Disaster response apps have multiplied in recent years. I’ve been reviewing the most promising ones and have found that many cater to professional responders and organizations. While empowering paid professionals is a must, there has been little focus on empowering the real first responders, i.e., the disaster-affected communities themselves. To this end, there is always a dramatic mismatch in demand for responder services versus supply, which is why crises are brutal audits for humanitarian organizations. Take this Red Cross survey, which found that 74% of people who post a need on social media during a disaster expect a response within an hour. But paid responders cannot be everywhere at the same time during a disaster. The response needs to be decentralized and crowdsourced.
In contrast to paid responders, the crowd is always there. And most survivals following a disaster are thanks to local volunteers and resources, not external aid or relief. This explains why FEMA Administrator Craig Fugate has called on the public to become a member of the team. Decentralization is probably the only way for emergency response organizations to improve their disaster audits. As many seasoned humanitarian colleagues of mine have noted over the years, the majority of needs that materialize during (and after) a disaster do not require the attention of paid disaster responders with an advanced degree in humanitarian relief and 10 years of experience in Haiti. We are not all affected in the same way when disaster strikes, and those less affected are often very motivated and capable at responding to the basic needs of those around them. After all, the real first responders are—and have always been—the local communities themselves, not the Search and Rescue Teams that parachutes in 36 hours later.
In other words, local self-organized action is a natural response to disasters. Facilitated by social capital, self-organized action can accelerate both response & recovery. A resilient community is therefore one with ample capacity for self-organization. To be sure, if a neighborhood can rapidly identify local needs and quickly match these with available resources, they’ll rebound more quickly than those areas with less capacity for self-organized action. The process is a bit like building a large jigsaw puzzle, with some pieces standing for needs and others for resources. Unlike an actual jigsaw puzzle, however, there can be hundreds of thousands of pieces and very limited time to put them together correctly.
This explains why I’ve long been calling for a check-in & match.com smartphone app for local collective disaster response. The talk I gave (above) at Where 2.0 in 2011 highlights this further as do the blog posts below.
Check-In’s with a Purpose: Applications for Disaster Response
http://iRevolution.net/2011/02/16/checkins-for-disaster-response
Maps, Activism & Technology: Check-In’s with a Purpose
http://iRevolution.net/2011/02/05/check-ins-with-a-purpose
Why Geo-Fencing Will Revolutionize Crisis Mapping
http://iRevolution.net/2011/08/21/geo-fencing-crisis-mapping
How to Crowdsource Crisis Response
http://iRevolution.net/2011/09/14/crowdsource-crisis-response
The Crowd is Always There
http://iRevolution.net/2010/08/14/crowd-is-always-there
Why Crowdsourcing and Crowdfeeding may be the Answer
http://iRevolution.net/2010/12/29/crowdsourcing-crowdfeeding
Towards a Match.com for Economic Resilience
http://iRevolution.net/2012/07/04/match-com-for-economic-resilience
This “MatchApp” could rapidly match hyper local needs with resources (material & informational) available locally or regionally. Check-in’s (think Foursquare) can provide an invaluable function during disasters. We’re all familiar with the command “In case of emergency break glass,” but what if: “In case of emergency, then check-in”? Checking-in is space- and time-dependent. By checking in, I announce that I am at a given location at a specific time with a certain need (red button). This means that information relevant to my location, time, user-profile (and even vital statistics) can be customized and automatically pushed to my MatchApp in real-time. After tapping on red, MatchApp prompts the user to select what specific need s/he has. (Yes, the icons I’m using are from the MDGs and just placeholders). Note that the App we’re building is for Androids, not iPhones, so the below is for demonstration purposes only.
But MatchApp will also enable users who are less (or not) affected by a disaster to check-in and offer help (by tapping the green button). This is where the match-making algorithm comes to play. There are various (compatible options) in this respect. The first, and simplest, is to use a greedy algorithm. This algorithm select the very first match available (which may not be the most optimal one in terms of location). A more sophisticated approach is to optimize for the best possible match (which is a non-trivial challenge in advanced computing). As I’m a big fan of Means of Exchange, which I have blogged about here, MatchApp would also enable the exchange of goods via bartering–a mobile eBay for mutual-help during disasters.
