Shiny Abraham, Arman Shahbazian, Kevin Dao, Han Tran, P. Thompson
{"title":"An Internet of Things (IoT)-based aquaponics facility","authors":"Shiny Abraham, Arman Shahbazian, Kevin Dao, Han Tran, P. Thompson","doi":"10.1109/GHTC.2017.8239339","DOIUrl":null,"url":null,"abstract":"Aquaponics, also known as the integration of hydroponics with aquaculture, has emerged to be a successful model of sustainable food production. The symbiotic relationship between fish, plants, and bacteria, in a controlled environment, is contingent upon optimal water quality conditions. This calls for a need to develop continuous water-quality monitoring techniques that are based on intelligent data acquisition, communication, and processing. This work focuses on using Internet of Things (IoT) technology to configure and deploy smart water-quality sensors that provide remote, continuous, and real-time information of indicators related to water quality, on a graphical user interface (GUI). A sensing system comprising of a Raspberry Pi and commercial sensor circuits 1 and probes that measure Dissolved Oxygen (DO), pH, and water temperature was deployed in an aquaponics facility in a town called Manchay, near Lima, Peru2. Data acquired from the sensor system is uploaded to ThingSpeak 3, an IoT analytics platform service that provides real-time data visualization and analysis. Continuous monitoring of this data, and making necessary adjustments, will facilitate the maintenance of a healthy ecosystem that is conducive to the growth of fish and plants, while utilizing about 90% less water than traditional farming.","PeriodicalId":248924,"journal":{"name":"2017 IEEE Global Humanitarian Technology Conference (GHTC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Global Humanitarian Technology Conference (GHTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GHTC.2017.8239339","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Aquaponics, also known as the integration of hydroponics with aquaculture, has emerged to be a successful model of sustainable food production. The symbiotic relationship between fish, plants, and bacteria, in a controlled environment, is contingent upon optimal water quality conditions. This calls for a need to develop continuous water-quality monitoring techniques that are based on intelligent data acquisition, communication, and processing. This work focuses on using Internet of Things (IoT) technology to configure and deploy smart water-quality sensors that provide remote, continuous, and real-time information of indicators related to water quality, on a graphical user interface (GUI). A sensing system comprising of a Raspberry Pi and commercial sensor circuits 1 and probes that measure Dissolved Oxygen (DO), pH, and water temperature was deployed in an aquaponics facility in a town called Manchay, near Lima, Peru2. Data acquired from the sensor system is uploaded to ThingSpeak 3, an IoT analytics platform service that provides real-time data visualization and analysis. Continuous monitoring of this data, and making necessary adjustments, will facilitate the maintenance of a healthy ecosystem that is conducive to the growth of fish and plants, while utilizing about 90% less water than traditional farming.