Research Article
A Cost-Effective Real-Time Monitoring System for Water Quality Management Based on Internet of Things
@INPROCEEDINGS{10.1007/978-3-030-51005-3_26, author={Gon\`{e}alo Marques and Rui Pitarma}, title={A Cost-Effective Real-Time Monitoring System for Water Quality Management Based on Internet of Things}, proceedings={Science and Technologies for Smart Cities. 5th EAI International Summit, SmartCity360, Braga, Portugal, December 4-6, 2019, Proceedings}, proceedings_a={SMARTCITY}, year={2020}, month={7}, keywords={Agriculture Enhanced living environments Internet of Things Mobile computing Smart cities Water quality monitoring}, doi={10.1007/978-3-030-51005-3_26} }- Gonçalo Marques
Rui Pitarma
Year: 2020
A Cost-Effective Real-Time Monitoring System for Water Quality Management Based on Internet of Things
SMARTCITY
Springer
DOI: 10.1007/978-3-030-51005-3_26
Abstract
Water is a limited and essential resource to human existence. Furthermore, water management is not only relevant but also a complex task for several applications such as agriculture and industry. Consequently, the water quality must be monitored in real-time not only to detect water contamination scenarios in a useful time for enhanced public health in smart cities but also to improve agricultural productivity. Internet of Things is the pervasive presence of a variety of objects with interaction and cooperation capabilities among them to reach a common objective and can provide the interoperability to develop essential and cost-effective applications for enhanced smart cities and agricultural activities. This paper presentsiWater, a cost-effective solution for water quality monitoring based on Internet of Things architecture. This solution is composed of a hardware prototype for water quality analysis and support Web compatibility for data consulting. The results show that theiWaterprovides efficient and effective water quality monitoring using integrated communication technology, combining sensitivity, flexibility, and accuracy of measurement in real-time, allowing significant evolution of the current water quality monitoring systems.
