Listening for Mosquitos

The ubiquitous mobile phone has opened many possibilities for citizen science. With most citizens equipped with a phone, and many with small supercomputers in the purse or pocket, it is easier than ever to collect data from wherever humans may be.

These devices are increasing the range of field studies, enabling the identification of plants and animals by sight and sound.

One key, of course, is the microphones and cameras. Sold to be used for deals and dating, not to mention selfies, these instruments are outstripping what scientists can afford.

The other key is that mobile devices are connected to the Internet, so data uploads are trivial. This technology is sold for commerce and dating and for sharing selfies, but it is perfect for collecting time and location stamped data.

In short, the vanity of youngsters has funded infrastructure that is better than scientists have ever built. Sigh.


This fall the Stanford citizen science folks are talking about yet another crowd sourced data collection: an project that identifies mosquitos by their buzz.

According to the information, Abuzz works on most phones, including older flip phones (AKA, non-smart phones).

It took me a while to figure out that Abuzz isn’t an app at all. It is a manual process. Old style.

You use the digital recording feature on your phone to record a mosquito. Then you upload that file to their web site. This seems to be a manual process, and I guess that we’re supposed to know how to save and upload sound files.

The uploaded files are analyzed to identify the species of mosquito. There are thousands of species, but the training data emphasized the important, disease bearing species we are most interested in knowing about.

A recent paper reports the details of the analysis techniques [2]. First of all, mobile phone microphones pick up mosquito sounds just fine. As we all know, the whiny buzz of those varmints is right their in human hearing, so its logical that telephones tuned ot human speech would hear mosquitos just fine.

The research indicates that the microphone is good in a range of up to 100mm. This is pretty much what you would expect for a hand held phone. So, you are going to have to hold the phone up to the mosquito, just like you would pass it to a friend to say hello.

At the crux of the matter, they were able to distinguish different mosquitos from recordings made by phone. Different species of mosquito have distinct sounds from their wing beats, and the research showed that they can detect the differences from these recordings.

They also use the time and location metadata to help identify the species. For example, the geographic region narrows down the species that are likely to be encountered.

The overall result is that it should be possible to get information about mosquito distributions from cell phone recordings provided by anyone who participates. This may contribute to preventing disease, or at least alerting the public to the current risks.

This project is pretty conservative, which is an advantage and a disadvantage. The low tech data collection is great, especially since the most interesting targets for surveillance are likely to be out in the bush, where the latest iPhones will be thin on the ground.

On the other hand, the lack of an app or a plug in to popular social platforms means that the citizen scientists have to invest more work, and get less instant gratification. This may reduce participation. Obviously, it would be possible to make a simple app, so that those with smart phones have an even simpler way to capture and upload data.

Anyway, it is clear that the researchers understand this issue. The web site is mostly instructions and video tutorials, featuring encouraging invitations from nice scientists. (OK, I thought the comment that “I would love to see is people really thinking hard about the biology of these complex animals” was a bit much.

I haven’t actually tried to submit data yet. (It’s winter here, the skeeters are gone until spring). I’m not really sure what kind of feedback you get. It would be really cool to return email a rapid report (i.e., within 24 hours). It should say the initial identification from your data (or possibly ‘there were problems, we’ll have to look at it), along with overall statistics to put your data in context (e.g., we’re getting a lot of reports of Aegyptus in your part of Africa).

To do this, you’d need to automate the data analysis, which would be a lot of work, but certainly is doable.

I’ll note that this particular data collection is something that cannot be done by UAVs. Drones are, well, too droney. Even if you could chase mosquitos, it would be difficult to record them over the darn propellers. (I won’t say impossible—sound processing can do amazing things).

I’ll also note that this research method wins points for being non-invasive. No mosquitos were harmed in this experiment. (Well, they were probably swatted, but the experiment itself was harmless.) This is actually important, because you don’t want mosquitos to selectively adapt to evade the surveillance.

