CloseRanks powered by Resonance

Project Info

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Project Description


CloseRanks

CloseRanks is the first application built on top of the Resonance algorithm and has been developed to demonstrate how the Resonance Algorithm can be applied to solve real problems in the world.

Overview

CloseRanks is application to assist with community co-ordination during times of emergency, by matching available community resources with members of the community who require them. CloseRanks leverages the Resonance API to determine if an emergency is happening and predict what type of emergency it is, even if there is no official government information available.

“The UberEats for emergency resource co-ordination”

User Flow

  1. A volunteer adds the resources which they have available in an emergency situation ahead of time
  2. Civilian, business or organisation uploads request for assistance with emergency labour/asset/transport
  3. “Resonance algorithm” matches volunteer to assistance request
  4. Request route is assessed for safety against data from emergency services
  5. Mission is approved for action

Overall Goal

To keep people, assets and infrastructure safe in emergencies by enabling grass-roots community involvement and support powered by helpful data.


Data Story


The resonance API

The Resonance API uses a range of data, including federal, state and local government data as well as data from social media and puts these volumes of data through a series of machine learning algorithms to predict the probability of events events in real time. The first application to exist within the Resonance ecosystem is CloseRanks, which uses the predictions of Resonance API to allow people to provide and receive tangible support in an emergency.

How it works

Resonance will initially use data from BOM, Emergency Services, and CSIRO and various social media services to determine:
his data is collated and processed by Resonance to determine:

In the future, this data will be made available to journalists and other members of the public in real-time via the subscription-based Resonance platform, which displays the structured event data (alongside the source data) in real-time. If a user reviews the source data and determines that the algorithm has made a mistake, they can flag that event as inaccurate and provide reasoning as to why. This information will help train the algorithm over time.

For now, this structured data is published to an API which is consumed by applications within the Resonance Ecosystem. The Resonance Ecosystem is a collection of first and third-party applications built on top of the data provided by the Resonance algorithm.


Evidence of Work

Video

Homepage

Team DataSets

Australian Estuaries Database - CAMRIS

Description of Use: Used to train the Resonance machine learning API to estimate the probability of emergency flooding events.

Data Set

City of Hobart Water Flood Zones

Description of Use: Used to inform the Resonance machine learning API of flood risks, and predict probabilities of flood events in realtime, in the Hobart area.

Data Set

BOM weather warnings, Tasmania

Description of Use: Used to inform the Resonance machine learning API of current emergency events.

Data Set

Challenges

Most Outstanding Tasmanian Benefit

Region: Tasmania

Challenge

🌟 Climate Change Issues in Hobart

Region: Tasmania

Challenge

Thrive or survive: how can we adapt for the future?

Region: Australia

Challenge

Best Use of Tasmanian Spatial Data

Region: Tasmania

Challenge

Most Tasmanian Commercial Benefit

Region: Tasmania

Challenge

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