Once a match is made, the two individuals in question receive an automated alert notifying them about the match. By default, both users’ identities and exact locations are kept confidential while they initiate contact via the app’s instant messaging (IM) feature. Each user can decide to reveal their identity/location at any time. The IM feature thus enables users to confirm that the match is indeed correct and/or still current. It is then up to the user requesting help to share her or his location if they feel comfortable doing so. Once the match has been responded to, the user who received help is invited to rate the individual who offered help (and vice versa, just like the Uber app, depicted on the left below).
As a next generation disaster response app, MatchApp would include a number of additional data entry features. For example, users could upload geo-tagged pictures and video footage (often useful for damage assessments). In terms of data consumption and user-interface design, MatchApp would be modeled along the lines of the Waze crowdsourcing app (depicted on the right above) and thus designed to work mostly “hands-free” thanks to a voice-based interface. (It would also automatically sync up with Google Glasses).
In terms of verifying check-in’s and content submitted via MatchApp, I’m a big fan of InformaCam and would thus integrate the latter’s meta-data verification features into MatchApp: “the user’s current GPS coordinates, altitude, compass bearing, light meter readings, the signatures of neighboring devices, cell towers, and wifi networks; and serves to shed light on the exact circumstances and contexts under which the digital image was taken.” I’ve also long been interested in peer-to-peer meshed mobile communication solutions and would thus want to see an integration with the Splinternet app, perhaps. This would do away with the need for using cell phone towers should these be damaged following a disaster. Finally, MatchApp would include an agile dispatch-and-coordination feature to allow “Super Users” to connect and coordinate multiple volunteers at one time in response to one or more needs.
In conclusion, privacy and security are a central issue for all smartphone apps that share the features described above. This explains why reviewing the security solutions implemented by multiple dating websites (especially those dating services with a strong mobile component like the actual Match.com app) is paramount. In addition, reviewing security measures taken by Couchsurfing, AirBnB and online classified adds such as Craig’s List is a must. There is also an important role for policy to play here: users who submit false misinformation to MatchApp could be held accountable and prosecuted. Finally, MatchApp would be free and open source, with a hyper-customizable, drag-and-drop front- and back-end.
iRevolutions 
Dont Forget StormPins iPhone app at StormPIns.com
Great ideas, as usual. Another useful component of a MatchApp would be a quick check by the match-making algorithm for reliable news on the situation on the ground – maybe no help between the two parties is possible, because of road/bridge damage, flooding, etc., without the two parties knowing about it. Just to make sure that the helping individual doesn’t get into trouble him/herself. I guess we both agree that “reliable news” can very well be the result of volunteered information from affected citizens 🙂
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when a disaster (like an earthquake) happens how do you communicate without data network?
Great post, amazing idea, I’d love see the app. A hackaton-to-do !
Although it fits the devidence that first responder are the community itself, I would not oppose the community and aid organizations – I also firmly believe organizations like the Red Cross are unique for they are rooted in the communities, and their volunteers are meant to act as a “standby task force” of its own kind. So I am curious it the app could not be also adjusted for some kind of second-level type of match or supervision by local committees.
Patrick,
Excellent App design concept!
I live in the Mountains west of Denver Colorado, and have experienced several large fires in the last few years as a firefighter and concerned resident. My experiences with these events influence my commentary on your design for the application. I consider it a very 1st world analysis compared to potential international applications of the app. I agree that an app which creates a platform where local residents can connect and establish community ties during an incident could be very readily used during wildfires here in the Colorado, and has lead me to research the subject in great detail and design a similar concept.
The idea presents many difficult challenges to be an effective tool for first responders on the ground. The most obvious being the potential loss of infrastructure and ability to communicate on a wireless network that can support such an application.
Some of my biggest concerns include:
Response- At least in the United States, when a large Type 1 incident occurs, there are usually mandatory evacuations that go along with it. Civilian, community member usage would be limited for volunteering and helping others in the effected area while the incident is occurring. Same would be the case for flooding or earthquakes.
