Author: Timo Luege

Drones are one of the most controversial technologies in disaster response operations. To find out what exactly humanitarian aid workers think about the use of these unmanned aerial vehicles (UAV), the Swiss Foundation for Mine Action (FSD) with funding from EU Humanitarian Aid has now published a survey. In total, close to 200 disaster responders working in 61 different countries took part in what is the first comprehensive survey of how humanitarian professional view drones.

The survey shows that a substantial majority of respondents (60%) believe that drones can have a positive impact in disaster response operations, while only less than a quarter (22%) see their use negatively – at least when used following natural disasters. The opinions shift significantly, when asking about use of drones in conflict zones. Here, humanitarian workers are sharply split: while 40% stated that drones should never be used by humanitarian organisations in conflict settings, 41% said they would consider using drones even during armed conflicts.

Interestingly, a majority (57%) said that they believe that the local populations feel threatened by drones – even in non-conflict environments. However, this perception is not backed up with the experience that FSD has gathered as part of the EU Humanitarian Aid funded initiative “Fostering the Appropriate Use of Air-Borne Systems in Humanitarian Crisis” so far. As part of that initiative, FSD, in partnership with the Zoi Environment Network and CartONG, is currently collecting 16 case studies ranging from mapping, to de-mining to transporting medical samples. Nine of these case studies have already been published and can be found here.

Most survey respondents saw a very real potential for drones to assist in humanitarian response operations, particularly in situations where drones can be used to create maps, monitor activities, support search and rescue operations or deliver cargo. However, humanitarian workers also stressed that drones need to be able to provide a real added value compared to existing technologies.

drones-in-humanitarian-action-survey-infographic3_800_2400_web

The survey also showed that much more needs to be done within the humanitarian sector to build knowledge about the advantages, disadvantages, capabilities and limitations of drones. The vast majority (87%) of respondents said that they did not have first-hand knowledge of using drones. Many of them explained that they were looking for guidance and needed experience to make the best use of the technology.

As drones become more affordable and widespread, there is no question that UAVs will become more and more common in disaster zones. The results of this survey show that more needs to be done to better understand the added value of drones and to provide humanitarian organisations with practical guidance on how and where drones should be used.

Key figures of the survey are summarised in the infographic below. The complete survey can be downloaded here.

This piece originally appears on the FSD Blog. All images courtesy of FSD.

 

When I hear the term “artificial intelligence”, my first thoughts go to HAL9000 and Data from Star Trek before settling on some vague notion about the Turing test. Clearly I’m not a computer scientist.

While reading Patrick Meier’s book, I realized that I had missed out on a wide range of advances in the field of machine learning, some of which also fall under “artificial intelligence”, which can help us make sense of the onslaught of information that we are faced with whenever a disaster strikes.

When the crowd gets overwhelmed

While nothing can beat the collective intelligence of a sufficiently large group of people that focus their energy on processing a lot of data, the problem with this type of crowdsourcing is that you need a very large group of people – and volunteers are a scarce resource.

Projects like Artificial Intelligence for Disaster Response (AIDR) from the Qatar Computing Research Institute (QCRI) are striving to make better use of the volunteer’s time. To do this, the AIDR algorithm is basically looking over the volunteers’ shoulders while they are processing a small amount of data. The machine learns from every decision, until it understands the patterns well enough to process the data itself. Datasets it is unsure about are returned to the volunteers for review and their decisions then improve the algorithm further. According to QCRI, the algorithm frequently reaches confidence levels of over 80 per cent, meaning that huge amounts of data can be analysed in a fraction of the time it would take volunteers.

You can test AIDR for free one the project’s website. If you want to know more, take a look at the video below.

Image analysis

The EU’s Joint Research Centre (JRC) as well DigitalGlobe, a company that provides satellite imagery and analysis, go even further: they are training their algorithms to interpret images. The JRC algorithm for example is already able to detect rubble for damage assessments in a city after an earthquake with up to 92% confidence, while DigitalGlobe is asking the crowd to teach its software how to recognize buildings on satellite photos. That information will no doubt be used to improve the company’s commercial products, but it is also being used to help fight malaria in Swaziland by providing aid organizations with a better idea of population density. This in turn can help program managers make decisions about where to commit the most resources.

You can support the malaria project through DigitalGlobe’s Tomnod platform here.

Another example, where this type of automatic population density data would have been useful, is the Ebola response, where population data had to be estimated manually, based on houses that first had to be mapped by OpenStreetMap volunteers. An algorithm that can automatically identify homes would have been much faster.

What I find amazing is that these tools are already working and available today. And while there are definitely still ways to improve them and bugs to work out, they make me very optimistic for the very near future of information management and needs assessment in disaster response.

What do you think about the role of artificial intelligence in disaster response? Comment below or tweet at us @TechChange. This post originally appeared on Social Media 4 Good.

If you are interested in learning about technologies like artificial intelligence that are helping in disaster response, join us in our upcoming online course “Technology for Disaster Response” which starts on 22 June.

