# **Rescue Bee -- Quick Response and Rescue System**
>Your challenge is to use this data to enable local stakeholders to develop more sustainable, disaster-risk resilient, and inclusive urban plans.
## Rescue Bee
### Motivation
* When disaster occurs, aside from the danger caused, push and trample among the crowd result in casualties as well. Therefore, the dynamic evacuation is necessary.
* With mobility of drones and area data offered by satellites, our team intend to achieve the goal of sdgs 11.3, hoping to improve living safety through the dynamic evacuation plan.
### How does our project works?
* When a disaster happens, our system can minimize casualties.
* After people send rescue signals, we will fetch data from NASA satellites API.
* In the meantime, we will deploy drones and plan evacuation routes by analyzing images we just fetch.
* Our drones will guide people to the safest location and wait for authorized personnel to pick them up.
## Project

### Main idea
* We can get the location and what type of disaster from our users.
* We use drones to analyze and also use "NASA Earth API" as support for our project.
* Guide people to the safest place and wait for authorized personnel by our app and drones.
### Technique
* SLAM : updating a map of an unknown environment
* NASA Earth API : fetch area data
### Background Information : about SLAM
Through are member's tests, we can find out how "SLAM" works
## Slides
* https://docs.google.com/presentation/d/1p3uJmiCjLfVlCaC03h5MRykGaKYz3z0NcOxbztcaVnc/edit?usp=sharing
## app Prototype
https://www.figma.com/file/iLdiBPsCUs05h7COjXNYf9/Untitled-Copy?node-id=0%3A1
## Referenced Resource
* NASA EARTH API :https://api.nasa.gov/
* SDGS : https://sdgs.un.org/goals
* SLAM : https://en.wikipedia.org/wiki/Simultaneous_localization_and_mapping
* THE CAUSES AND PREVENTION OF CROWD DISASTERS:https://www.workingwithcrowds.com/wp-content/uploads/2018/02/THE-CAUSES-AND-PREVENTION-OF-CROWD-DISASTERS-by-John-J.-Fruin-Ph.D.-P.E..pdf
### Image Referenced
* https://www.pexels.com/video/a-burning-apartment-4116863/
* https://www.pexels.com/zh-tw/video/3764259/
* https://www.pexels.com/zh-tw/video/8943939/
## Team : Coding 365

### Team Members
consultant 賴桑
NTHU Chan Chin-Chun
NTUT Wu keng-young
NTUT LU WEI-REN
NCCU Lin Ye-Hsiang
NCTU Chen Yuan-Hao