SCE – Smart City Energy Analytics
Objectives
Design a decision-support tool allowing cities’s intelligence energy management.
SCE (Smart City Energy Analytics) project was launched in 2014 with the aim of developing solutions for better energy management. The main goal was to take benefit from Artificial Intelligence techniques at different scales of the city of tomorrow. Various granularities and end-users are targeted. Scenarios simulating buildings, districts and factories and mobility of the future are envisioned.
Results
Publications
SCE publications
A New Crypto-Classifier Service for Energy Efficiency in Smart Cities.
Oana Stan, Mohamed-Haykel Zayani, Renaud Sirdey, Amira Ben Hamida, Alessandro Ferreira Leite, Mallek Sallami-Mziou
Conférence SmartGreens 2018
A novel model and tool for energy renovation planning in French Residential buildings and districts.
Kahina Amokrane-Ferka and Amira Ben Hamida
International Conference on Smart Data and Smart Cities (SDSC) 2018
Train speed profiles optimization using a genetic algorithm based on a random-forest model to estimate energy consumption.
Ahmed Amrani, Amira Ben Hamida, Tao Liu, Olivier Langlois
Transport Research Arena 2018
A SaaS implementation of a New Generic Crypto-Classifier Service for Secure Energy Efficiency in Smart Cities.
Oana Stan, Mohamed-Haykel Zayani, Renaud Sirdey, Amira Ben Hamida, Mallek Sallami-Mziou, Alessandro Ferreira Leite
Springer CCIS Series Book 2018
Privacy-preserving Tax Calculations in Smart Cities by Means of Inner-Product Functional Encryption.
Oana Stan, Renaud Sirdey, Cédric Gouy-Pailler, Pierre Blanchart, Amira Ben Hamida, Mohamed-Haykel Zayani.
Cyber Security In Networking Conference (CSNET) 2018
Probabilistic load flow method for estimation of electrical network reliability indices
Fallilou Diop, Martin Hennebel
Powertech Manchester 2017
A dedicated mixture clustering-based model applied on smart meters data: Identification and analysis of electricity consumption behaviors.
Fateh Nassim Melzi, Allou Samé, Mohamed Haykel Zayani, and Latifa Oukhellou
Revue Energies 2017
Stratégies de planification de recharge de véhicules électriques pour minimiser le coût financier.
Fallilou Diop, Martin Hennebel
Symposium du Génie électrique 2016
Hourly solar irradiance forecasting based on machine learning models.
Nassim Fateh Melzi, Latifa Oukhellou and co.
International Conference on Machine Learning and Application (ICMLA) 2016
Towards Smart City Energy Analytics: Identification of Electric Consumption Patterns Based on Clustering Approaches.
Nassim Fateh Melzi, Latifa Oukhellou and co.
Complex System Design and Management (CSD&M) 2015
Identifying Daily Electric Consumption Patterns from Smart Meter Data by Means of Clustering Algorithms.
Nassim Fateh Melzi, Latifa Oukhellou and co.
International Conference on Machine Learning and Application (ICMLA) 2015
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