About author

Timo Luege

Timo Luege, TC103: Technology for Disaster Response Facilitator

After nearly ten years of working as a journalist (online, print and radio), Timo worked four years as a Senior Communications Officer for the International Federation of Red Cross and Red Crescent Societies (IFRC) in Geneva and Haiti. During this time, he also launched the IFRC’s social media activities and wrote the IFRC social media staff guidelines. He then worked as Protection Delegate for International Committee of the Red Cross (ICRC) in Liberia before starting to work as a consultant. His clients include UN agencies and NGOs. Among other things, he wrote the UNICEF “Social Media in Emergency Guidelines” and contributed to UNOCHA’s “Humanitarianism in the Network Age”. Over the last year, Timo advised UNHCR- and IFRC-led Shelter Clusters in Myanmar, Mali and most recently the Philippines on Communication and Advocacy. He blogs at Social Media for Good.

Did you see Facebook’s Safety Check feature recently? Did you use it?

Following the recent earthquake in Nepal, Facebook activated “Safety Check“, a feature that helps friends and relatives quickly find out whether their loved ones are safe. Safety Check was originally launched in October 2014 and was mainly based on experiences gained during the 2011 earthquake and Tsunami in Japan.

The idea is very simple: In case of a large scale emergency, Facebook can use the information it is constantly collecting about its users to determine who is likely to be in the affected area. It then asks these users to confirm whether they are safe and shares that information with their facebook friends. Alternatively, people can also report their facebook friends as being safe and those marked safe can see who marked them. People can also say “I’m not in the area”.

Safety Check is a dormant Facebook feature that is only activated when necessary. One thing that I had been curious about since the launch was how well Facebook would be able to determine whether someone was in the affected area.

According to the original press release:
“We’ll determine your location by looking at the city you have listed in your profile, your last location if you’ve opted in to the Nearby Friends product, and the city where you are using the internet.”

Indeed I quickly heard from two former colleagues who were in Nepal: One of them lives permanently in Kathmandu but was actually on a plane when the earthquake happened. In his case, Facebook assumed he was still in Nepal, because his phone was off at the time of the quake. In the absence of current information, Facebook took his home city and/or his last location, which was at the airport, to include him in the group of affected people.
The other person I know normally lives in the UK but was in Nepal on a trip. In his case, Facebook used the IP address of his last login to estimate his location.


Users see how many of their Facebook friends are
in the affected area and how many are safe.

Why this is relevant
Anyone who has ever been in a situation where family members or close friends are in danger, knows that finding out what happened to them is one of the first things on your mind. Not knowing is not only a source of great anxiety, but it can actually be dangerous if you yourself are also close to the affected area:

Think of a father who knows that his daughter was at a shopping mall downtown when the earthquake struck. If he doesn’t know what happened to his child, he will probably run to the shopping mall to find out. By doing so he can put himself at risk and he will not be at home to look after the other children when a strong aftershock occurs. He will also try to call his daughter every 5 seconds, thereby accidentally helping to crash the phone network.

On the other hand, we have now seen in a number of disasters that internet connections frequently remain functional (if slow) even when phone and SMS networks are down – to a large part because many people open their WiFi networks to let others use the internet.
Using social media is also much more efficient since one “I am safe” update will reach all of one’s friends, making multiple calls unnecessary, thus reducing further load on the telecommunications infrastructure.

facebook safety check blogpost photo 2
The application also shows clearly whether people have
reported themselves as safe or whether others have done so for them. 

Why this is better
Of course, there are also other systems to find out whether friends and family are safe. Google, for example, has its “Person Finder“. The Red Cross Red Crescent Movement has been providing tracing and restoring family links services for many years and local government authorities, as well as embassies, are also very much involved in these tasks.

However all of them require that a (distressed) user finds out about these services and actively registers or gets in touch with them. That is a lot to ask of someone who just survived a disaster. Facebook’s Safety Check on the other hand is part of the normal Facebook application that most people are already familiar with. This reduces the barrier to share and receive information significantly which in turn reduces the load on the other, more sophisticated, systems like the Red Cross’ tracing program. Facebook’s Safety Check can provide clarity in many of the easy cases, freeing up resources for the difficult ones.

What do you think about Facebook’s Safety Check? Let us know by commenting below or tweeting at us @TechChange. This post originally appeared on Social Media 4 Good

Interested in learning about other ways technology is being used in disaster response? Join us in our upcoming online course on Technology for Disaster Response that begins on June 22.

About author

Timo Luege
Timo Luege, TC103: Technology for Disaster Response Facilitator

After nearly ten years of working as a journalist (online, print and radio), Timo worked four years as a Senior Communications Officer for the International Federation of Red Cross and Red Crescent Societies (IFRC) in Geneva and Haiti. During this time, he also launched the IFRC’s social media activities and wrote the IFRC social media staff guidelines. He then worked as Protection Delegate for International Committee of the Red Cross (ICRC) in Liberia before starting to work as a consultant. His clients include UN agencies and NGOs. Among other things, he wrote the UNICEF “Social Media in Emergency Guidelines” and contributed to UNOCHA’s “Humanitarianism in the Network Age”. Over the last year, Timo advised UNHCR- and IFRC-led Shelter Clusters in Myanmar, Mali and most recently the Philippines on Communication and Advocacy. He blogs at Social Media for Good.