ANTICALAMITY

Prediction of Calamity Using Bar Charts and AI
Donation and Get Involved Page for Community Service
Impact of the Natural Disaster and Scale Analysis
Natural Calamity Prediction Website Page using ML & AI
Using MageAi for running past database of Calamities to predict future ones

💡Inspiration💡

According to a survey, a total of 98.9667million people were affected by natural disasters globally in 2020, of whom 45.95% were affected by storms, reaching 45.4708 million people, accounting for the largest proportion of the total; 33.56% by floods, reaching 33.2156 million people

People especially living in remote locations prone to natural disasters live their life in fear of leaving everything of sudden and rushing without any financial aid.

❓What it does❓

The purpose of Anti-Calamity is to watch and analyse the ground situations of the earth using satellite imagery for different sustainable aspects and predict the future situations of the earth via utilising machine learning tools. The application's main benefit is to broaden the horizon of people across all ages and demographics, industries and government authorities so appropriate actions are/could be taken.

🏗️How we built it🏗️

We use HTML/CSS/JS to build the application and along with it, we use MageAI to train the dataset models and implement them.

🚧Challenges we ran into🚧

We had problem working on collecting the datasets to train the model since some of them were biased towards one of the calamities and we had to work on it to provide as accurate results as we can.

🏅🏆ACCOMPLISHMENTS THAT WE ARE PROUD OF🏅🏆

We are proud of the final project we built. We learned a lot while working on the project not just technically but also in time management. We are proud we could complete the project and deliver a beautiful fully functional Hack this weekend.

⏱⌛⏳🏃‍♂️Time Management⏱⌛⏳🏃‍♂️

We had a tough time managing time this weekend with our participation in this Hackathon as we had to work on multiple things altogether. We lost a lot of hackathon time in brainstorming and team building yet we are proud that things went according to our plans. Fortunately, we could do this by distributing our work and focusing on multitasking. Extremely excited about all the learnings and teachings we got through this hack.

💭What's next for AntiCalamity💭

Further, development would be done for training models used to predict future “Critical Data-Map Index”, which forecasts future critical aspects of the environment at the local, regional and global levels. This would allow citizens, industry and governments to take appropriate action ahead of time while avoiding the serious environmental, societal and economical consequences.