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The real time monitoring of water quality in IoT environment
Abstract
In order to ensure the safe supply of the drinking water the quality needs to be monitor in real time. In this paper we present a design and development of a low cost system for real time monitoring of the water quality in IOT(internet of things). The system consist of several sensors is used to measuring physical and chemical parameters of the water. The parameters such as temperature, PH, turbidity, conductivity, dissolved oxygen of the water can be measured. The measured values from the sensors can be processed by the core controller. The raspberry PI B+ model can be used as a core controller. Finally, the sensor data can be viewed on internet using cloud computing.
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Citations
Cited by
Internet of things for smart agriculture: Technologies, practices and future direction
Ray, P. P. (2017) · Journal of Ambient Intelligence and Smart Environments · doi:10.3233/ais-170440 · Cited by 532
IoT Based Real-time River Water Quality Monitoring System
Chowdury, M. S. U., Emran, T. B., Ghosh, S., Pathak, A., Alam, M. M., Absar, N., Andersson, K., & Hossain, M. S. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.08.025 · Cited by 319
IoT-based platform for environment data sharing in smart cities
Rubí, J. N. S., & de Lira Gondim, P. R. (2021) · International Journal of Communication Systems · doi:10.1002/dac.4515 · Cited by 36
Metadata
- Authors
- Vijayakumar, N., & Ramya, R.
- Venue
- 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS)
- Publisher
- IEEE
- Published
- 2015-03
- Pages
- 1-5
- OpenAlex
- W1785618169
- Cited by
- 191
- References
- 0
- FWCI
- 48.27
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: The real time monitoring of water quality in IoT environment. https://app.cochat.ai/papers/10.1109/iciiecs.2015.7193080
- The paper
- Vijayakumar, N., & Ramya, R. (2015). The real time monitoring of water quality in IoT environment. 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS). https://doi.org/10.1109/iciiecs.2015.7193080
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