  1. Taylor Kubota, Stanford researchers seek citizen scientists to contribute to worldwide mosquito tracking, in Stanford – News. 2017.
  2. Haripriya Mukundarajan, Felix Jan Hein Hol, Erica Araceli Castillo, and Cooper Newby Using mobile phones as acoustic sensors for high-throughput mosquito surveillance. eLife. doi: 10.7554/eLife.27854 October 11 2017,

The Psychology of the Supernatural

This month Kathryn Schulz writes a lovely little essay in the New Yorker about “Fantastic Beasts and How to Rank Them” [1]. As a member of the original International Society of Cryptozoology, as well as life long fan of fictional worlds of all kinds, I enjoyed her summary of recent psychological research on how people think about “impossible” things.

As the title implies, some of this research examines how people reason about imaginary entities and situations. Is a Yeti more or less “impossible” than a vampire? Is levitation more or less impossible than becoming invisible? And so on.

The interesting thing for psychologists is that even though people may agree that something is imaginary and pretty much impossible in the real world, we can not only imagine it, but imagine the world that it exists in.

Of course, imagining the not (yet) real is the heart of creativity of all kinds, so no one should be surprised that people do it. And imagining how a not-yet-real think would really work is the crux of both invention and story telling.

The recent psychological work has worked to tie this imagination with intuitive physics, the unscientific scientific rules that people learn about how the world works. AKA, “commonsense”. For example, objects do not change into other objects. Big objects are generally heavier than little objects. Stuff like this.

Schulz discusses recent experiments that sort through different sets of these rules as they apply to imaginary animals and situations. Essentially, the concept of “impossible” can be broken down into a range of ways that things are impossible. Some things are “impossible” in many, many ways (such as Hollywood vampires or time travel). Others are actually possible, but just not actually factual (such as Yetis or visitors from outer space).

As she notes, at least from what people say in psychology experiments, there is often strong agreement on such decisions. This is very interesting because it offers a glimpse into what and how people learn about the world. These imaginary cases shed light on everyday reasoning about the real and the possible.

As is often the case, psychologists would benefit from walking across the quad to talk with some Anthropologists about this topic.

Schultz hints as some of the cultural variation that can be found in the world. Almost everyone has grown up with tales of ghosts, but the details are different in different traditions. Hollywood has blurred folk cultures with its own super-cultural mish-mash, but Chinese ghosts and vampires are still quite different from English and Transylvanian entities.

These differences are due to the critical role of story telling. Humans like to tell stories,which tie up events, causes, and effects into a coherent narrative. Stories give explanations for random and inexplicable events, and describe the world at a human level.

(Perhaps the key innovation in all of “science” is that it uses a different kind of story, one that isn’t human centered, includes randomness, and is not judged by whether people like the story or not. Stories, yes. But not just any story.)

Many “impossible” animals and situations are known to us through stories, not through experience.  When people are judging Yeti vs.. Dracula they are working from folk tales, not from scientific journals or personal experience. These stories may be based in cognitive illusions (e.g., ideas about disembodied souls) and intuitive physics, but mostly they reflect the motives and anxieties of the society they come from.

Hollywood vampires are scientifically improbable for sure, but some of their features are obviously ideological. Setting aside the evident deep, deep anxieties about the seduction of young women, Hollywood vampires are associated with demonic forces, and are supposed to be allergic to crucifixes and holy water as much as sunlight and silver. These traits is obviously Christian propaganda, painted onto folk tales about revenents. And, by the way, the supposed effects  of a cross on a Vampire is just as plausible or implausible as your beliefs in holy water, crucifixes, and exorcism—which is a whole different psychological question.

Taking verbal reports as indications of folk-science also misses the key point that many such tales have become symbols of specific cultural identity. Endorsing Bigfoot, Biblical literalism, and the everyday influence of demons and angels may be as much about asserting cultural solidarity (or resistance), as a literal claim of truth. This has nothing to do with reason and evidence, and everything to do with personal identity.

