Tag Archives: UAVs

Welcome to the Humanitarian UAV Network

UAViators Logo

The Humanitarian UAV Network (UAViators) is now live. Click here to access and join the network. Advisors include representatives from 3D Robotics, AirDroids, senseFly & DroneAdventures, OpenRelief, ShadowView Foundation, ICT4Peace Foundation, the United Nations and more. The website provides a unique set of resources, including the most comprehensive case study of humanitarian UAV deployments, a directory of organizations engaged in the humanitarian UAV space and a detailed list of references to keep track of ongoing research in this rapidly evolving area. All of these documents along with the network’s Code of Conduct—the only one of it’s kind—are easily accessible here.

UAViators 4 Teams

The UAViators website also includes 8 action-oriented Teams, four of which are displayed above. The Flight Team, for example, includes both new and highly experienced UAV pilots while the Imagery Team comprises members interested in imagery analysis. Other teams include the Camera, Legal and Policy Teams. In addition to this Team page, the site also has a dedicated Operations page to facilitate & coordinate safe and responsible UAV deployments in support of humanitarian efforts. In between deployments, the website’s Global Forum is a place where members share information about relevant news, events and more. One such event, for example, is the upcoming Drone/UAV Search & Rescue Challenge that UAViators is sponsoring.

When first announcing this initiative,  I duly noted that launching such a network will at first raise more questions than answers, but I welcome the challenge and believe that members of UAViators are well placed to facilitate the safe and responsible use of UAVs in a variety of humanitarian contexts.

Acknowledgements: Many thanks to colleagues and members of the Advisory Board who provided invaluable feedback and guidance in the lead-up to this launch. The Humanitarian UAV Network is result of collective vision and effort.

bio

See also:

  • How UAVs are Making a Difference in Disaster Response [link]
  • Humanitarians Using UAVs for Post Disaster Recovery [link]
  • Grassroots UAVs for Disaster Response [link]
  • Using UAVs for Search & Rescue [link]
  • Crowdsourcing Analysis of UAV Imagery for Search and Rescue [link]

Using Crowd Computing to Analyze UAV Imagery for Search & Rescue Operations

My brother recently pointed me to this BBC News article on the use of drones for Search & Rescue missions in England’s Lake District, one of my favorite areas of the UK. The picture below is one I took during my most recent visit. In my earlier blog post on the use of UAVs for Search & Rescue operations, I noted that UAV imagery & video footage could be quickly analyzed using a microtasking platform (like MicroMappers, which we used following Typhoon Yolanda). As it turns out, an enterprising team at the University of Central Lancashire has been using microtasking as part of their UAV Search & Rescue exercises in the Lake District.

Lake District

Every year, the Patterdale Mountain Rescue Team assists hundreds of injured and missing persons in the North of the Lake District. “The average search takes several hours and can require a large team of volunteers to set out in often poor weather conditions.” So the University of Central Lancashire teamed up with the Mountain Rescue Team to demonstrate that UAV technology coupled with crowdsourcing can reduce the time it takes to locate and rescue individuals.

The project, called AeroSee Experiment, worked as follows. The Mountain Rescue service receives a simulated distress call. As they plan their Search & Rescue operation, the University team dispatches their UAV to begin the search. Using live video-streaming, the UAV automatically transmits pictures back to the team’s website where members of the public can tag pictures that members of the Mountain Rescue service should investigate further. These tagged pictures are then forwarded to “the Mountain Rescue Control Center for a final opinion and dispatch of search teams.” Click to enlarge the diagram below.

AeroSee

Members of the crowd would simply log on to the AeroSee website and begin tagging. Although the experiment is over, you can still do a Practice Run here. Below is a screenshot of the microtasking interface (click to enlarge). One picture at a time is displayed. If the picture displays potentially important clues, then the digital volunteer points to said area of the picture and types in why they believe the clue they’re pointing at might be important.

AeroSee MT2

The results were impressive. A total of 335 digital volunteers looked through 11,834 pictures and the “injured” walker (UAV image below) was found within 69 seconds of the picture being uploaded to microtasking website. The project team subsequently posted this public leaderboard to acknowledge all volunteers who participated, listing their scores and levels of accuracy for feedback purposes.

Aero MT3

Upon further review of the data and results, the project team concluded that the experiment was a success and that digital Search & Rescue volunteers were able to “home in on the location of our missing person before the drones had even landed!” The texts added to the tagged images were also very descriptive, which helped the team “locate the casualty very quickly from the more tentative tags on other images.”

