Mohcine Draou, PhD
  • Bio
  • Papers
  • Experience
  • Projects
  • Projects
    • PVfitlab.com
    • Nassim AI
    • Nassim Home
    • Nassim Autoconsommation
  • Projects
  • Experience
  • Blog
  • Coming Soon
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    • Learn Python
  • Publications
    • Enhancing Home Energy Management: A Day-Ahead Machine Learning Approach Using EMHASS for Predictive Temperature Control
    • Prediction of residential building occupancy using Machine learning with integrated sensor and survey Data: Insights from a living lab in Morocco
    • Multi-objective optimization of a diverter-driven photovoltaic water heater: A residential case study in Morocco
    • Data-Driven Approach for Residential Occupancy Modeling Using PIR Sensors: A Moroccan Case Study
    • Techno-economic feasibility assessment of a photovoltaic water heating storage system for self-consumption improvement purposes
    • Exploring BIM and Energy Analysis Potential of Binayate Software Tools for Energy Retrofit Purposes
    • Impact of insulation and natural ventilation on the thermal performances of a west-facing bioclimatic building

Nassim AI

Sep 1, 2024 · 1 min read

An approach based on machine learning (ML) algorithms is being applied to the real data generated by Nassim Home (Energy, Temperature, Water…). The aim is to set up a real-time machine learning algorithm, on the basis of which future decisions can be taken.

Last updated on Feb 26, 2025
Scikit-Learn EMHASS Home Assistant
Authors
R2 - Recognised Researcher

← PVfitlab.com Feb 1, 2025
Nassim Home Jun 1, 2021 →

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