A field-deployable water quality monitoring with machine learning-based smartphone colorimetry
Vakkas Doğan, Tuǧba Isık, Volkan Kılıç, Nesrin Horzum
Abstract
. The proposed approach was also tested with real samples taken from local water sources. The results prove that incorporating color strips with ML with a smartphone application can be used for water quality monitoring, which offers promising alternatives for sophisticated equipment that is especially applicable in resource-limited settings.
Topics & Concepts
Computer scienceWater qualityRobustness (evolution)Android appArtificial intelligenceColorimetryAndroid (operating system)PollutantProof of conceptMachine learningEnvironmental scienceReal-time computingComputer visionOperating systemOrganic chemistryEcologyBiologyChemistryBiochemistryGeneWater Quality Monitoring TechnologiesBiosensors and Analytical DetectionAir Quality Monitoring and Forecasting