SMART CARBON FOOTPRINT MONITORING MODEL FOR BUILDINGS IN BANDUNG INSTITUTE OF TECHNOLOGY GANESHA

Rapid innovation in technology has led to unwanted side effects such as global warming and climate change. Recent studies report that in today's digital age, many industries use energy-consuming technologies in their buildings. Unfortunately, this results in considerable carbon emissions tha...

Full description

Saved in:
Bibliographic Details
Main Author: Sakura Kireyna Aji, Byan
Format: Theses
Language:Indonesia
Subjects:
Online Access:https://digilib.itb.ac.id/gdl/view/77047
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Institut Teknologi Bandung
Language: Indonesia
Description
Summary:Rapid innovation in technology has led to unwanted side effects such as global warming and climate change. Recent studies report that in today's digital age, many industries use energy-consuming technologies in their buildings. Unfortunately, this results in considerable carbon emissions that are often unmonitored and poorly managed. This challenge also occurs in buildings at Institut Teknologi Bandung that operate various facilities that can contribute to the level of carbon footprint. Currently, there is no system that monitors energy use and emission production in every building at Institut Teknologi Bandung. Data collection related to energy use is still done manually and there is no follow-up on the information obtained so that it cannot be known which buildings contribute the most and have the potential to cause a spike in the amount of carbon emissions at the Bandung Institute of Technology. To solve this problem, this research focuses on developing a carbon footprint smart monitoring model for buildings at Institut Teknologi Bandung by utilizing prediction features so that preventive measures can be taken to avoid an increase in carbon emission levels. The development of this model includes improving the flow of information using the Business Process Reengineering (BPR) method, classifying the sustainability value of buildings with the standardization of the Leadership in Energy and Environmental Design (LEED) assessment, and developing a prediction system using Vector Auto Regression (VAR). This model is expected to provide an overview of the level of carbon production of each building and future projections so that it can be taken into consideration in efforts to manage emissions at the Bandung Institute of Technology.