Results: Evaluation of UAVs for Humanitarian Use

UAViators Logo

My team & I at the Humanitarian UAV Network (UAViators) have just completed the first phase of our evaluation and welcome feedback on the results. We have reviewed over 150 UAV models along with camera technologies, payload units as well as image processing and analysis software. Each of these items have been reviewed within the context of humanitarian applications and with humanitarian practitioners in mind as end-users.

The results of the evaluation are available here in the form of an open and editable Google spreadsheet. We are actively looking for feedback and very much welcome additional entries. So feel free to review & add more UAVs and related technologies directly to the spreadsheet. Our second phase will involve the scoring/weighing of the results to identity the UAVs, cameras and software that may be the best fit for humanitarian organizations.

In the meantime, big thanks to my research assistants who carried out all the research for this review.

bio

See Also:

  • Humanitarian UAV Network: Strategy for 2014-2015 [link]
  • Humanitarians in the Sky: Using UAVs for Disaster Response [link]
  • Humanitarian UAV Missions During Balkan Floods [link]
  • UAVs, Community Mapping & Disaster Risk Reduction in Haiti [link]
  • Crisis Map of UAV Videos for Disaster Response [link]
  • Check-List for Flying UAVs in Humanitarian Settings [link]

 

From Russia with Love: A Match.com for Disaster Response

I’ve been advocating for the development of a “Match.com” for disaster response since early 2010. Such a platform would serve to quickly match hyperlocal needs with relevant resources available at the local and national level, thus facilitating and accelerating self-organization following major disasters. Why advocate for a platform modeled after an online dating website? Because self-organized mutual-aid is an important driver of community resilience.

Russian Bell

Obviously, self-organization is not dependent on digital technology. The word Rynda, for example, is an old Russian word for a “village bell” which was used by local communities to self-organize during emergencies. Interestingly, Rynda became a popular meme on social media during fires in 2010. As my colleague Gregory Asmolov notes in his brilliant new study, a Russian blogger at the time of the fires “posted an emotional open letter to Prime Minister Putin, describing the lack of action by local authorities and emergency services.” In effect, the blogger demanded a “return to an old tradition of self-organization in local communities,” subsequently exclaiming “bring back the Rynda!” This demand grew into a popular meme symbolizing the catastrophic failure of the formal system’s response to the massive fires.

At the time, my colleagues Gregory, Alexey Sidorenko & Glafira Parinos launched the Help Map above in an effort to facilitate self-organization and mutual aid. But as Gregory notes in his new study, “The more people were willing to help, the more difficult it was to coordinate the assistance and to match resources with needs.” Moreover, the Help Map continued to receive reports on needs and offers-of-help after the fires had subsided. To be sure, reports of flooding soon found their way to the map, for example. Gregory, Alexey, Glarifa and team thus launched “Virtual Rynda: The Help Atlas” to facilitate self-help in response to a variety of situations beyond sudden-onset crises.

“We believed that in order to develop the capacity and resilience to respond to crisis situations we would have to develop the potential for mutual aid in everyday life. This would rely on an idea that emergency and everyday-life situations were interrelated. While people’s motivation to help one another is lower during non-emergency situations, if you facilitate mutual aid in everyday life and allow people to acquire skills in using Internet-based technologies to help one another or in asking for assistance, this will help to create an improved capacity to fulfill the potential of mutual aid the next time a disaster happens. [...] The idea was that ICTs could expand the range within which the tolling of the emergency bell could be heard. Everyone could ‘ring’ the ‘Virtual Rynda’ when they needed help, and communication networks would magnify the sound until it reached those who could come and help.”

In order to accelerate and scale the matching of needs & resources, Gregory and team (pictured below) sought to develop a matchmaking algorithm. Rynda would ask users to specify what the need was, where (geographically) the need was located and when (time-wise) the need was requested. “On the basis of this data, computer-based algorithms & human moderators could match offers with requests and optimize the process of resource allocation.” Rynda also included personal profiles, enabling volunteers “to develop an online reputation and increase trust between those needing help and those who could offer assistance. Every volunteer profile included not only personal information, but also a history of the individual’s previous activities within the platform.” To this end, in addition to “Help Requests” & “Help Offers,” Rynda also included an entry for “Help Provided” to close the feedback loop.