I may say that Bigfoot is more likely than Zombies, but maybe that’s reflecting my preference in popular TV shows, and the sub-cultures they reflect.  This belief is social signalling, not pseudo-scientific reasoning about the world.

Finally, I’ll suggest that the psychologists and new anthropologist friends toodle across the quad again, over to the business and law school. Over in that part of campus, the boffins operate in the most dangerous fantasy world of all, one that believes that humans are rational creatures with common sense.

We aren’t. We are fabulists, who believe absurd stories about the world all the time. Any theory that doesn’t take that as an axiom is just plain broken.

  1. Kathryn Schulz, “Fantastic Beasts and How to Rank Them”. The New Yorker.November 6 2017, Conde Nast.


Book Review: “Righteous” by Joe Ide

Righteous by Joe Ide

Yay! I’ve been waiting to hear more from Joe Ide about this young latter-day Holmes, IQ, who is one of my favorite new characters from 2016.

Righteous picks up where IQ left off. IQ is still serving his ‘hood as a low-cost private investigator in the hood, helping folks and righting wrongs. He very smart, but has not really recovered from the loss of his brother. In his twenties, he hasn’t really grown up, has few friends and fewer plans.

In this story, IQ is called upon to help a friend’s sister who is in serious trouble in Las Vegas. This leads into deep and dangerous trouble, confronting Chinese human trafficking gangs and home-grown loan sharks.

At the same time, IQ becomes convinced that the hit and run that killed his brother was murder rather than accident. If so, who did it, and why? Unraveling this mystery puts him in yet more dangerous conflict with local criminals and gangs.

And, if this weren’t enough, IQ is growing up, working through friendship with Dodson and the possibility of romance.

We’re worried about you, kid. You’re smart and good-hearted, but so, so young for the responsibilities you take on.

This is a great novel, with real life settings, but also some larger than life characters. And, like all good stories, it’s deeply human and humane. These are beautiful people, trying to be good and do good.

Who can read this without wanting to emulate IQ?

It is clear that we’ve not heard the last of IQ. I, for one, am ready for the next installment of this remarkable guy.

  1. Joe Ide, Righteous, New York, Little, Brown and Company, 2017.


Sunday Book Reviews

What is Coworking? It’s More Diverse Than You Might Think

It is frequently observed that Coworking Spaces, like the Tech Industry, seems pretty, well, undiverse.

For example, Lori Kane commented, [4]

it hit me immediately: almost everyone in the space was young and white” (and mostly male). This was “not at all what the walk through the diverse neighborhood primed me to expect.

Similar sentiments have been expressed by many people.

At the same time, coworkers frequently perceive their own workplace to be diverse, and, indeed, the diversity of fellow workers is seen to be one of the principle benefits of a coworking space (e.g., [5, 8, 9]).

What is going on here?

For one thing, there are many different ways to be “diverse”. Kane notices the visible demographics of the space, especially compared to the city around it. Others are more focused on the range professional and technical skills in the room.

A second caveat is that any given coworking space has only so many workers, and generally draws a group “like-minded” workers. But there are many coworking spaces, with different membership, and no single workplace represents all coworking spaces or coworkers.

Atypical Entrepreneurs”

Sean Captain wrote last year in Fast Company about “A Growing Movement Of Coworking Spaces For Atypical Entrepreneurs” [1].  He writes about the emergence of “work spaces with public-service missions”. These operations may be not-for-profit, or for-profit B-corps, and may have a variety of members. The common theme is serving a social mission rather than pure profit.

Captain views this as a “new” trend, but coworking has had this strain of social mission from the beginning (e.g., the Centre for Social Innovation [9], Make Shift Boston [6], or EnSpiral Space [3]). But he does find that this concept is holding its own amid “mainstream, big-city coworking spaces like those in the WeWork empire” and their clones.

Besides a social mission, these spaces are also emphatically local.

