Tag Archives: Mobile

Tracking Population Movements using Mobile Phones and Crisis Mapping: A Post-Earthquake Geospatial Study in Haiti

I’ve been meaning to blog about this project since it was featured on BBC last month: “Mobile Phones Help to Target Disaster Aid, says Study.” I’ve since had the good fortune of meeting Linus Bengtsson and Xin Lu, the two lead authors of this study (PDF), at a recent strategy meeting organized by GSMA. The authors are now launching “Flowminder” in affiliation with the Karolinska Institutet in Stockholm to replicate their excellent work beyond Haiti. If “Flowminder” sounds familiar, you may be thinking of Hans Rosling’s “Gapminder” which also came out of the Karolinska Institutet. Flowminder’s mission: “Providing priceless information for free for the benefit of those who need it the most.”

As the authors note, “population movements following disasters can cause important increases in morbidity and mortality.” That is why the UN sought to develop early warning systems for refugee flows during the 1980’s and 1990’s. These largely didn’t pan out; forecasting is not a trivial challenge. Nowcasting, however, may be easier. That said, “no rapid and accurate method exists to track population movements after disasters.” So the authors used “position data of SIM cards from the largest mobile phone company in Haiti (Digicel) to estimate the magnitude and trends of population movements following the Haiti 2010 earthquake and cholera outbreak.”

The geographic locations of SIM cards were determined by the location of the mobile phone towers that SIM cards were connecting to when calling. The authors followed the daily positions of 1.9 million SIM cards for 42 days prior to the earthquake and 158 days following the quake. The results of the analysis reveal that an estimated 20% of the population in Port-au-Prince left the city within three weeks of the earthquake. These findings corresponded well with of a large, retrospective population based survey carried out by the UN.

“To demonstrate feasibility of rapid estimates and to identify areas at potentially increased risk of outbreaks,” the authors “produced reports on SIM card move-ments from a cholera outbreak area at its immediate onset and within 12 hours of receiving data.” This latter analysis tracked close to 140,000 SIM cards over an 8 day period. In sum, the “results suggest that estimates of population movements during disasters and outbreaks can be delivered rapidly and with potentially high validity in areas with high mobile phone use.”

I’m really keen to see the Flowminder team continue their important work in and beyond Haiti. I’ve invited them to present at the International Conference of Crisis Mappers (ICCM 2011) in Geneva next month and hope they’ll be able to join us. I’m interested to explore the possibilities of combining this type of data and analysis with crowdsourced crisis information and satellite imagery analysis. In addition, mobile phone data can also be used to estimate the hardest hit areas after a disaster. For more on this, please see my previous blog post entitled “Analyzing Call Dynamics to Assess the Impact of Earthquakes” and this post on using mobile phone data to assess the impact of building damage in Haiti.

Mobile Technologies for Conflict Management

“Mobile Technologies for Conflict Management: Online Dispute Resolution, Governance, Participation” is the title of a new book edited by Marta Poblet. I recently met Marta in Vienna, Austria during the UN Expert Meeting on Croudsource Mapping organized by UN SPIDER. I’m excited that her book has just launched. The chapters are is divided into 3 sections: Disruptive Applications of Mobile Technologies; Towards a Mobile ODR; and Mobile Technologies: New Challenges for Governance, Privacy and Security.

The book includes chapters by several colleagues of mine like Mike Best on “Mobile Phones in Conflict Stressed Environments”, Ken Banks on “Appropriate Mobile Technologies,” Oscar Salazar and Jorge Soto on “How to Crowdsource Election Monitoring in 30 Days,” Jacok Korenblum and Bieta Andemariam on “How Souktel Uses SMS Technology to Empower and Aid in Conflict-Affected Communities,” and Emily Jacobi on “Burma: A Modern Anomaly.”

My colleagues Jessica Heinzelman, Rachel Brown and myself also contributed one of the chapters. I include the introduction below.