Redundancy- Do other social media apps such as Neighborhood, Loci.st, Facebook event pages, Twitter, as well as the myriad of other social media platforms act as the users go to communication tool during an incident where they would share the information that this app needs to be relevant? The previous comment obviously describes crowd mapping, but does this app incorporate crow mapped information? Without an audience or large viewership, would this app turn into vaporware? People would have no use for an application like this until an incident occurred. I.e. its market consists of a limited population. I look at Elerts as an example, where as far as I can tell, not a single user has uploaded information onto its platform.
Financial Mechanism- Brilliant concept and is something I have pondered for some time. The first concern that always comes to mind is fraud… Verifying which individuals are telling the truth is a difficult task. Also with an interface where victims who embellish their stories get the most crowd response and contributions, your asking half truths and lies.
Great presentation and layout for the idea. I am a big fan of your work!
Emmit
You should check out “NoonHat” – very similar idea for people able to get connected to meetup for lunch by not sharing their information until private criteria are met (look, you both are ‘nearby’ and said you want to share lunch at this time frame)
http://www.noonhat.com/lunch/
Fun!Thanks very much for sharing, Andrew!
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Hello, I do think that the weak side of these applications is to be designed for Android and Iphone like devices whereas the most of users may own only for example Nokia Symbian phones!
Most of users… in the developing countries for sure, where old good Nokias will be king as long as people don’t have 3 to 600$ at hand!. Yet disasters also strike very much in the US, obvisouly a good experimentation ground for more advanced uses and the developed world.
Thanks for reading and commenting, Agnes! Recent stats show that virtually all mobile phones produced today are smart phones; feature phones are going extinct and very quickly. Also, Androids are now available for $50 and getting cheaper every year. As for producing this app for other smart phones, that is perfectly easy and straightforward. Hope this helps! Thanks again for reading! 🙂
That is true when working for the future, yet I think for the present and near times this might be a bit optimistic andf I would rather stick with @Calamita’s reserve, for:
1- phones produced today and phones used today are two different statistics – phone repairing in Africa is a national sports and they manage to get old Nokias work on and on for decades when need is (the same repaimen can also destroy an iphone in no times 😉
2 – 50$ Android are rather available through NGO or other-driven programmes but not so much available in the shops, in my experience, where phones match the market,with either cheap ZTE phones for the large public, and expensive Blackberry, Iphones Samsung etc for the so caloled new middle class (happy few)
3 – even 50$ will be very expensive for the general African public, as long as their development
Do you have the statistics for the % of phones that are feature phones in developing countries, or are these more anecdotal comments? Fact is, 50% of people living in developing countries will be on the Internet within the next 20 months (OCHA 2013 stats in upcoming report). But again, we are not building our app exclusively for developing countries. Indeed, in not point in the blog post do I even hint at applying this app in resource scarce environments, so your comments are somewhat misplaced because I never argued the contrary 🙂 Re your iPhone comment, yes, the screenshots on my post are of iPhones but we’re building our app for Androids which has the greatest market share of all phones. I realize this was not made explicit in the post so have just added it now.
$50 Android phones are readily available in shops in Nairobi and not for NGOs only. And again, as already mentioned (sorry to repeat myself), phone prices are rapidly decreasing, not increasing. I’ve lived and worked in Africa for 15 years, so I know all about Juwa kali jobs. But I think you underestimate people’s insatiable thirst for accessing more information (cf Ethan Zuckerman’s Cute Cat Theory). Androids will soon be worth $30, then $20 and who knows, even $10 or less. In the meantime, yes, my team and I at QCRI and MIT are building for the near future because that is precisely where our own comparative advantage is. But this in no way prevents anyone from trying to come up with a basic SMS matching system. So by all means go ahead and create one (please let me know if you do). I know that Occupy Sandy tried and it failed miserably. But do let me know if you find one that works, and if it is open source, then we should be able to integrate it in our App.
