Apophis

Istanbul | Warning: Things are heating up!

HRT (Heat Risk Tracker)

High-Level Project Summary

Earth's climate has changed by natural causes throughout history. But we have been experiencing an unusual increase in the Earth's temperature mainly due to human activity. With the Industrial Revolution, the average surface temperature has risen about 1.18°C (2.12°F) since the late 19th century. Based on credible emission scenarios, average surface temperatures could rise between 2°C and 6°C by the end of the 21st century. The results of the rising heat create various risks for human health and the ecosystem. To minimize the potential damage and enhance life quality, we developed an app that predicts the possible effects of the increasing heat and notifies the user of vital precautions.

Link to Project "Demo"

https://www.youtube.com/watch?v=TzUhW8Ywodg

Link to Final Project

https://github.com/SelcukOz05/HRT_spaceapps

Detailed Project Description

How We Prepared For This Challenge:

The preparation process for this project was divided into two main parts ...

Health effects:

Started by analyzing the effects of heat and humidity changes on human health. Found specific humidity and temperature ranges that are risky for certain health issues such as heat stroke, heat exhaustion, and other heat-related diseases and other conditions heat might exacerbate (heart disease, asthma) from official resources. Then we used a system that calculates the heat index by combining the humidity levels and temperature and ranks them from normal to extreme. By combining the data we found on the risky temperature rages with the heat index levels we came up with a measuring scale on possible heat-related health issues.

2. Environmental effects:

Rising temperatures also have a crucial impact on the environment. By studying the effects of climate on forest fires we figured that the combination of low humidity and high temperatures rise the possibility of a fire starting. We also found that as the world warms wildfires are burning longer and more often in some latitudes.Then combining that information with the regional forest densit, we are able to estimate the probability of a forest fire.

WHAT EXACTLY DOES IT DO? / HOW DOES IT WORK?

With the real-time data received from an API (OpenWeather) about the temperature and humidity levels of individual locations, we are able to collect relevant data. By applying listing methods to the received data through Python we generate four different functions to work for the app. The first function combines the temperature and humidity levels to calculate the heat index. The second function takes the heat index and classifies it into four parts (normal, moderate, high, extreme) to form a useful scale. The third function matches several heat-related health issues according to what temperatures may pose as a risk. Lastly, the fourth function adds forest density to the equation and determines the probability of a wildfire.

HRT gathers the entire data that was generated from its multiple functions to create a data frame using Pandas library on Python. Then, that data frame gets processed and categorized through GUI. Putting the new categories into work the app forms a color-based geographic map to showcase the information in an easily understandable form.The last part of our project contains manual demand from the user. Once the user chooses the specific state they are in, the relevant data is portrayed in a pop-up form. This way allows the user to understand the information in a fast and clear way.

Benefits and our goals:

First and foremost, with our project HRT, we try to enhance human life quality under unusual conditions by enlightening the public about the effects of global warming. The app informs the user of required precautions according to humidity levels, temperature, and user's location. With the continuous data, we receive from API, our app can update each state's statistics on real time which makes the information it offers more reliable and relevant to the user. Preventing any harm done to the ecosystem and wildlife is also one of our most essential aims. The information provided by HRT can be used to notify related authorities of any possibility of a wildfire they might be facing. So, they will be prepared for every outcome. The public and the authorities will be well aware of the kinds of risks they are facing. Therefore, the community will act more responsibly to avoid causing any harm. In sum, we aspired to create a safe and reliable information source available to the public to spread as much beneficial knowledge as possible because we believe that spreading credible information among people on global issues is the first step to preventing them.

TOOLS- CODING LANGUAGES- LIBRARIES-API USED TO DEVELOP:

Python
Tkinter
Pandas
Pillow
CEFPYTHON
OpenStreetMap
OpenWeatherMap
Requests

Space Agency Data

Used to compare forest density data and heat changes:

https://climate.nasa.gov/news/3095/nasas-airs-tracks-record-breaking-heat-wave-in-pacific-northwest/.

Used to determine a connection between fires and global warming:

https://earthobservatory.nasa.gov/images/148789/climate-change-pushes-fires-to-higher-ground

https://earthobservatory.nasa.gov/global-maps/MOD_LSTAD_M

https://earthobservatory.nasa.gov/global-maps/MOD14A1_M_FIRE

-Used to get a definition for global warming and data on rising temperatures:

https://earthobservatory.nasa.gov/world-of-change/global-temperatures

Hackathon Journey

It has been a notable experience that helped us improve ourselves in various aspects. We learned how to act fast and efficiently under pressure. Although it was hard at times, we tried to gain as much knowledge from each other and our mentors as possible. We chose this challenge because we wanted to bring awareness to the effects of rising temperatures on human life and the importance of taking the required precautions, and we experienced a series of extreme wildfire in our own country as well. We thought our ideas might have positive outcomes for feature generations. But, due to the nature of our project, we had to collect a lot of data and find an efficient way to sort them. That was the main obstacle on our way. So, we made an effective plan and distributed the workload according to each member's unique strengths. Thanks to working together we managed to get our work done in time and created an open environment for learning while also having fun. Firstly our team would like to thank our school administration for providing a pleasant atmosphere for working then we'd like to thank the NASA Space Apps Team for giving us this opportunity to participate in the challenges.