Captain quotes Robbie Brown of WELabs [12] (located in Long Beach), “we’re drawing in membership from the community here rather than so much attracting outside folks into the area,” As Kane suggested, the local group is ”less threatening than walking into a coworking space and seeing a bunch of white guys in dress shirts, their faces in computers and typing away.

Captain mentions similarly local work spaces in Raleigh, NC,  Detroit, and other cities.

Again, the emphasis on serving a local community has been a key to coworking from the beginning. Indeed, the gigantic, one-size-fits all WeWork-Seats2Meet-NextSpace style of “consumer coworking” is a recent development. In the beginning, all coworking was “authentic”, local coworking, and there are plenty of locally oriented (but not necessarily social mission oriented) work spaces, such as The Harlem Collective [10], The Shift [11], Nebula [7], or CoHoots [2]).

In addition to demographic diversity (or perhaps, demographic locality), these small, low profit operations generally attract a variety of “non-traditional” businesses. He notes a variety of occupations and businesses, including healthcare, small manufacturing, and community development projects.

Again, these businesses aren’t as new and ground-breaking as Captain seems to believe–there have been similar community development projects for a century or more in most places. But, again, in recent years the big chains and business schools have promulgated a picture of what entrepreneurs are like, and what they do.

Captain does raise the interesting point that the leadership of these social mission spaces isn’t itself particularly diverse. This is embarrassing, smacking of cultural colonization, but also a matter of access to funding and know-how. Obviously, the next wave of “authentic local coworking” must be locally run and led.

My own view is that coworking has never been as homogeneous or, indeed, “corporate” as the business school version.

More important, coworking is all about community, and about the community feeling of comfortable solidarity and mutual support. Large scale operations may offer consistent, low cost services, but no one community “vibe” will please everyone.

If coworking is to persist and grow, it will need to recruit more and more diverse workers. This will require creating and sustaining communities that attract and nurture new workers, including people who do not aim to “move fast and break things”. (“Move steadily forward and fix things together”?)

For this reason, I view the future of coworking as a patchwork of many spaces, each locally led and connected to it’s location. Authentic, home style, workspaces?

“Even more diverse.”

  1. Sean Captain, Inside A Growing Movement Of Coworking Spaces For Atypical Entrepreneurs, in FastCompany – Leadership. 2016.
  2. CoHoots. CoHoots Coworking. 2017,
  3. Enspiral. Enspiral Space. 2015,
  4. Kane, Lori, Tabitha Borchardt, and Bas de Baar, Reimagination Stations: Creating a Game-Changing In-Home Coworking Space, Lori Kane, 2015.
  5. Liquid Talent, Dude, Where’s My Drone: The future of work and what you can do to prepare for it. 2015.
  6. Make Shift Boston. Make Shift Boston. 2016,
  7. Nebula. Nebula Coworking St. Louis. 2017,
  8. Olma, Sebastian, The Serendipity Machine: A Disruptive Business Model for Society 3.0. 2012.
  9. The Centre for Social Innovation. Culture | The Centre for Social Innovation. 2016,
  10. The Harlem Collective. The Harlem Collective. 2017,
  11. The Shift. The Shift – Home. 2017,
  12. Work Evolution Labs. Work Evolution Labs,. 2017,


What is Coworking

Note:  please stay tuned for my new ebook, “What is Coworking”, coming in 2017 Real Soon Now.

Semantic Aware Framework for 3D Tele-Immersion

One of the latest products from Sensei Klara Nahrstedt’s teleimmersion lab is Shannon Chen’s prize-winning thesis, “Semantics-Aware Content Delivery Framework for 3D Tele-Immersion[1].

Nahrstedt’s group has been developing 3D Tele-immersion (3DTI) technology for a decade or so. 3DTI allows “full-body, multimodal interaction among geographically dispersed users,” for a decade and more now.

Chen’s dissertation is about optimizing the trade-offs that are inherent in the end-to-end transmission of 3DTI. This is a recent refinement of the quality of service concepts this group has developed over many years.