If the area being surveyed during a Search & Rescue operation is fairly limited, then using the crowd to process UAV images is a quick and straightforward, especially if the crowd is relatively large. We have over 400 digital humanitarian volunteers signed up for MicroMappers (launched in November 2013) and hope to grow this to 1,000+ in 2014. But for much larger areas, like Kruger National Park, one would need far more volunteers. Kruger covers 7,523 square miles compared to the Lake District’s 885 square miles.

kruger-gate-sign

One answer to this need for more volunteers could be the good work that my colleagues over at Zooniverse are doing. Launched in February 2009, Zooniverse has a unique volunteer base of one million volunteers. Another solution is to use machine computing to prioritize the flights paths of UAVs in the first place, i.e., use advanced algorithms to considerably reduce the search area by ruling out areas that missing people or other objects of interest (like rhinos in Kruger) are highly unlikely to be based on weather, terrain, season and other data.

This is the area that my colleague Tom Snitch works in. As he noted in this recent interview (PDF), “We want to plan a flight path for the drone so that the number of unprotected animals is as small as possible.” To do this, he and his team use “exquisite mathematics and complex algorithms” to learn how “animals, rangers and poachers move through space and time.” In the case Search & Rescue, ruling out areas that are too steep and impossible for humans to climb or walk through could go a long way to reducing the search area not to mention the search time.

bio

See also:

  • Using UAVs for Search & Rescue [link]
  • MicroMappers: Microtasking for Disaster Response [link]
  • Results of MicroMappers Response to Typhoon Yolanda [link]
  • How UAVs are Making a Difference in Disaster Response [link]
  • Crowdsourcing Evaluation of Sandy Building Damage [link]

Using UAVs for Search & Rescue

UAVs (or drones) are starting to be used for search & rescue operations, such as in the Philippines following Typhoon Yolanda a few months ago. They are also used to find missing people in the US, which may explain why members of the North Texas Drone User Group (NTDUG) are organizing the (first ever?) Search & Rescue challenge in a few days. The purpose of this challenge is to 1) encourage members to build better drones and 2) simulate a real world positive application of civilian drones.

Drones for SA

Nine teams have signed up to compete in Saturday’s challenge, which will be held in a wheat field near Renaissance Fair in Waxahachie, Texas (satellite image below). The organizers have already sent these teams a simulated missing person’s report. This will include a mock photo, age, height, hair color, ethnicity, clothing and where/when this simulated lost person was last seen. Each drone must have a return to home function and failsafe as well as live video streaming.

Challenge location

When the challenge launches, each team will need to submit a flight plan to the contest’s organizers before being allowed to search for the missing items (at set times). An item is considered found when said item’s color or shape can be described and if the location of this item can be pointed to on a Google Map. These found objects then count as points. Points are also awarded for finding tracks made by humans or animals, for example. Points will be deducted for major crashes, for flying at an altitude above the 375 feet limit and risk disqualification for flying over people.

While I can’t make it to Waxahachie this weekend to observe the challenge first-hand, I’m thrilled that the DC Drones group (which I belong to), is preparing to host its own drones search & rescue challenge this Spring. So I hope to be closely involved with this event in the coming months.

Wildlife challenge

Although search & rescue is typically thought of as searching for people, UAVs are also beginning to appear in conversations about anti-poaching operations. At the most recent DC Drones MeetUp, we heard a presentation on the first ever Wildlife Conservation UAV Challenge (wcUAVc). The team has partnered with Krueger National Park to support their anti-poaching efforts in the face of skyrocketing Rhino poaching.

Rhino graph

The challenge is to “design low cost UAVs that can be deployed over the rugged terrain of Kruger, equipped with sensors able to detect and locate poachers, and communications able to relay accurate and timely intelligence to Park Rangers.” In addition, the UAVs will have to “collect RFID tag data throughout the sector; detect, classify, and tack all humans; regularly report on the location of all rhinos and humans; and receive commands to divert from general surveillance to support poacher engagement anywhere in the sector. They also need to be able to safely operate in same air space with manned helicopters, assisting special helicopter borne rangers engage poachers.” All this for under $3,000.

Why RFID tag data? Because rangers and tourists in Krueger National Park all carry RFID tags so they can be easily located. If a UAV automatically detects a group of humans moving through the bush and does not find an RFID signature for them, the UAV will automatically conclude that they may be poachers. When I spoke with one of the team members following the presentation, he noted that they were also interested in having UAVs automatically detect whether humans are carrying weapons. This is no small challenge, which explains why the total cash prize is $65,000 and an all-inclusive 10-day trip to Krueger National Park for the winning team.

