Optimizing Energy Consumption and Water Management in small localities through Data Collection and AI Processing / Emmanuel ROCHET / 2024

Titre : Optimizing Energy Consumption and Water Management in small localities through Data Collection and AI Processing Type de document : Mémoire Auteurs : Emmanuel ROCHET, Auteur Année de publication : 2024 Importance : 57 p. Note générale : Pour accéder aux fichiers PDF, merci de vous identifier sur le catalogue avec votre compte Office 365 via le bouton CONNEXION en haut de page Langues : Anglais (eng) Mots-clés : Management INTELLIGENCE ARTIFICIELLE ; ANALYSE DES DONNEES ; ECOLOGIE ; MINORITE ; TECHNOLOGIE Résumé : The report explores the potential of AI and data analytics to enhance energy and water efficiency in small communities. It identifies critical challenges such as the lack of resources and expertise in these areas and proposes innovative solutions including scalable AI technologies and educational programs to improve AI literacy. The document also highlights the importance of empirical research, stakeholder engagement, and the development of sustainable AI models that consider environmental impacts. The conclusion emphasizes the need for a balanced approach that incorporates technological innovation, ecological responsibility, and community involvement to achieve sustainability goals in energy and water management. Programme : Tema Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=602271