The basic challenge is that 3DTI sucks CPU, memory, and bandwidth like crazy, and user experience suffers badly from latency or inadequate bit rates. Managing the network very critical, and very difficult.


Chen’s contribution is to introduce semantic information into the system, to manage resource usage and trade-offs, “to bridge the gap between high-level semantics and low-level data delivery”, specifically “by injecting environmental and user-activity semantic information “.

The thesis considers several aspects of 3DTI, capture, dissemination, and receiving. In each phase, resource limitations challenge the ability to deliver a satisfactory user experience.

The semantics to be considered are computing environment, activity, and user role. From a high level understanding of these, the system can tune performance at many levels.

The overall design is a set of modules that use the elements of the semantics to adjust the parameters of the 3DTI phases.

I’ll refer the reader to the dissertation for full details. Briefly,

  • Activity semantics are used to optimize data capture, helping identify the most important data based on the user’s task and behavior.
  • User semantics are used to optimize The user’s role is used to help identify the most important flows of data and required QoS.
  • Activity + Environment semantics are used to optimize The user’s environment determines his or her view point and also the capabilities of the local device.

The thesis reports on analysis of three prototypes for different use cases that emphasize these three types of optimization.

I note that these systems he tackled present very difficult technical problems. For example, the 3DTI is not only all around (i.e., multiple simultaneous video streams), it may include on body and other sensors (that must be synchronized with the video). 3DTI can be synchronous or asynchronous, and might need to be archived for analysis and replay.

In short, the data is diverse and voluminous, and generally needs to be synchronized. The trick, of course, is that there are slews of data that might be needed at any moment, but only some of it is actually needed at any particular time in a particular part of the system. The idea is to use semantics to deliver what is needed when and where it is needed, to improve the experience.

This is a nice piece of work. He hits on a lot of important themes.

For one thing, it shows again the importance of end-to-end design. In this case, his “semantics” come from the requirements and constraints on the whole system, from human to human, though many systems and links. In my view, he could have called it “An end-to-end framework….

I also endorse his call that:

we need a formalized scripting language to describe the dynamics in the cyber-physical regime to the digital computing entities” (p. 98)

Absolutely. (See McGrath (2003) [2] : – ), which is woefully out of date, but outlines the general idea.)

More generally, I think there is a lot of use for logical description languages which can combine both manual assertions (e.g., this user is a patient or is a doctor) and automated inferences (e.g., a doctor is likely to need to access archives at full resolution if possible). These systems can also (in principle) reason and produce inferences, e.g., suggestions about optimization based on perceived similarity previous sessions.

Dr. Chen is reportedly now working with a large social media company, so I’m sure his future systems could have access to slews of interesting metadata, including social networks, and histories of digital behavior.

Nice work.

  1. Chien-nan Chen, Semantics-Aware Content Delivery Framework for 3D Tele-Immersion, in Computer Science. 2016, University of Illinois, Urbana-Champaign: Urbana.
  2. Robert E. McGrath, Semantic Infrastructure for a Ubiquitous Computing Environment, in Computer Science. 2005, University of Illinois, Urbana-Champaign: Urbana.
  3. August Schiess, CS alumnus Shannon Chen receives SIGMM Outstanding PhD Thesis Award, in CS@Illinois – News. 2017.


Bitcoin is More Evil Than Ever

From the beginning, Nakamoto style cryptocurrency was intended to enable unimpeded flows of funds [2]. Cryptocurrencies are specifically designed to be the perfect mechanism for grey and black markets; for tax evasion and for money laundering of all kinds. While crypto-enthusiasts see this as a feature, most of civilized society views this as a serious bug.

In the short history of Bitcoin, we have seen it become a medium for illicit commerce and ransomware. (Even more-or-less legitimate uses, such as digital commerce are being highjacked by a flood of scams, including preposterous “initial coin offerings”, which might as well be called “tulipware”.)