I think it would be particularly powerful if the team could open up the raw footage for public analysis via microtasking, i.e., include a citizen science component to this challenge to engage and educate people from around the world about the plight of rhinos in South Africa. Participants would be asked to tag imagery that show rhinos and humans, for example. In so doing, they’d learn more about the problem, thus becoming better educated and possibly more engaged. Perhaps something along the lines of what we do for digital humanitarian response, as described here.

Drone Innovation Award

In any event, I’m a big proponent of using UAVs for positive social impact, which is precisely why I’m honored to be an advisor for the (first ever?) Drones Social Innovation Award. The award was set up by my colleague Timothy Reuter (founder of the the Drone User Group Network, DUGN). Timothy is also launching a startup, AirDroids, to further democratize the use of micro-copters. Unlike similar copters out there, these heavy-lift AirDroids are easier to use, cheaper and far more portable.

As more UAVs like AirDroids hit the market, we will undoubtedly see more and more aerial photo- and videography uploaded to sites like Flickr and YouTube. Like social media, I expect such user-generated imagery to become increasingly useful in humanitarian response operations. If users can simply slip their smartphones into their pocket UAV, they could provide valuable aerial footage for rapid disaster damage assessments purposes, for example. Why smart-phones? Because people already use their smartphones to snap pictures during disasters. In addition, relatively cheap hardware add-on’s can easily turn smartphones for LIDAR sensing and thermal imaging.

All this may eventually result in an overflow of potentially useful aerial imagery, which is where MicroMappers would come in. Digital volunteers could easily use MicroMappers to quickly tag UAV footage in support of humanitarian relief efforts. Of course, UAV footage from official sources will also continue to play a more important role in the future (as happened following Hurricane Sandy). But professional UAV teams are already outnumbered by DIY UAV users. They simply can’t be everywhere at the same time. But the crowd can. And in time, a bird’s eye view may become less important than a flock’s eye view, especially for search & rescue and rapid disaster assessments.

Bio

 See also:

  • How UAVs are Making a Difference in Disaster Response [link]
  • UN World Food Program to Use UAVs [link]
  • Drones for Human Rights: Brilliant or Foolish? [link]
  • The Use of Drones for Nonviolent Civil Resistance [link]

Imagery and Humanitarian Assistance: Gems, Errors and Omissions

The Center for Technology and National Security Policy based at National Defense University’s Institute for National Strategic Studies just published an 88-page report entitled “Constructive Convergence: Imagery and Humanitarian Assistance.” As noted by the author, “the goal of this paper is to illustrate to the technical community and interested humanitarian users the breadth of the tools and techniques now available for imagery collection, analysis, and distribution, and to provide brief recommendations with suggestions for next steps.” In addition, the report “presents a brief overview of the growing power of imagery, especially from volunteers and victims in disasters, and its place in emergency response. It also highlights an increasing technical convergence between professional and volunteer responders—and its limits.”

The study contains a number of really interesting gems, just a few errors and some surprising omissions. The point of this blog post is not to criticize but rather to provide constructive-and-hopefully-useful feedback should the report be updated in the future.

Lets begin with the important gems, excerpted below.

“The most serious issues overlooked involve liability protections by both the publishers and sources of imagery and its data. As far as our research shows there is no universally adopted Good Samaritan law that can protect volunteers who translate emergency help messages, map them, and distribute that map to response teams in the field.”

Whether a Good Samaritan law could ever realistically be universally adopted remains to be seen, but the point is that all of the official humanitarian data protection standards that I’ve reviewed thus far simply don’t take into account the rise of new digitally-empowered global volunteer networks (let alone the existence of social media). The good news is that some colleagues and I are working with the International Committee of the Red Cross (ICRC) and a consor-tium of major humanitarian organizations to update existing data protection protocols to take some of these new factors into account. This new document will hopefully be made publicly available in October 2012.

“Mobile devices such as tablets and mobile phones are now the primary mode for both collecting and sharing information in a response effort. A January 2011 report published by the Mobile Computing Promotion Consortium of Japan surveyed users of smart phones. Of those who had smart phones, 55 percent used a map application, the third most common application after Web browsing and email.”

I find this absolutely fascinating and thus read the January 2011 report, which is where I found the graphic below.

