Back to Projects

Team Name:

O.R.G.


Team Members:


Evidence of Work

WeatherWise

Project Info

Team Name


O.R.G.


Team Members


Conor Bennett , Karam , Michael , Tristan , Jordan

Project Description


We have made a twin map and chatbot application that is able to track weather events in real time, and help assist users in being able to craft protection plans for themselves, as well as customised protection plans for precious heritage sights during extreme weather events. We utilise the text generative power of ChatGPT to create custom, user specific action plans based on the context the user gives to the bot, as well as weather information that we feed as context into the bot as well.

Our action plans are built to be tailored to your specific situation. We inform the chatbot of your specific weather emergency, and any associated data that has been posted by the government relevant to the emergency. The chatbot then figures out precisely what questions it needs to be answered by you to create the optimal evacuation / protection plan, and once you answer them, the custom action plan is created.

Please note that this project is only a demo, and thus the GPS location tracker is locked into place in our demo location in Queensland and Moreton Bay. We currently are only pulling data from Queensland local governments, so there is no data available for other regions.

After judging is completed, we will be revoking the API access keys used for both our mapbox API key and openAI key. To use the project, please create your own mapbox API key.

Mapbox:
1. Create an account on https://account.mapbox.com/auth/signup/
2. Create an access token at https://account.mapbox.com/access-tokens/

OpenAI:
1. Create an account at https://platform.openai.com/
2. Create an api key at https://platform.openai.com/account/api-keys

Once you have your keys, continue with the following:

You should see a .envtemplate in your repository once its forked. Please make a copy of the file, and rename it to ‘.env’. Once this is done, your keys will now be private to you, and you may replace with your actual API keys.

We use the OpenAI model gpt-4, which is not available for all users. If you do not have access, please replace all instances of ‘gpt-4’ with ‘gpt-3.5-turbo’ in the code base.

You should now be able to run the code as normal.


#climate #weather #personalisation #ai #chatbot #innovative #culture #heritage

Data Story


The foundation of our application lies in the real-time emergency data sourced from Queensland's official incident data - https://www.data.qld.gov.au/dataset/qfes-incident-data. This data acts as the backbone of our system, allowing the system to know about various weather emergencies.

We use this data in a two ways:

Visualisation: Leveraging the comprehensive emergency dataset, we visually represent weather emergencies on a user-friendly map. This gives users an instant overview of the emergencies around them, enhancing their situational awareness.

Chatbot Contextualisation: Beyond visualisation, the data plays a pivotal role in informing our chatbot. By feeding the chatbot specifics about the user's nearby weather emergency and any associated information posted by the government, we empower the bot with a rich context.

Achievements Through Data: The chatbot, armed with this tailored context, intelligently determines the set of questions it needs to ask users. This is a significant leap from generic queries. By understanding the user's unique circumstances and surrounding emergencies, the chatbot crafts an optimal evacuation or protection plan. The result is a personalised action plan that is not just based on standard protocols but is tailored to the individual's specific situation.

Transparency and Accessibility: Our commitment to transparency and public good is unwavering. The data we rely upon is publicly accessible and is fetched in real-time from this (https://services1.arcgis.com/vkTwD8kHw2woKBqV/arcgis/rest/services/ESCAD_Current_Incidents_Public/FeatureServer/0/query?outFields=*&where=1%3D1&f=geojson). Additionally, the data uses the creative commons licensing terms as outlined by Queensland Fire and Emergency Services (https://www.qfes.qld.gov.au/copyright), ensuring that our use of this data is in line with public permissions and rights.


Evidence of Work

Video

Homepage

Project Image

Team DataSets

QFES Active Incidents Dashboard

Description of Use Used to plot on the map where the incidents are (via a live API call), and the data is automatically fed into the context for the chatbot's large language model to provide more personalised responses. The API endpoint is located at: https://services1.arcgis.com/vkTwD8kHw2woKBqV/arcgis/rest/services/ESCAD_Current_Incidents_Public/FeatureServer/0/query?outFields=*&where=1%3D1&f=geojson This is simply an easily parsable format of the same data for programmatic purposes.

Data Set

QFES Incident Data

Description of Use Used to inform our approach to the problem by giving us historical trends and a larger dataset than the active data. Concrete conclusion from this was that fires are the most prominent issue.

Data Set

Challenge Entries

Moreton Bay being resilient in times of uncertainty (QLD)

How might council be able to utilise our open datasets to assist the community during climate change and significant weather events? We have published datasets that have been built for command centres during adverse weather conditions. What opportunities also exist for these datasets to be used to enable and protect our community during periods of significant weather events?

Eligibility: Open to everyone, preference will be given to those providing solutions using at least one local Moreton Bay region (City of Moreton Bay and/or Unity Water) data set. Employees of City of Moreton Bay with a direct working relationship with members of the local Moreton Bay Gov Hack node organising committee are ineligible to apply for this prize. If unsure, please feel welcome to check and discuss via Slack channels upon commencement of the event.

Go to Challenge | 7 teams have entered this challenge.

Generative AI: Unleashing the Power of Open Data

Explore the potential of Generative AI in conjunction with Open Data to empower communities and foster positive social impact. This challenge invites participants to leverage Generative AI models to analyse and derive insights from Open Data sourced from government datasets. By combining the power of Generative AI with the wealth of Open Data available, participants can create innovative solutions that address real-world challenges and benefit communities.

Eligibility: Ethical use of a generative AI in your project and at least one Australian or New Zealand data set.

Go to Challenge | 29 teams have entered this challenge.

Cultural Coasts: Empowering Aboriginal site protection amidst climate change

As climate change threatens our precious coastal areas, ancient Aboriginal cultural sites are being damaged and pose the very real risk of losing them forever. How do we use climate data to protect them and help empower communities to preserve these irreplaceable cultural landmarks?

Go to Challenge | 3 teams have entered this challenge.

Brisbane City Community Preparedness

How can we use open and public data to understand the community’s level of preparedness for disruption to inform Council’s response and recovery efforts?

Eligibility: Needs to cover the Brisbane City Council area.

Go to Challenge | 3 teams have entered this challenge.