Asmolov1

As Gregory acknowledges, the results were mixed but certainly interesting and insightful. “Most of the messages [posted to the Rynda platform dealt] with requests for various types of social help, like clothing and medical equipment for children, homes for orphans, people with limited capabilities, or families in need. [...]. Some requests from environmental NGOs were related to the mobilization of volunteers to fight against deforestation or to fight wildfires. [...]. In another case, a volunteer who responded to a request on the platform helped to transport resources to a family with many children living far from a big city. [...]. Many requests concern[ed] children or disabled people. In one case, Rynda found a volunteer who helped a young woman leave her flat for walks, something she could not do alone. In some cases, the platform helped to provide medicine.” In any event, an analysis of the needs posted to Rynda suggests that “the most needed resource is not the thing itself, but the capacity to take it to the person who needs it. Transportation becomes a crucial resource, especially in a country as big as Russia.”

Alas, “Despite the efforts to create a tool that would automatically match a request with a potential help provider, the capacity of the algorithm to optimize the allocation of resources was very limited.” To this end, like the Help Map initiative, digital volunteers who served as social moderators remained pivotal to the Virtual Ryndal platform. As Alexey notes, “We’ve never even got to the point of the discussion of more complex models of matching.” Perhaps Rynda should have included more structured categories to enable more automated-matching since the volunteer match-makers are simply not scalable. “Despite the intention that the ‘matchmaking’ algorithm would support the efficient allocation of resources between those in need and those who could help, the success of the ‘matchmaking’ depended on the work of the moderators, whose resources were limited. As a result, a gap emerged between the broad issues that the project could address and the limited resources of volunteers.”

To this end, Gregory readily admits that “the initial definition of the project as a general mutual aid platform may have been too broad and unspecific.” I agree with this diagnostic. Take the online dating platform Match.com for example. Match.com’s sole focus is online dating; Airbnb’s sole purpose is to match those looking for a place to stay with those offering their places; Uber’s sole purpose is matching those who need to get somewhere with a local car service. To this end, matching platform for mutual-aid may indeed been too broad—at least to begin with. Amazon began with books, but later diversified.

In any case, as Gregory rightly notes, “The relatively limited success of Rynda didn’t mean the failure of the idea of mutual aid. What [...] Rynda demonstrates is the variety of challenges encountered along the way of the project’s implementation.” To be sure, “Every society or community has an inherent potential mutual aid structure that can be strengthened and empowered. This is more visible in emergency situations; however, major mutual aid capacity building is needed in everyday, non-emergency situations.” Thanks to Gregory and team, future digital matchmakers can draw on the above insights and Rynda’s open source code when designing their own mutual-aid and self-help platforms.

For me, one of the key take-aways is the need for a scalable matching platform. Match.com would not be possible if the matching were done primarily manually. Nor would Match.com work as well if the company sought to match interests beyond the romantic domain. So a future Match.com for mutual-aid would need to include automated matching and begin with a very specific matching domain. 

Bio

 

See also:

  • Using Waze, Uber, AirBnB, SeeClickFix for Disaster Response [link]
  • MatchApp: Next Generation Disaster Response App? [link]
  • A Marketplace for Crowdsourcing Crisis Response [link]

Common Misconceptions About Humanitarian UAVs

Superficial conversations on the challenges and opportunities of using UAVs in humanitarian settings reveal just how many misconceptions remain on the topic. This is admittedly due to the fact that humanitarian UAVs are a relatively recent innovation. There are of course legitimate and serious concerns around the use of UAVs in humanitarian settings. But superficial conversations tend to obfuscate intelligent discourse on what the potential solutions to these challenges might be.

SkyEyeGrassRoots

I would thus like to address some of the more common misconceptions in the hopes that we can move beyond the repetitive, superficial statements that have been surfacing in recent discussions on humanitarian UAVs. This will hopefully help improve the quality of discourse on the topic and encourage more informed conversations.