“The rapid deployment of Cellular on Wheels [COW] is dramatically improving. The Alcatel-Lucent Light Radio is 300 grams (about 10 ounces) and stackable. It also consumes very little power, eliminating large generation and storage requirements. It is capable of operating by solar, wind and/or battery power. Each cube fits into the size of a human hand and is fully integrated with radio processing, antenna, transmission, and software management of frequency. The device can operate on multiple frequencies simultaneously and work with existing infrastructure.”

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“In Haiti, USSOUTHCOM found imagery, digital open source maps, and websites that hosted them (such as Ushahidi and OpenStreetMap) to occasionally be of greater value than their own assets.”

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“It is recommended that clearly defined and restricted use of specialized #hashtags be implemented using a common crisis taxonomy. For example:

#country + location + emergency code + supplemental data

The above example, if located in Washington, DC, U.S.A., would be published as:

#USAWashingtonDC911Trapped

The specialized use of #hashtags could be implemented in the same cultural manner as 911, 999, and other emergency phone number systems. Metadata using these tags would also be given priority when sent over the Internet through communication networks (landline, broadband Internet, or mobile text or data). Abuse of ratified emergency #hashtag’s would be a prosecutable offense. Implementing such as system could reduce the amount of data that crisis mappers and other response organizations need to monitor and improve the quality of data to be filtered. Other forms of #Hashtags syllabus can also be implemented such as:

#country + location + information code (411) + supplemental data
#country + location + water (H20) + supplemental data
#country + location + Fire (FD) + supplemental data”

I found this very interesting and relevant to this earlier blog post: “Calling 911: What Humanitarians Can Learn from 50 Years of Crowdsourcing.” Perhaps a reference to Tweak the Tweet would have been worthwhile.

I also had not come across some of the platforms used in response to the 2011 earthquake in New Zealand. But the report did an excellent job sharing these.

EQviewer.co.nz

Some errors that need correcting:

Open source mapping tools such as Google Earth use imagery as a foundation for layering field data.”

Google Earth is not an open source tool.

CrisisMappers.net, mentioned earlier, is a group of more than 1,600 volunteers that have been brought together by Patrick Meier and Jen Ziemke. It is the core of collaboration efforts that can be deployed anywhere in the world. CrisisMappers has established workshops and steering committees to set guidelines and standardize functions and capabilities for sites that deliver imagery and layered datasets. This group, which today consists of diverse and talented volunteers from all walks of life, might soon evolve into a professional volunteer organization of trusted capabilities and skill sets and they are worth watching.”

CrisisMappers is not a volunteer network or an organization that deploys in any formal sense of the word. The CrisisMappers website explains what the mission and purpose of this informal network is. The initiative has some 3,500 members.

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“Figure 16. How Ushahidi’s Volunteer Standby Task Force was Structured for Libya. Ushahidi’s platform success stems from its use by organized volunteers, each with skill sets that extract data from multiple sources for publication.”

The Standby Volunteer Task Force (SBTF) does not belong to Ushahidi, nor is the SBTF an Ushahidi project. A link to the SBTF website would have been appropriate. Also, the majority of applications of the Ushahidi platform have nothing to do with crises, or the SBTF, or any other large volunteer networks. The SBTF’s original success stems from organized volunteers who where well versed in the Ushahidi platform.

“Ushahidi accepts KML and KMZ if there is an agreement and technical assistance resources are available. An end user cannot on their own manipulate a Ushahidi portal as an individual, nor can external third party groups unless that group has an arrangement with the principal operators of the site. This offers new collaboration going forward. The majority of Ushahidi disaster portals are operated by volunteer organizations and not government agencies.”

The first sentence is unclear. If someone sets up an Ushahidi platform and they have KML/KMZ files that they want to upload, they can go ahead and do so. An end-user can do some manipulation of an Ushahidi portal and can also pull the Ushahidi data into their own platform (via the GeoRSS feed, for example). Thanks to the ESRI-Ushahidi plugin, they can then perform a range of more advanced GIS analysis. In terms of volunteers vs government agencies, indeed, it appears the former is leading the way vis-a-vis innovation.

Finally, below are some omissions and areas that I would have been very interested to learn more about. For some reason, the section on the Ushahidi deployment in New Zealand makes no reference to Ushahidi.

Staying on the topic of the earthquake in Christchurch, I was surprised to see no reference to the Tomnod deployment:

I had also hoped to read more about the use of drones (UAVs) in disaster response since these were used both in Haiti and Japan. What about the rise of DIY drones and balloon mapping? Finally, the report’s reference to Broadband Global Area Network (BGAN) doesn’t provide information on the range of costs associated with using BGANs in disasters.

In conclusion, the report is definitely an important contribution to the field of crisis mapping and should be required reading.