NEOM Challenge - King Abdulaziz University

Team Forward-Looking

Welcome! This is the repository for KAU Energy team for the NEOM AI challenge.

University representative - Dr. Adil Khadidos
Supervisor - Prof. Maher Khemakhem

The team members are-

• Abrar Alkhamisi
• Junaid Qurashi
• Osama Younis
• Ulaa Alhaddad
• Zaakki Ahamed Luthufi

Download our app -

Contents of the Repository

• The Models folder contains the trained Machine learning models used for the final prediction

• Weather_prediction.ipynb - Contains all the code and details concerned with training the Neural Networks as a Jupyter Notebook

• NEOM KAU Energy Documentation.docx/.pdf- Contains all the necessary information pertaining to how the problem was defined and the solution was finally achieved

• NEOM_KAU_Energy.pptx - Contains the slides prepared to accompany the project

• Results - Contains the values of predicted vs actual outputs in raw csv format

• Datasets - Contains the datasets from which the ML models were trained from

• Mobile_app - Contains the APK file for the android app of our solution

• Dashboard - Contains the source code of Grafana for all the data visualizations

Required python packages

math, csv, tqdm, matplotlib, sklearn, datetime, keras, pickle, numpy, pandas, xgboost

Dashboard

The dashboard contains the visualization of the datasets and the predictions. They can be found in these links -

Actual versus Predicted - Solar Power

Actual versus Predicted - User Consumption

Consumption Dashboard - Total User Consumption

Solar Power Dashboard - Solar Power

Wind Power Dashboard -

• Wind Power Generation + Wind Speed Rate
• Sky Ceiling Height
• Air Temperature
• Visibility Distance
• Atmospheric Pressure
• Elevation
• Air Temperature Dew Point
• Wind Direction Angle
• Air Density