It uses these two technologies in a symbiotic combination in which the plant uses the waste from the fish as food while at the same time filtering the water for immediate re-use by the fish. This helps to solve the problem of frequent change of water. An Internet of Things (IoT) system consisting of an ESP-32 microcontroller which controls water quality sensors in aquaponics fish ponds was designed and developed for automatic data collection. The sensors include temperature, pH, dissolved oxygen, turbidity, ammonia and nitrate sensors. The IoT system reads water quality data and uploads the same to the cloud in real time. The dataset is visualized in the cloud and downloaded for the purposes of data analytics and decision-making. We present the dataset in this paper. The dataset will be very useful to the agriculture, aquaculture, data science and machine learning communities. The insights such dataset will provide when subjected to machine learning and data analytics will be very useful to fish farmers, informing them when to change the pond water, what stocking density to apply, provide knowledge about feed conversion ratios, and in predict the growth rate and patterns of their fishes. Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: (© 2022 The Authors. Published by Elsevier Inc.) |
| فهرسة مساهمة: | Keywords: Aquaculture; Catfish; IoT; Microcontroller; Sensors; aquaponics |
| تواريخ الأحداث: | Date Created: 20220708 Latest Revision: 20220708 |
| رمز التحديث: | 20231215 |
| مُعرف محوري في PubMed: | PMC9253161 |
| DOI: | 10.1016/j.dib.2022.108400 |
| PMID: | 35799855 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 2352-3409 |
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| DOI: | 10.1016/j.dib.2022.108400 |