Thanks again for reading!
oups… tbc
as long as their average revenue is as low as it is.
On top of that, the quality of the 50$ tablets is still often problematic to run general apps (most Chinese makes need compliate ahcks to access the market, etc). Not an unovverrideable ifficulty, but not to be ignored.
I did some researck about a year ago for an African web project, and the result was definitely pro-mobile, but also very much pro-Nokia – or call it low tech (sorry the links apparently won’t go through):
A large number of African users are indeed mobile-only (that is even true of 25% of mobile web users in the US (mobithinking). “Feature phones” (low tech phones with web access) still outnumber smartphones 2:1 worldwide. “If your mobile strategy doesn’t include feature phones, it doesn’t include most of your customers.” says Mobithinking. That may change fast in the developed world (smartphone usage has definitely passed cell usage in the US), but will remain very true for longer in Africa, where 85 percent of the mobile-only Web users access the Web with a feature phone. The main OS for this African audience is made of Symbian (above 70%!), Samsung (7%) & Android (3.7%), far above iOS, according to Statcounter (below or here). This article on feature phones also gives nice insights on feature phones & shows how Nokia dominates Africa.
Here is the latest article named “Why You Must Never Forget About the Humble Feature Phone in Africa”
http://afrinnovator.com/blog/2012/02/02/why-you-must-never-forget-about-the-humble-feature-phone-in-africa/
The analysis is about a year old, so it obviously can be considered past, yet again inertia in Africa is higher than in the developed world as devices enjoy a much longer lifecycle there.
Thanks, but please see my previous reply. You’re putting words in my mouth. At no point in my blog post do I write that we were building this for developing countries, nor do I even hint at this! So you’re comments are misplaced and not in relation to what I actually wrote. I understand that you’re approaching the app from your own perspective/lens and field experience, which is great, but your (constructive) criticisms would be legitimate if I actually made a case for this app to be used in resource constrained environments.
No problem, Patrick, I understood also from your blog post that the app was not primarily targeted for the developing world. I was myself suggesting to @cypherinfo that his/her comment about Nokias was valid for the developing world, while the app could certainly demonstrate its value in disasters that will strike the more developed regions – before one day possibly be used elsewhere (how fast those OS will reach Africa, only history will say). Then my comments and stats about mobile phones in Africa were just to keep that distinction (developed/developing world) alive in mind in front of the trend that “virtually all mobile phones produced today are smart phones”.
Rest I think is a difference between a visionnary approach of yours and that previous research of mine for a practical implementation at a present time – nothing to argue much about 🙂
The map I linked to actually shows that if the US and Western Europe are iOS, most of Asia is already very much Android, and only Africa and India stick with more low tech phones, so the developedd/developing distinction I did is a bit Afro-centric.
Then, until they can rely on a better user base, many communities and organisations in Africa do use more basic tools like with frontlineSMS, but obviousy those can’t be as smart as apps for smartphones! So I keep being a real fan of this app proposal 🙂
For fresh stats, check out these maps (that will prove Nokia-like conservatism right or wrong, depending on the country base!)
http://gs.statcounter.com/?mobile_os-af-monthly-201301-201302-map#mobile_os-ww-monthly-201302-201303-map
The time view is also interesting.
Thanks, please let me know where exactly in my blog post I hint at or suggest that we are building MatchApp for resource constrained environments.
You have not indeed, and I only meant to provide some hints over the high tech / low tech isssue raised by @cypherinfo.
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Hi Patrick,
Where about are you in the development stage. We are working on a very similar project at University of Cambridge. It would be good to get in touch.
http:www.crowdaidexchange.com
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This is very interesting as most of the humanitarian technology work. I appreciate the theoretical part of it, but I haven’t seen many of these ideas working in a real emergency setting. Not yet that is. I find one of your picture summarizes pretty well my thought, the “I have no water but 3g connection” one. Best of luck and will be following the developments!
Thanks for reading, Luca. This approach, matching needs & resources, could work on SMS as well. But a no point do I make a claim that 3G or SMS is universally available 🙂
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