  • UAVs are expensive: Yes, military drones cost millions of dollars. But small, civilian UAVs range from a few hundred dollars to the price of a small car.  The fixed-wing UAV used by the International Organization for Migration (IOM) in Haiti and by Medair in the Philippines cost $20,000. Contrast this to UN Range Rovers that cost over $50,000. The rotary-wing UAV (quadcopter) purchased by the UN Office for the Coordination of Humanitarian (OCHA) costs $1,200 (the price of a laptop). The one pictured above now costs around $500. (And balloon mapping costs even less). Like other technologies, UAVs are clearly becoming cheaper every year, which is why they’re increasingly used in humanitarian settings.
  • UAVs are limited in range: So are cars. In other words, whether UAVs are “too limited” depends on what their intended use is. Small, fixed-wing UAVs have a flight time of about an hour while small rotary-wing UAVs typically remain airborne for half-an-hour (on 1 battery). Naturally, more expensive UAVs will have longer flight-times. For targeted damage assessments, current ranges are easily manageable with several batteries. With one team and a few batteries, IOM covered 45 square kilometers in 6 days of flying. As more groups use UAVs in humanitarian settings, the opportunities to collaborate on flight plans and data sharing will necessarily expand both range and coverage. Then again, if all I need is 25 minutes of flight-time to rapidly assess disaster damage in rural village, then a rotary-wing UAV is a perfect fit. And if I bring 5 batteries along, I’ll have more than two hours’ worth of very high-resolution imagery.
  • UAVs are dangerous: Cars cause well over 1 million deaths every year. There are safe ways to use cars and reckless ways, regardless of whether you have a license. The same holds true for UAVs: there are safety guidelines and best practices that need to be followed. Obviously, small, very light-weight UAVs pose far less physical danger than larger UAVs. Newer UAVs also include a number of important fail-safe mechanisms and automated flight-plan options, thus drastically reducing pilot error. There is of course the very real danger of UAVs colliding with piloted-aircraft. At the same time, I for one don’t see the point of flying small UAVs in urban areas with complex airspaces. I’m more interested in using UAVs in areas that have been overlooked or ignored by international relief efforts. These areas are typically rural and hard to access; they are not swarmed by search and rescue helicopters or military aircraft delivering aid. Besides as one UAV expert recently noted at a leading UAV conference, the best sense-and-avoid systems (when flying visual line-of-site) are your eyes and ears. Helicopters and military aircraft are loud and can be heard from miles away. If you or your spotter hear and/or see them, it takes you 10 seconds to drop to a safer altitude. In any event, flying UAVs near airports is pure idiocy. Risks (and idiocy) cannot be eliminated, but they can be managed. There are a number of protocols that provide guidance on the safe use of UAVs such as the Humanitarian UAV Network’s Code of Conduct and Operational Check-List available here. In sum, both education and awareness-raising are absolutely key.
  • UAVs are frightening: Compare the UAV pictured above with UN military helicopters and aircraft. What looks more scary? Talk to any UAV professional who actually has experience in flying small UAVs in developing countries and virtually all will tell you that their UAVs are almost always perceived as toys by both kids and adults alike. CartONG & OSM who use UAVs for community mapping note that UAVs in Haiti bring communities together. Meanwhile, SkyEye and partners in the Philippines use the excitement that UAVs provoke in kids to teach them about science,  maths and aeronautics. Do the kids in the picture above look scared to you? This doesn’t mean that process—reassurance, awareness raising & community engagement— isn’t important. It simply means that critics who play on fear to dismiss the use of UAVs following natural disasters don’t know what they’re talking about; but they’re great at “Smart Talk”.
  • UAVs are not making a difference: This final misconception is simply due to ignorance. Humanitarian UAVs are already a game-changer. Anyone who follows this space will know that UAVs have already made a difference in Haiti, Philippines and in the Balkans, for example. Their use in Search and Rescue efforts have already saved lives. As such, critics who question the added value of humanitarian UAVs don’t know what they’re talking about. Acquiring and analyzing satellite imagery after a disaster still takes between 48-72 hours. And if clouds are lingering after a major Typhoon, for example, then humanitarians have to wait several days longer. In any event, the resulting imagery is expensive and comes with a host of data-sharing restrictions. These limitations explain why disaster responders are turning to UAVs. This doesn’t mean that we don’t need more evidence of impact (and failure), we certainly do since this is still a new space. But suggesting that there is no evidence to begin with is precisely the kind of ignorance that gets in the way of intelligent discourse.

