“The European summer of 2003 was unusually hot. The prolonged and intense heat killed Between 22,000 and 35,000 people, particularly elderly individuals, and caused economic losses of over USD 13 billion.” - (IFRC, 2004)

News articles like these strike a chord with people living in areas prone to frequent disasters. Above is an example of such natural calamity, a heatwave. Heatwaves only become a large-scale calamity due to the lack of early warning. In fact, the best way to decrease the damage of heatwaves is to give an early warning, giving time for proper preparations. Heatwaves can be predicted at least three days in advance, and societies must be ready to read that signal and take action. The problem lies due to the lack of a system to properly interact with the weather forecasting institute and the general public—based on the effects of the weather rather than plain meteorological statistics—clear channels of communication, well-designed plans to follow once such a warning is issued, and the availability of human and physical resources to mitigate the heat wave’s effects, particularly on the most vulnerable groups in society.

Therefore the idea of making a platform that could not only show the variations in climate data but also predict disasters based on certain parameters was born. We also wanted to accelerate the growth of renewable sources of energy by suggesting a source of renewable energy to the user based on their exact location, cutting down all the hassle.

What it does

After the log-in, the program asks the user for their location. The program uses that location to find the climate conditions and based on them, displays three things: climate prediction till 5 days in the future in the form of graphs, possibility of any disaster, compatible renewable energy sources in the area.

The program is created to make people more climate secure and climate aware.

How we built it

Our code is solely based on the Python programming language, also using the MySQL.connector module. We have made use of the OpenWeatherMap API for our location-specific information. The code in itself has a simple logic, using conditional statements that are easily modifiable as we go on improving the complexity of the project.

The program initially started as a school project, but our team decided to modify it to make it of practical use. The team consists of a pair of high school students, and we are very excited to share and improve this application.

Challenges we ran into

For a group of high schoolers, to say that this project was new would be an understatement. It was our first time working with an API, and it took time to utilize and make the huge amount of data usable for the program.

Due to the logical and time constraints, we were not able to include a lot of functions in the product, but we were able to make an MVP on our core concepts.

Accomplishments that we're proud of

We are proud of the final product we were able to build, and the fact that we have a lot of ideas pilling up that can improve it further. It was a journey that taught us more than we could imagine. The experiments with APIs and Tkinter formatting helped us improve our programming skills and logic of how to approach problem solutions.

What's next for Klimacc: One Click to Sustainability

Our project has just started, and this is nothing but a Minimum Viable Product. We are working to enable people to record videos or pictures during disaster conditions and share them on social networks automatically to raise awareness. We also aim to improve our climate display system in such a way that we can show pinpoint causation of particular weather in one place due to particular conditions in another.

For example, Punjab (India) is known for stubble burning during the end of the harvest season, and that causes a spike in pollution in other areas of Nothern India. We plan to be able to show this information in a simple way such that our consumers can understand how they impact the environment around themselves

In our current project, we have linked renewable energy sources to just informative sites. But we are working towards making a program that could direct the users to manufacturers/sellers based on which model would suit them the best.

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