Treatment to Tap - securing water quality by extracting value from high resolution sensor network data
Lead Research Organisation:
University of Sheffield
Department Name: Civil and Structural Engineering
Abstract
This project will take advantage of an internationally unique 12-month period time series data set from deployment of over 75 multi parameter water quality instruments in the Southampton area of Southern Water network. The data set will be made available for development and application of analytical techniques on the unique Siemens MindSphere environment.
This dataset and access via MindSphere will readily enable:
Technology transfer and adaptation of tools and techniques developed for water quantity analysis to water quality.
Techniques developed for very limited one-off example water quality data sets to be generalised, enhanced, and validated.
Application and development of new techniques from the rapidly developing word of machine learning and AI.
This dataset and access via MindSphere will readily enable:
Technology transfer and adaptation of tools and techniques developed for water quantity analysis to water quality.
Techniques developed for very limited one-off example water quality data sets to be generalised, enhanced, and validated.
Application and development of new techniques from the rapidly developing word of machine learning and AI.
People |
ORCID iD |
| Joby Boxall (Primary Supervisor) | |
| Killian John Gleeson (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/S023666/1 | 01/04/2019 | 30/09/2027 | |||
| 1983969 | Studentship | EP/S023666/1 | 30/09/2019 | 29/09/2023 | Killian John Gleeson |