The emergence of low cost and easy to use do-it-yourself boards such as Arduino and Raspberry Pi have paved the way for an unprecedented boom in creativity among technology and application enthusiasts. Most of these enthusiasts are would-be developers and undergraduate students with an idea for creating a design, who often are limited in the necessary underlying technical know-how and experience but are willing to learn as they are doing.
No less profound and far reaching is the impact DIY hardware platforms have had on the domain experts. In addition to working engineers with expertise in a particular market segment, this category includes the graduate students and professors at universities and technical institutes. Rather than wile away months and even years on the electronic implementation details of getting a particular domain experiment going, such projects sometimes take only a few months using DIY boards.
My fascination with these specialists comes out of my experience at California Institute of Technology, where my job was defined as staff writer for the PR group and the alumni magazine. But I was also often called on to help grad students, post docs, and professors write articles about their research for popular science magazines, as well as to work with them on grant proposals and other documentation on their research projects.
In that context I saw first-hand how the lack of the right equipment and expertise, much of it computer-based, prolonged the time just to get to the point of actually doing the experimental work. Due mainly to the necessary "implementation details," before DIY boards it could be years before the actual experimental work could get started.
When I worked at Caltech in the 1970s, the age of microprocessors and microcontrollers had just started. The domain experts I worked with had to beg, borrow, or steal the appropriate computer hardware by sharing a mainframe, borrowing an unused minicomputer such as a DEC PDP or a Data General machine, or building their own using the bipolar, NMOS, PMOS, and CMOS MSI and SSI "bit slices" for Arithmetic Logic Units, registers and various digital signal processing functions as barrel shifters. Single chip microprocessors such as Intel’s 4040 and Motorola’s 6800 were still too primitive and did not have the processing power needed in most such projects.
As microprocessors and their software support in the form of the C-language and programming tools have become more common and powerful, the implementation details have taken less time. But with DIY boards such as Raspberry Pi and Arduino, the cost and the time to get a project to the point of collecting useful data has been reduced drastically. Now it is a matter of only weeks or months, not years. Instead of major grants to get started research projects can often be funded out of pocket by the researcher and a few friends and family, maybe some grad students interested in the project, or by crowd-funding on the Web.
Not only have the number of projects increased, the time required to complete projects has been drastically shortened. Using the regular online search engines, I find a couple of dozen academic research projects using DIY boards described each month. It’s clear that the combination of low cost and ease of implementation is opening up a range of projects for researchers that were not possible before, as well as funding possibilities beyond the traditional university and governmental grants. Here are just a few of the hundreds of recent such DIY-board based research projects that caught my attention:
Cloud services on the cheap. Researchers at Glasgow University have built a scale model for cloud computing infrastructure research using plastic Leggo Bricks and Raspberry Pi boards. The PiCloud test bed is used to study such things as the economics of provisioning, application scheduling, and resource discovery. Composed of 56 Raspberry Pi's, it cost about $2000, about 50 times lower than that for an X86-based implementation.
A $45 all-purpose mobile electrochemical detector.A team of researchers at the University of California, Berkeley, have built uMed, an Arduino-based petrochemical tester for use in tandem with a mobile phone. They use it for remote and low-cost collection and transmission to a cloud based servers of a range of analyses for personal and public health, clinical, food safety, and environmental monitoring.
Measuring mechanical vibrations in physics experiments. Researchers in the department of physics and astronomy at Uppsula University have used an Arduino-based board in combination with dual MEMS accelerometers to measure mechanical vibrations so that they can be eliminated and factored into the design of the measurement equipment for their experiments.
Plant phenotyping with a Raspberry Pi. To replace the largely manual methods of identifying the genotype (genetic structure) of new plant species by their appearance (phenotype), researchers at the IMT Institute for Advanced Studies in Luca, Italy, have developed a low-cost, automated method of visual analysis of plants using a Raspberry Pi-based board to study multiple plants growing in a laboratory test plot.
These are just a sampling of recent university research projects that now use DIY board platforms. Such projects cover the entire spectrum of knowledge domain specialties: social sciences, biology, genetics, climate, oceanography, nuclear physics, medicine, communications, and engineering disciplines of all sorts.
With government funding of research already going down, will this make it possible for universities and technical institutes to do more with less? Or will the use the of low cost of DIY boards be used as an excuse to reduce funding further? Or will Web-enabled crowd-funding of basic research, now still relatively rare, become the norm? What are the legal ramifications of such research? Who owns it? Who controls it? If it has both government funding and crowdfunding, who is top dog? It will take time for answers to these questions to become clear.
One thing I do know for sure: now, I would not be able to do work on as many projects at a time as I did when I worked at Caltech years ago. I was usually involved in five or six projects at a time because of the months or years it took to pull together and build the equipment for collecting data. Those hurry-up-and-wait stalled periods gave me plenty of wiggle-room in terms of multitasking my time. That would be impossible today, given the dramatically narrowed time it now takes to get a project to the point at which a researcher can get useful data.
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