Through strong community relationships, Day One Relief serves disaster-impacted populations. Since each disaster is unique, a relief solution that is predictable, repeatable and systematic in nature has been identified as what’s needed to make an improved impact.
Day One Relief was founded in September 2018, during Hurricane Florence, in order to rapidly source and deliver supplies via air and road to those affected by the storm. Our formation came as a result of our efforts spearheading the rapid response at the TAC AIR terminal at RDU. We brought together volunteer pilots and NGOs who have been on the ground in eastern NC, some for 45+ years. We raised the supply and engaged the community, resulting in 1500 volunteers throughout the week.
We are working on creating racial equity in the vaccine rollout. We are phonebanking, canvassing, and helping organize vaccine clinics with vaccine providers, HBCUs and DHHS.
Whether it’s a hurricane, or Pandemic relief or a building collapse, The best first responders are the local NGOS, these organizations know their environments and people best. NGOs are the “go-to” entities in disaster response and recovery because of their real insight on the needs, and sociocultural complexities of their neighborhoods.
Day One Relief goes wherever the gaps are, and recently that has been the supply chain for the COVID-19 response. It has secured and delivered gowns, booties and masks to federal prisons, emergency departments in hospitals, farmworker camps—wherever the need was greatest.
For Day One Relief and its partner NGOs, toughest challenge, however, might be coming up. COVID-19 is surging in the South. And this year’s hurricane season, which started in June and continues through November, is predicted to be harsher than usual. How do you not only keep people safe after their homes have been destroyed, but also keep them socially distant? And how do you keep your volunteers safe when they enter coronavirus hotspots?
Fatalities and injuries from natural disasters can be reduced if the disaster can be predicted and advance warning given to people in the danger zone. In recent times, technology has been employed to fast track disaster relief efforts.Awareness, education, preparedness, and prediction and warning systems can reduce the disruptive impacts of a natural disaster on communities.
A web based dashboard which show all data points, forecasts, power outages - everything is in one place, constantly updating, so that decisions can be made faster and smarter. Other disaster relief groups can customize this platform to better understand their respective geographical regions by tracking weather patterns, COVID-19 cases and locations of the poorest, most vulnerable people, as well as sites of hospitals, airports, private airstrips and warehouses.
- IBM Cloud for Web-App Deploy
- IBM Cloud PAK For Data
- Watson Studio - Jupyter Notebook for data extraction, cleansing and prediction analysis
- Auto-AI for analyzing weather forecast data and generating candidate machine learning models
- The Weather Company (TWC) Apis for Storm/Hurricane Forecasts
- A Interactive Web Based Dashboard of North Carolina
- Jupyter Notebook based prediction - Predict which NC counties will be most at risk from a Hurricane or Tropical Storm
Success of disaster preparedness in sometime depends more on effective local response. With that in mind, we created a State/County Dashboard For North Carolina. User can select a county, and- the dashboard will be customized for that selection. State view will have the ability to select all alerts for the state, points of interest, and various indexes by county. County view will provide all indexes and alerts, as well as relevant information like population and population density. In addition, users can select venues such as parks and schools.
Currently we have only North Carolina and its counties enabled but we are in the process of adding other states, starting with Florida, Texas.
In the Situational awareness you can see SVI. Social vulnerability refers to the potential negative effects on communities caused by external stresses on human health. Such stresses include natural or human-caused disasters, or disease outbreaks. Reducing social vulnerability can decrease both human suffering and economic loss. The CDC/ATSDR Social Vulnerability Index (CDC/ATSDR SVI) uses 15 U.S. census variables to help local officials identify communities that may need support before, during, or after disasters
FEMA calculated NRI - The National Risk Index to help illustrate the nation’s communities most at risk of natural hazards. It is made possible through a collaboration between FEMA and dozens of partners in academia; local, state and federal government; and private industry. The Index leverages best available source data to provide a holistic view of community-level risk nationwide by combining multiple hazards with socioeconomic and built environment factors. It calculates a baseline relative risk measurement for each United States county and census tract for 18 natural hazards, based on Expected Annual Loss, Social Vulnerability, and Community Resilience. We are also showing flood index calculated by FEMA based on historic flood loss in that region.
The dashboard also shows shows a heatmap of current Covid Numbers by county, and the percentage of eligible population fully vaccinated - data provided by CDC.
When it comes to Flooding due to heavy rains or storms, elevation of the location plays a major role, so we are also showing elevation data for North Carolina provided by USGS,
And Critical locations, Venues and current temperatures & daily forecast for top cities for each county.
