Net-Zero Smart city AI-based Strategic Decision System

[#1]

                                                       

Develop a smart Deep Learning model (AI, ML, NN) to analyze thousands of energy sources in a Smart city / Municipality (public lighting, buildings energy consumption, use of external data sources, degree days, Temps, local weather conditions, demographics, geospatial data, financial data, utility bills, etc) and create specific KPIs (quantitative, qualitative) in order to model, predict and detect anomalies and outliers (energy, C02, etc) so that to propose automatically specific solutions (storage, RES, Eco mobility, DERs) to covert this City into a Net-Zero City

The model will be applied to one Smart City in Greece (we have data) and then after the supervised learning process and the finalization, the model will be able to be applied to ALL Cities in the World, in order to convert them into Net-Zero Cities

This applies to UNSDG 11

We will also apply this model to our customers (Smart Cities) as one of the leading Utilities in Greece

                                                       

Team Name	PIL
Track	Data for Good
Use Case	Smart City decision support system to self-adapt and propose Net-zero driven solutions, based on various large data inputs
Technology	Platform-based offering, Python Algos, AI approach, Data analysis, Agents, Supervised Learning
Region	Europe, Smart Cities, Municipalities
Team lead	Dr. Vassilis Nikolopoulos @Vnikolop
Team members	Nikos Babis, Dimitris Karpodinis (Data Scientists)

Smart City Assets