“We built Air Triage at #hack4good 0.5 London and won 2nd Place”

Team: James O’Halloran Rob Finean Olivia Comberti Andrew Curtis Jon Somerscales Florian Rathgeber

Date: 7 – 9 Feb 2014 Location: London NGO: MSF NGO lead: Ivan Gayton Geeklist: http://bit.ly/1bELjpA

Summary A team of 6 formed at the Global #Hack4Good 0.5 in London. We created the following. Background / Problem When organisations like Médecins Sans Frontières and other NGO's arrive in a country that needs humanitarian aid it is chaos! Teams of people in their hundreds arrive with thousands of tonnes of supplies to distribute but the problem is knowing which areas are high priority; areas that have no clean drinking water for example need to be quickly identified. Narrative The images that follow are an example of what the NGO’s see when they arrive

Narrative As you can see, chaos! BUT is this the worst affected area? What about these places…

Narrative Often the best approach is to hire a helicopter and fly over in order to assess.

Narrative But as you can imagine helicopters are not always available and if they are they take time to arrange and it is not an ideal use of a resource that could be dropping aid. A brilliant inexpensive solution is to fly an unmanned micro helicopter aka drone with a camera to capture aerial photographs and a tiny computer to capture coordinate data about where these pictures are being taken. This equipment, costing less than £400, is ultra-portable and has the power to provide mission critical data.

Narrative These budget devices have already been trialled successfully however the photographs and the coordinate-file need to be manually cross referenced to understand where the picture was taken and then manually transcribed onto a map. A drone can reach a distance of 20 kilometres before the battery needs to be charged. We created an application which allows the operator to rapidly review the pictures and then automatically pinpoint them on a map. The field user can also add notes in order to triage the situation and therefore rapidly identify the high priority areas. Web app completed using: Django, Python, GoPro, KML inputs, HTML, CSS, Javascript and OpenStreetMap

Live Demo!

Functionality Rapidly flick through the drone-taken images. The precise location (that the photo was taken) is pinpointed on the map. Depending on the image content the user can mark the map eg “No Drinking water” and therefore triage the surrounding area to ascertain where the high priority location is. You can use keystrokes to rapidly mark-up the area. This app is fully functional and would be deployed on a field laptop, therefore not requiring a connection

Narrative The following wireframes show the next steps for development. We estimate that we can complete this functionality within a day.

Narrative The trace of the drone flight is marked on the map so that you can quickly see what area the pictures were taken. You can click on the map to see the associated image.

Narrative If you press 1 “Area has no drinking water” on the keyboard a marker is placed on the map

Narrative You can mark more than one priority on the map and add a note

Narrative If you hover over a dot on the map you can see a pop-up of the needs required in this area

Narrative The next step for development: To create a new map of the images, see the following slides as an example

NEXT STEPS The previous slides show a new map of the area stitched together laboriously weeks after the disaster (Typhoon Haiyan, Philippians). This would have taken 2 to 3 days. The process is: look at each image and try to figure out where it is on the map. The process is aided by software but is still a time consuming and human solution. We want to automate this. The team are psyched to continue this project which has a wider benefit too: A local in Congo, an area that doesn’t currently have a reliable map whatsoever could build a drone with a camera and Arduino for £400 . This individual could then fly it around the area and use the software we want to create to map the area. A reliable map is something we take for granted in the West but there are many places that are not mapped or in the case of Typhoon Haiyan places change. There is currently no available software to map an area using aerial images from a drone or helicopter! We wish to create a freely and widely available solution.