RT Journal Article
T1 Modeling- and simulation-driven methodology for the deployment of an inland water monitoring system
A1 Andrade, Giordy A.
A1 Esteban San Román, Segundo
A1 Risco Martín, José Luis
A1 Chacón Sombría, Jesús
A1 Besada Portas, Eva
AB In response to the challenges introduced by global warming and increased eutrophication, this paper presents an innovative modeling and simulation (M&S)-driven model for developing an automated inland water monitoring system. This system is grounded in a layered Internet of Things (IoT) architecture and seamlessly integrates cloud, fog, and edge computing to enable sophisticated, real-time environmental surveillance and prediction of harmful algal and cyanobacterial blooms (HACBs). Utilizing autonomous boats as mobile data collection units within the edge layer, the system efficiently tracks algae and cyanobacteria proliferation and relays critical data upward through the architecture. These data feed into advanced inference models within the cloud layer, which inform predictive algorithms in the fog layer, orchestrating subsequent data-gathering missions. This paper also details a complete development environment that facilitates the system lifecycle from concept to deployment. The modular design is powered by Discrete Event System Specification (DEVS) and offers unparalleled adaptability, allowing developers to simulate, validate, and deploy modules incrementally and cutting across traditional developmental phases.
PB MDPI
YR 2024
FD 2024-05-09
LK https://hdl.handle.net/20.500.14352/115722
UL https://hdl.handle.net/20.500.14352/115722
LA eng
NO Andrade, G. A., Esteban, S., Risco-Martín, J. L., Chacón, J., & Besada-Portas, E. (2024). Modeling- and Simulation-Driven Methodology for the Deployment of an Inland Water Monitoring System. Information, 15(5), 267. https://doi.org/10.3390/info15050267
NO Comunidad Autónoma de Madrid
NO Ministerio de Ciencia e Innovación (España)
NO Agencia Estatal de Investigación (España)
NO European Commission
DS Docta Complutense
RD 17 abr 2025