I had long wanted to collaborate on a peer-reviewed chapter in which I could combine my earlier study of conflict resolution theory with my experience in conflict early warning and crisis mapping. See also this earlier blog post on “Crowdsourcing for Peace Mapping.”  I’ve been a big fan of Will Ury’s approach ever since coming across his work while at Columbia University back in 2003. Little did I know then that I’d be co-authoring this book chapter with two new stellar colleagues. Rachel has taken much of this thinking and applied it to the real world in her phenomenal project called Sisi ni Amni, or “We Are Peace.” You can follow them on Twitter. Jessica now serves on their Advisory Board.

A List of Completely Wrong Assumptions About Technology Use in Emerging Economies

I’ve spent the past week at the iLab in Liberia and got what I came for: an updated reality check on the limitations of technology adoption in developing countries. Below are some of the assumptions that I took for granted. They’re perfectly obvious in hindsight and I’m annoyed at myself for not having realized their obviousness sooner. I’d be very interested in hearing from others about these and reading their lists. This need not be limited to one particular sector like ICT for Development (ICT4D) or Mobile Health (mHealth). Many of these assumptions have repercussions across multiple disciplines.

The following examples come from conversations with my colleague Kate Cummings who directs Ushahidi Liberia and the iLab here in Monrovia. She and her truly outstanding team—Kpetermeni Siakor, Carter Draper, Luther Jeke and Anthony Kamah—spearheaded a number of excellent training workshops over the past few days. At one point we began discussing the reasons for the limited use of SMS in Liberia. There are the usual and obvious reasons. But the one hurdle I had not expected to hear was Nokia’s predictive text functionality. This feature is incredibly helpful since the mobile phone basically guesses which words you’re trying to write so you don’t have to type every single letter.

But as soon as she pointed out how confusing this can be, I immediately understood what she meant. If I had never seen or been warned about this feature before, I’d honestly think the phone was broken. It would really be impossible to type with. I’d get frustrated and give up (the tiny screen further adds to the frustration). And if I was new to mobile phones, it wouldn’t be obvious how to switch that feature off either. (There are several tutorials online on how to use the predictive text feature and how to turn it off, which clearly proves they’re not intuitive).

In one of the training workshops we just had, I was explaining what Walking Papers was about and how it might be useful in Liberia. So I showed the example below and continued talking. But Kate jumped in and asked participants: “What do you see in this picture? Do you see the trees, the little roads?” She pointed at the features as she described the individual shapes. This is when it dawned on me that there is absolutely nothing inherently intuitive about satellite images. Most people on this planet have not been on an airplane or a tall building. So why would a bird’s eye view of their village be anything remotely recognizable? I really kicked myself on that one. So I’ll write it again: there is nothing intuitive about satellite imagery. Nor is there anything intuitive about GPS and the existence of a latitude and longitude coordinate system.

Kate went on to explain that this kind of picture is what you would see if you were flying high like a bird. That was the way I should have introduced the image but I had taken it completely for granted that satellite imagery was self-explanatory when it simply isn’t. In further conversations with Kate, she explained that they too had made that assumption early on when trying to introduce the in’s and out’s of the Ushahidi platform. They quickly realized that they had to rethink their approach and decided to provide introductory courses on Google Maps instead.

More wrong assumptions revealed themselves during the workshpos. For example, the “+” and “-” markers on Google Map are not intuitive either nor is the concept of zooming in and out. How are you supposed to understand that pressing these buttons still shows the same map but at a different scale and not an entirely different picture instead? Again, when I took a moment to think about this, I realized how completely confusing that could be. And again I kicked myself. But contrast this to an entirely different setting, San Francisco, where some friends recently told me how their five year old went up to a framed picture in their living room and started pinching at it with his fingers, the exact same gestures one would use on an iPhone to zoom in and out of a picture. “Broken, broken” is all the five year old said after that disappointing experience.

The final example actually comes from Haiti where my colleague Chrissy Martin is one of the main drivers behind the Digicel Group’s mobile banking efforts in the country. There were of course a number of expected challenges on the road to launching Haiti’s first successful mobile banking service, TchoTcho Mobile. The hurdle that I had not expected, however, had to do with the pin code. To use the service, you would enter your own personal pin number on your mobile phone in order to access your account. Seems perfectly straight forward. But it really isn’t.