I hope we can move beyond the above misconceptions and discuss topics that are grounded in reality; like issues around legislation, coordination, data privacy and informed consent, for example. We’ll be focusing on these and several other critical issues at the upcoming “Experts Meeting on Humanitarian UAVs” co-organized by the UN Office for the Coordination of Humanitarian Affairs and the Humanitarian UAV Network (UAViators), which is being held in November at UN Headquarters in New York.

My advocacy around the use of humanitarian UAVs should obviously not be taken to suggest that UAVs are the answer to every and all humanitarian problems; UAVs, like other novel technologies used in humanitarian settings, obviously pose a number of risks and challenges that need to be managed. As always, the key is to accurately identify and describe the challenge first; and then to assess potential technology solutions and processes that are most appropriate—if any—while keeping in mind the corner stone principle of Do No Harm.

bio

  • Humanitarian UAV Network: Strategy for 2014-2015 [link]
  • Humanitarians in the Sky: Using UAVs for Disaster Response [link]
  • Humanitarian UAV Missions During Balkan Floods [link]
  • UAVs, Community Mapping & Disaster Risk Reduction in Haiti [link]
  • Crisis Map of UAV Videos for Disaster Response [link]
  • Using MicroMappers to Make Sense of UAV/Aerial Imagery During Disasters [link]

Live: Crowdsourced Verification Platform for Disaster Response

Earlier this year, Malaysian Airlines Flight 370 suddenly vanished, which set in motion the largest search and rescue operation in history—both on the ground and online. Colleagues at DigitalGlobe uploaded high resolution satellite imagery to the web and crowdsourced the digital search for signs of Flight 370. An astounding 8 million volunteers rallied online, searching through 775 million images spanning 1,000,000 square kilometers; all this in just 4 days. What if, in addition to mass crowd-searching, we could also mass crowd-verify information during humanitarian disasters? Rumors and unconfirmed reports tend to spread rather quickly on social media during major crises. But what if the crowd were also part of the solution? This is where our new Verily platform comes in.

Verily Image 1

Verily was inspired by the Red Balloon Challenge in which competing teams vied for a $40,000 prize by searching for ten weather balloons secretly placed across some 8,000,0000 square kilometers (the continental United States). Talk about a needle-in-the-haystack problem. The winning team from MIT found all 10 balloons within 8 hours. How? They used social media to crowdsource the search. The team later noted that the balloons would’ve been found more quickly had competing teams not posted pictures of fake balloons on social media. Point being, all ten balloons were found astonishingly quickly even with the disinformation campaign.

Verily takes the exact same approach and methodology used by MIT to rapidly crowd-verify information during humanitarian disasters. Why is verification important? Because humanitarians have repeatedly noted that their inability to verify social media content is one of the main reasons why they aren’t making wider user of this medium. So, to test the viability of our proposed solution to this problem, we decided to pilot the Verily platform by running a Verification Challenge. The Verily Team includes researchers from the University of Southampton, the Masdar Institute and QCRI.

During the Challenge, verification questions of various difficulty were posted on Verily. Users were invited to collect and post evidence justifying their answers to the “Yes or No” verification questions. The photograph below, for example, was posted with the following question:

Verily Image 3

Unbeknownst to participants, the photograph was actually of an Italian town in Sicily called Caltagirone. The question was answered correctly within 4 hours by a user who submitted another picture of the same street. The results of the new Verily experiment are promissing. Answers to our questions were coming in so rapidly that we could barely keep up with posting new questions. Users drew on a variety of techniques to collect their evidence & answer the questions we posted:

Verily was designed with the goal of tapping into collective critical thinking; that is, with the goal of encouraging people think about the question rather than use their gut feeling alone. In other words, the purpose of Verily is not simply to crowdsource the collection of evidence but also to crowdsource critical thinking. This explains why a user can’t simply submit a “Yes” or “No” to answer a verification question. Instead, they have to justify their answer by providing evidence either in the form of an image/video or as text. In addition, Verily does not make use of Like buttons or up/down votes to answer questions. While such tools are great for identifying and sharing content on sites like Reddit, they are not the right tools for verification, which requires searching for evidence rather than liking or retweeting.

