View Proposal

---

Proposer

Habte Lejebo Leka

Title

Building Energy Consumption Forecasting and Analysis System

Goal

Description

The project aims to develop a system for analysing and forecasting building energy consumption using historical energy and relevant contextual data. Students will perform data preprocessing, time-series analysis, feature engineering, predictive modelling, and model evaluation. The system will provide an interactive web-based dashboard for exploring energy consumption patterns, visualizing forecasts, and presenting prediction results. The project will also investigate how factors such as weather, time, and building characteristics influence energy consumption.

Resources

"Ayenew, Melak, Hang Lei, Xiaoyu Li, Kulla Kekeba, Maregu Assefa, Abebe Tamrat Tegene, Seid Belay Muhammed, and Habte Lejebo Leka. ""Data Analytics and Machine Learning for Reliable Energy Management: A Case Study."" 2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). IEEE, 2022: 1-6Dataset: Building Energy Consumption Dataset Kaggle Link: https://www.kaggle.com/datasets/claytonmiller/buildingdatagenomeproject2"

Background

Url

Difficulty Level

Moderate

Ethical Approval

None

Number Of Students

1

Supervisor

Habte Lejebo Leka

Keywords

building energy consumption, energy forecasting, energy analytics, time-series analysis, machine learning

Degrees

Bachelor of Science in Computational Sciences and Software Engineering