Sustainable Moreton Bay (QLD)
How can we create a diverse and flourishing planet for generations to come?
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Team Energetik
Energetik is a revolutionary app, in the energy sector, that brings in gamification and reward-based systems to reduce user's month electricity bills using machine learning models, which ultimately contributes to saving the earth from global warming . By tracking the green house gas emissions, Energetik hopes to use human behavioural strategies, for example positive reinforcement technique , to motivate users to think about how their actions can help their finances and also the environment. At the moment, we as human beings are all affected by the COVID-19 pandemics. Finally, Energetik provides COVID-19 relief, keeping in mind of the "impacted" citizen based on their credit history prior to the COVID-19 pandemic, to suggest them alternative payments by redeeming rewards and generating the delayed instalment payment plans.
(https://github.com/ayaz95/Extra_Files_2021_GovHack/blob/main/Future%20Scope.pdf)
Due to the nature of GovHack, there were many features we thought of and would love to implement, but did not have time for. These include:
Energetik's main aims include to aid user's decisions that help them manage their finances, motivate users to go green, and provide Covid-Relief schemes to support impacted Australian Citizens to let them transition to covid-normal. In the process of this project, we have aggregated datasets from open data sources like data.gov.au, bom.gov.au, ausgrid.com.au, and kaggle.com to find the factors affecting energy consumption and utilize machine learning techniques to make bill predictions to aid the users to manage their budget. Energetik has used more than 10,000 data points combined to analyze the price and demand patterns during peak hours and found that there are certain hours in the day that are cheaper for the user to use electricity, and found that certain weather conditions significantly affect the user's energy consumption. Moreover, the data has identified certain sources of energy and their correlation with weather conditions.
Description of Use To find how various weather conditions affect air temperature and created a Machine Learning model to predict air temperature. So that it can be used to forecast electricity consumption.
Description of Use To identify price and demand patterns with respect to hours of the day.
Description of Use To find the correlation between energy and weather conditions.
Description of Use We used this dataset to compare the average daily usage of electricity in the neighborhood LGA.
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