The concept of a pin number is one that many of us take completely for granted. But the idea is often foreign to many would-be users of mobile banking services and not just in Haiti. Think about it: all one has to do to access all my money is to simply enter four numbers on my phone. That does genuinely sound crazy to me at a certain level. Granted, if you guess the pin wrong three times, the phone gets blocked and you have to call TchoTcho’s customer service. But still, I can understand the initial hesitation that many users had. When I asked Chrissy how they overcame the hurdle, her answer was simply this: training. It takes time for users to begin trusting a completely new technology.

So those are some of the assumptions I’ve gotten wrong. I’d be grateful if readers could share theirs as there must be plenty of other assumptions I’m making which don’t fit reality. Incidentally, I realize that emerging economies vary widely in technology diffusion and adoption—not to mention sub-nationally as well. This is why having the iLab in Liberia is so important. Identifying which assumptions are wrong in more challenging environments is really important if our goal is to use technology to help contribute meaningfully to a community’s empowerment, development and independence.

Part 6: Mobile Technologies and Collaborative Analytics

This is Part 6 of 7 of the highlights from “Illuminating the Path: The Research and Development Agenda for Visual Analytics.” Please see this post for an introduction to the study and access to the other 6 parts.

Mobile Technologies

The National Visual Analytics Center (NVAC) study recognizes that “mobile technologies will play a role in visual analytics, especially to users at the front line of homeland security.” To this end, researchers must “devise new methods to best employ these technologies and provide a means to allow data to scale between high-resolution displays in command and control centers to field-deployable displays.”

Collaborative Analytics

While collaborative platforms from wiki’s to Google docs allow many individuals to work collaboratively, these functionalities rarely feature in crisis mapping platforms. And yet, humanitarian crises (just like homeland security challenges) are so complex that they cannot be addressed by individuals working in silos.

On the contrary, crisis analysis, civilian protection and humanitarian response efforts are “sufficiently large scale and important that they must be addressed through the coordinated action of multiple groups of people, often with different backgrounds working in disparate locations with differing information.”

In other words, “the issue of human scalability plays a critical role, as systems must support the communications needs of these groups of people working together across space and time, in high-stress and time-sensitive environments, to make critical decisions.”

Patrick Philippe Meier

Mobile Spying Software Sophistication

Computerworld New Zealand reports that spying programs for mobile phones are likely to grow in sophistication and stealth as the business around selling the tools grows.

There is increasing evidence that money from selling the tools will create a stronger incentive for more accomplished programmers to get into the game, which could make the programs harder to detect. The prediction follows what has happened with the malware writers in the PC market. Many hackers are now in the business of selling easy-to-use tools to less technical hackers rather than hacking into PCs themselves.

One of the latest tools on the market is Mobile SpySuite, which some believe is the first spy tool generator for mobiles. It sells for US$12,500. The number of mobile spyware programs pales in comparison to the number of such programs available for PCs. However, mobile spying programs are harder to track, since security companies don’t see as many samples circulating on the internet as they do of malicious software for PCs.

Some of the more well-known spy programs are Neo-call and FlexiSpy. Neo-call is capable of secretly forwarding SMS (Short Message Service) text messages to another phone, transmitting a list of phone numbers called, and logging keystrokes. FlexiSpy has a neat, web-based interface that shows details of call times, numbers and SMSes, and it can even use a phone’s GPS (Global Positioning System) receiver to pinpoint the victim’s location.

I’m not too worried though, SecureSMS would have those forwarded SMS texts encrypted. And besides, as SpySuite increases it’s market share, this will increase customer demand for tighter data security. Companies like CellTrust will move in and offer anti-spying tools. And so on, and so on. In other words, we’re likely to see the dynamic observed vis-a-vis PCs, i.e., the basic dynamic of evolutionary biology: adaptation.

Patrick Philippe Meier