Our Verification Challenge confirmed the feasibility of the Verily platform for time-critical, crowdsourced evidence collection and verification. The next step is to deploy Verily during an actual humanitarian disaster. To this end, we invite both news and humanitarian organizations to pilot the Verily platform with us during the next natural disaster. Simply contact me to submit a verification question. In the future, once Verily is fully developed, organizations will be able to post their questions directly.

bio

See Also:

  • Verily: Crowdsourced Verification for Disaster Response [link]
  • Crowdsourcing Critical Thinking to Verify Social Media [link]
  • Six Degrees of Separation: Implications for Verifying Social Media [link]

Live: Crowdsourced Crisis Map of UAV/Aerial Videos for Disaster Response

The first version of the Humanitarian UAV Network’s Crisis Map of UAV/aerial videos is now live on the Network’s website. The crowdsourced map features dozens of aerial videos of recent disasters. Like social media, this new medium—user-generated (aerial) content—can be used by humanitarian organizations to complement their damage assessments and thus improve situational awareness.

UAViators Map

The purpose of this Humanitarian UAV Network (UAViators) map is not only to provide humanitarian organizations and disaster-affected communities with an online repository of aerial information on disaster damage to augment their situational awareness; this crisis map also serves to raise awareness on how to safely & responsibly use small UAVs for rapid damage assessments. This explains why users who upload new content to the map must confirm that they have read the UAViator‘s Code of Conduct. They also have to confirm that the videos conform to the Network’s mission and that they do not violate privacy or copyrights. In sum, the map seeks to crowdsource both aerial footage and critical thinking for the responsible use of UAVs in humanitarian settings.

UAViators Map 4

As noted above, this is the first version of the map, which means several other features are currently in the works. These new features will be rolled out incrementally over the next weeks and months. In the meantime, feel free to suggest any features you’d like to see in the comments section below. Thank you.

Bio

  • Humanitarian UAV Network: Strategy for 2014-2015 [link]
  • Humanitarians in the Sky: Using UAVs for Disaster Response [link]
  • Humanitarian UAV Missions During Balkan Floods [link]
  • Using UAVs for Disaster Risk Reduction in Haiti [link]
  • Using MicroMappers to Make Sense of UAV/Aerial Imagery During Disasters [link]

Using UAVs for Community Mapping and Disaster Risk Reduction in Haiti

“What if, to solve our problems, we simply need to rise above them?” CartONG and France’s OpenStreetMap (OSM) community recently teamed up to support OSM Haiti’s disaster risk reduction efforts by deploying a small UAV, “which proved very useful for participatory mapping.” The video documentary below provides an excellent summary of this humanitarian UAV mission which took place just a few weeks ago.

As I noted in this earlier blog post on grassroots UAVs, the use of UAVs at the community level can be viewed as an extension of community and participatory mapping, which is why community engagement is pivotal for humanitarian UAV deployments. In many ways, a micro-UAV can actually bring a community together; can catalyze conversations & participation, which should be taken as more than simply a positive externality. Public Participatory GIS Projects (PPGIS) have long been used as a means to catalyze community conversations and even conflict resolution and mediation. So one should not overlook the positive uses of UAVs as a way to convene a community. Indeed, as CartONG and partners rightly note in the above video documentary, “The UAV is the uniting tool that brings the community together.”

Credit: CartONG/OSM.fr Video

This joint UAV project in Haiti has three phases: training for data collection; analysis and use of collected data; and empowering the Haitian OSM community to lead their own projects with their own partners. The first phase, which was just completed, comprised 42 individual UAV flights (using SenseFly’s eBee) in multiple locations including the Port-au-Prince area, the urbanized part of Saint-Marc, Sans-Souci Palace (Unesco World Heritage Site), Dominican Republic border areas and Bord de Mer. This enabled the Haitian OSM community to test the UAV under varying conditions and across different terrains.