It has become evident that Bitcoin has also become a favorite tool for human smuggling and human trafficking: modern day slave trade. I’m not seeing this as a good thing in any way at all.

As reported in Coindesk [1], this issue was highlighted by Joseph Mari of the Bank of Montreal at the The Pontifical Academy of Social Sciences, Workshop on Assisting Victims of Human Trafficking: Best Practices in Legal Aid, Compensation and Resettlement [4]. (It’s not often that I cite something “Pontifical” : – )) Mari reports that, as conventional financial services move to block illicit commerce, including human trafficking, criminals have moved to use Bitcoin to collect their illicit money.

Cryptocurrency enthusiasts are quick to point out that this is pretty much exactly how Bitcoin was designed to work: it is supposed to be immune to “censorship”. Other cynics like me would also point out that the wealthy get away with this stuff without resorting to frippery like Bitcoin. (See perhaps: England, Queen of, offshore accounts of.)

Of course, the original Nakamoto design was more than a little hacky, and it isn’t completely immune to interference by determined authorities. Companies make good money selling analytics that spot suspicious transactions and, with favorable winds and some luck, might nab some bad guys.

However, this mostly retroactive data mining is hardly adequate. Detecting this stuff after the fact doesn’t stop, prevent, or deter it.

Worse, the tiny successes so loudly touted are technically obsolete, as the dark web moves to far more opaque cryptocurrencies.

Mari is right to be concerned, and it is good to educate conventional banks and other authorities about this technology. But I’m really not sure that there is anything that can be done, at least until quantum computing takes it all down.

  1. Michael del Castillo, Vatican Address to Highlight Bitcoin Use in Slave Trade. Coindesk.November 2 2017,
  2. Satoshi Nakamoto, Bitcoin: A Peer-to-Peer Electronic Cash System. 2009.
  3. Darryn Pollock , Jamaican Police Take Aim at Human Traffickers’ Bitcoin Pockets, in Cointelegraph. 2017.
  4. The Pontifical Academy of Social Sciences, Workshop on Assisting Victims of Human Trafficking: Best Practices in Legal Aid, Compensation and Resettlement. 2017: Vatican City.


Cryptocurrency Thursday


More on Gita, Personal Cargo Bot

Earlier this year, I noted the interesting personal cargo bot, Gita (coming Real Soon Now?)

Development seems to be progressing, and the company released video of Gita in some more real world settings.

It seems to be working pretty well, at least in the “follow” mode.   Evan Ackerman points out “looks like they may have ditched that SLAM belt thing”.  I assume that they are using computer vision which is the basis for their navigation, but can also follow one target. (Their technology is not documented.)

Also, the video suggests that they have a nice, simple operation: stand “in front of the eyes” and press the “follow me” button. Then it follows (and presumably learns the route). I like that interface—it’s clear, and it’s real hard to hack.

In my earlier post, I commented that this plain, simple device is kind of cool, but very utilitarian. I still think there is a call for customization (everything is better with flames pained on it!) and unauthorized racing and acrobatic modifications.

Just how many Gitas can a (modified) Gita jump over? Show me a Gita that tips up and drives on one tire! And so on.

From earlier post :

“First of all, they simply have to come in different colors (duh!). Second, I strongly recommend the company encourage customization, including hand painted decorations, decal kits (e.g., flames, team logos), and even plastic and foam 3D decorations (Fins! Shark’s teeth! Ray gun pods!).

“Third, there should be (unsanctioned) modifications to hot rod them. 35 KMH? Not good enough!

“For that matter, there should be rodeos and shows, with trick jumps (I’m seeing flaming hoops), motocross, ski races, etc. For these Gita-X Games, it would be cool to be able to stream out the video, a la drone racing, no”

Finally, I still want to see similar behavior, but in a raptor-like bot. Cross Gita with, say Michigan’s Cassie, and you’ll really have a personal cargo bot!


Robot Wednesday

A personal blog.

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