Natural Disasters are problems in Japan, with risk of earthquakes, floods and tsunamis. Japan has well-developed disaster response systems, but densely populated cities and narrow roads make managing the response difficult. By giving individuals information about the safest ways from their homes and places of work, it will increase their awareness of the surrounding area and improve their preparedness.
Challenge hosted by Omdena - Japan Chapter
Omdena Japan Chapter Challenge Original Repo : https://github.com/OmdenaAI/omdena-japan-finding-paths-to-safety-following-natural-disasters
Final Presentation Link : https://docs.google.com/presentation/d/1QXsRvVFebxiqTap7XVmtLy226pMNWzFn/edit?usp=sharing&ouid=101910884647262199554&rtpof=true&sd=true
Japan Safest Path Google Drive Path : https://drive.google.com/drive/folders/1ad9nzMFXG22QrsqpAWb79-MRedfFi-GS
Japan Safest Path Dashboard Streamlit App : https://share.streamlit.io/prathimacode-hub/nakagawa--safest_path_during_earthquakes/main/app.py
You can find all the pickle files here
• collect satellite images and identify road characteristics
• build a model for scoring the roads in terms of their suitability for use in emergency
• build a pathfinding model from A to B, combining it with road characteristics
• suggest safest path from A to B
• publish interactive dashboards to display road characteristics and safest paths
• arrange demonstration and publicise to local audiences
We had choosen "Nakagawa-Ku as our region of interest, which comes under Aichi prefecture of Nagoya City. It comes under Chubu region and is the 4th densely populated city in Japan with high risk prone to disasters.
• We had designed a model collecting data about the local roads from satellite images, classify them and indicate the safest route to be taken from point A to point B and an interactive dashboard to display the safest route in a map.
• By making individuals aware, it will improve their preparedness and it can be used within families to prepare disaster response plans, depending on their circumstances. To be used by individuals, families and groups, and foreign residents who may not understand local information. Further development will be covering more geographical areas and publicising on a local level.
• Safest route path to take at occurences of disaster conditions at Nakagawa
• Locates shelters in Nakagawa Ward - Earthquakes, Tsunamis and Floods
• Visualizations to Check and Differentiate Parameters across the Nakagawa Ward
• Data Gathering - Shelter Details, Latitude, Longitude, Ward Type.
• Data Preparation - Merging all the Details, Configuring, Evaluating and Converting it into Readable Format.
• Risk Classification - Japan Earthquake Zoning Areas, Nakagawa Evacuation Shelters, Risk Factors of Earthquake and Building Density.
• Path Finding Algorithms - Python, Jupyter Notebook (Earthquake Risk Score, Building Density Risk Score, Distance Risk Score and Combined Risk Score).
• Dashboard - Streamlit.
• Gathering the data about the Shelters (Earthquake, Tsunami and Flood) on Nakagawa Ward with various parameters needed to calculate risk factor and safest path. • Preparing and pre-processing the data for it to read and determine the risk classification and path finding appropriately. • Check up, configure and evaluate with the risk factors based on distance, building density and earthquake considerations. • Devising the safest path using algorithms that gives out the best possible route to take up during emergencies. • Deploying Safest Path Integrated Web App on Streamlit.
An Interactive WebApp to devise safest path in Nakagawa-Ku region, Japan during natural disasters like Earthquakes, Tsunamis and Floods that helps in prioritizing the citizen's safety in risk prone zones.
Avinash Mahech, Prathima Kadari, Armielyn Obinguar, Deepali Bidwai, Shalini GJ, Rhey Ann Magcalas, Pawan Roy Choudhury, Ahmed Gaal, Monika Manolova
Galina Naydenova