Credit: CartONG & OSM.fr video

The UAV flight training included “aerial security” and an overview of the UAV’s weaknesses. As CartONG rightly notes, the use of UAVs for data collection and the training that goes along with “strengthen Haitian OSM communities, so that they can fully take part in local development.” To this end, I’m hoping to see more women flying UAVs in the future rather than seeing them standing by as passive observers. Community engagement without women is not community engagement. Perhaps UAVs can play a role in uniting and enabling women to become more engaged and take on leadership roles within communities.

Credit: CartONG & OSM.fr video

As part of their initial phase, CartONG and team also set up a mini-server to facilitate the processing of UAV imagery on site. “Considering the difficulties faced regarding aerial image processing the need for such a tool has been confirmed for all situations where accessing internet & electricity is a challenge.” Moreover, the Haitian OSM community expressed a direct interest in not only piloting UAVs but also in the processing and analysis of the resulting data: “communities wish to be trained to be able to fully master the process of collection and processing of aerial image, including on software such as ArcGIS and QGIS.”

Credit: OSM.fr

Screen Shot 2014-07-09 at 12.44.06 PM

I’m excited about these efforts and keen to follow the next phases of this UAV community mapping project. In the meantime, big thanks to CartONG’s Martin Noblecourt for kindly sharing this important volunteer-driven project. If you want to learn more about this initiative, feel free to contact Martin via email at info@cartong.org.

bio

See Also:

  • Humanitarians in the Sky: Using UAVs for Disaster Response [link]
  • Humanitarian UAV Missions in During Balkan Floods [link]

Humanitarian UAV Missions During Balkan Floods

The Balkans recently experienced the heaviest rains in 120 years of recorded weather measurements, causing massive flooding and powerful landslides. My colleague Haris Balta, a certified UAV pilot with the European Union’s ICARUS Unmanned Search & Rescue Project (and a member of the Humanitarian UAV Network, UAViators), was deployed to Bosnia to support relief efforts. During this time, another colleague, Peter Spruyt from the European Commission (DG JRC), was also deployed to the region to carry out a post-disaster needs assessment using UAVs.

Image: Flood in Bosnia and Herzegovina

Haris, who also works at the intersection of robotics and demining, was asked by the Government of the Federation of Bosnia and Herzegovina to identify the location of mines displaced due to the major flooding and mudslides. As it turns out, some mines were displaced as far as 23 kilometers. When the flood waters subsided and villagers returned, most were unaware of this imminent danger. Haris used a rotary-wing UAV (the quadcopter pictured below) and logged some 20 flights (both manual and autonomous) at more than a dozen locations.

ICARUS Quadcopter

Screen Shot 2014-07-02 at 9.41.49 AM

The purpose of these flights was to capture imagery that could be used to identify displaced land mines and to analyze the effects of landslides on other explosive remnants of war. Haris and team created 3D maps from the imagery and used geo-statistical modeling to try and determine in which direction land mines may have been displaced. The imagery also provided valuable information on dyke-breaches and other types of infrastructure damage.

Meanwhile, my colleague Peter from DG JRC (who is also a member of the Humanitarian UAV Network) flew a light fixed-wing UAV in five locations to support damage and needs assessments in close collaboration with the World Bank and the UN. According to Peter, both local and regional authorities were very supportive. Some of the resulting images and models of landslide areas are depicted below, courtesy of DG JRC (click to enlarge).

DG JRC

Screen Shot 2014-07-02 at 12.39.17 PM

Screen Shot 2014-07-02 at 12.31.18 PM

I just introduced Peter and Haris since they weren’t aware of each other’s respective efforts. If you’re participating in humanitarian UAV missions, please consider sharing you work with the Humanitarian UAV Network by posting a quick summary of your mission to the Network’s Operations page; even a one-sentence description will go a long way to facilitate information sharing.

bio

See Also:

  • Humanitarians in the Sky: Using UAVs for Disaster Response [link]
  • Crisis Map of UAV/Aerial Videos for Disaster Response [link]
  • Using UAVs for Search & Rescue [link]
  • Debrief: UAV/Drone Search & Rescue Challenge [link]
  • Crowdsourcing Analysis of UAV Imagery for Search/Rescue [link]
  • Check-List for Flying UAVs in Humanitarian Settings [link]