In the IBM Cloud Pak for Data - IBM Watson Studio, you can create Python, Scala, and R notebooks to analyze your data.Jupyter notebooks provide an interactive computational environment for developing Python based Data Science applications. Jupyter notebooks can illustrate the analysis process step by step by arranging the stuff like code, images, text, output etc. in a step by step manner. We are using Watson Studio Jupyter Notebook for predicting which NC counties will be most at risk from a Hurricane or Tropical Storm.
With all the data and indexes available , we can calculate which areas will need more attention in case of a hurricane, We are doing this for a Zip code level, North Carolina has 802 zip codes, based on SVI, NRI, Population and the elevation data, we can calculated the most vulnerable areas. Next based on 15 day Forecast from National Weather Service and National Hurricane Service, we can calculate the areas that will need more focus. Finally, if any ot the areas is facing power outages, we can highlight that.
For this project, we are using data from many datasources, in different formats like csv, json etc. To generate high-quality analysis we need to ensure that we are cleaning data in order to accurately represent the dataset. Pandas offer a diverse range of built-in functions that can be used to clean and manipulate datasets prior to analysis. It can allow you to drop incomplete rows and columns, fill missing values and improve the readability of the dataset through category renaming.
Foursquare API provides a range of tools for developers to incorporate the up-to-date location data to enhance their projects. The Places API offers real-time access to Foursquare’s global database of rich venue data and user content to power location-based experiences in app. In this project, we are using the Places API for extracting venues like Parks, Schools, Churches in North Carolina.
Python Web scraping is a technique to automatically access and extract large amounts of information from a website. In this project, we are using web scraping to extract power outage information for North Carolina
Our state dashboard consolidates thousands of static data sets with multi-level dynamic risk analysis onto an easily digestible dashboard that disaster response leaders can use to prioritize the most vulnerable during relief efforts.
Moving forward: With IBM’s powerful cognitive computing technology, we aim to utilize Watson’s machine learning capabilities to generate a single composite metric of risk based on the numerous variables specific to each zone on the state dashboard–counties or zip codes in the future. Then, at the time of a risk event, Watson’s algorithm will provide the user with a score for each zone, highlighting those areas which are most at risk, and allowing users to spend precious hours on directing relief efforts rather than losing time on complex risk assessment done manually.
We intend to allow easy integration of new data so that stakeholders may prioritize hazards or distribution points most crucial to them. For example, concentrated animal feeding operations, or hog farms, which are ubiquitous in North Carolina, can become severe risks during flood events when tons of manure and wastewater are discharged into clean water sources. The EPA provides data and locations for the whole state and once these data sets are loaded, Watson could tell us which zones are likely to face contamination of drinking water, often a major issue in the aftermath of heavy storms.
With enough data, Watson should be able to produce a more accurate index of social vulnerability than is displayed by either the CDC’s SVI or FEMA’s NRI, due to the thoroughness and speed by which risk assessment may be calculated algorithmically.
IBM® Eclipse Tools for Bluemix® provides plug-ins that can be installed into an existing Eclipse environment to assist in integrating the developer's integrated development environment (IDE) with Bluemix.
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Download and install IBM Eclipse Tools for Bluemix.
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Import this app into Eclipse using
File->Import->git import->clone urloption. -
Create a Liberty server definition:
- In the
Serversview right-click ->New->Server - Select
IBM->WebSphere Application Server Liberty - Choose
Install from an archive or a repository - Enter a destination path (/Users/username/liberty)
- Choose
WAS Liberty with Java EE 7 Web Profile - Continue the wizard with default options to Finish
- Run your application locally on Liberty:
- Right click on the
stateoriand selectRun As->Run on Serveroption - Find and select the localhost Liberty server and press
Finish - In a few seconds, your application should be running at http://localhost:9080/stateori/
- Create a Bluemix server definition:
- In the
Serversview, right-click ->New->Server - Select
IBM->IBM Bluemixand follow the steps in the wizard.\ - Enter your credentials and click
Next - Select your
organdspaceand clickFinish
- Run your application on Bluemix:
- Right click on the application and select
Run As->Run on Serveroption - Find and select the
IBM Bluemixand pressFinish - A wizard will guide you with the deployment options. Be sure to choose a unique
Namefor your application - In a few minutes, your application should be running at the URL you chose.
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To deploy the application on IBM Cloud:
- Jil Christensen
- Nikita Nangia
- Zachary Haugan
- Isshaan Oren Pilant
This project is licensed under the Apache 2 License - see the LICENSE file for details.
- Based on Billie Thompson's README template.
- How to create and deploy a simple webapp on IBM Cloud.