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Peer-reviewedCC BYFrontiers in artificial intelligence

An AI-driven hybrid random forest-LSTM framework for IoT-based groundwater level prediction and sustainable water management in Chennai, India

  • S. Boomika1
  • R. Sitharthan2
  • R. Tanukasree1
  • R. Senthil Kumar1
  1. 1School of Electrical Engineering, Vellore Institute of Technology , ,
  2. 2Centre for Smart Grid Technologies, Vellore Institute of Technology , ,
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Cite

BibTeXRIS
BibTeX
@article{boomika2026aidriven,
  title = {{An AI-driven hybrid random forest-LSTM framework for IoT-based groundwater level prediction and sustainable water management in Chennai, India}},
  author = {S. Boomika and R. Sitharthan and R. Tanukasree and R. Senthil Kumar},
  journal = {Frontiers in artificial intelligence},
  year = {2026},
  month = oct,
  url = {https://europepmc.org/article/PMC/PMC13669168},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - An AI-driven hybrid random forest-LSTM framework for IoT-based groundwater level prediction and sustainable water management in Chennai, India
AU  - S. Boomika
AU  - R. Sitharthan
AU  - R. Tanukasree
AU  - R. Senthil Kumar
PY  - 2026
DA  - 2026/10/19
JO  - Frontiers in artificial intelligence
UR  - https://europepmc.org/article/PMC/PMC13669168
SN  - 2624-8212
ER  -