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Rainbow Unit: Networks Big and Small

1A: Programmable Electronics, Smart Technology, and the Internet of Things

Background Knowledge Probe

  1. Create a spreadsheet with two columns and at least 20 rows.
  2. Take a few minutes to walk around your home, listing in the right column all the electronic devices you use on a regular basis.
  3. Review your list of devices and note in the left column which category you think each device belongs:
    1. Non-programmed circuit
      • Example from Orange Unit: 5 Volt resistor -> momentary switch -> light -> ground
    2. Programmable circuit(s), no connectivity to other devices
      • Example from Orange Unit: Using a momentary switch and Python on Raspberry Pi to turn LEDs on or off
      • Example from Blue Unit: Using a momentary switch and MakeCode on Circuit Playground Express to turn LEDs on or off
    3. Programmable circuit(s), data connectivity with one or more local devices only
      • Example from Blue Unit: Circuit Playground Express capacitive touch sensors informing which counterstory to play on the Raspberry Pi
    4. Programmable circuit(s), Internet connectivity providing remote information and/or control
      • Examples from Rainbow Unit to follow
  • Which of the items on your list are analog electronics? Which are digital electronics?
  • How many more devices would be added if the list were to include non-electronic, mechanical devices?

The Mechanical World

I wake up a little before the sun rises. I stand up and stretch, then walk out of the sleeping quarters and over to the outhouse with composting toilet. It’s light enough out now so my kerosene lantern isn’t needed, although it’s still a little dark in the outhouse. I start my campfire and 30 minutes later have some water boiling eggs and making some tea. The morning is first spent feeding and providing clean water to the chickens and washing clothes in the nearby stream before putting them out to dry. Then I take some time weeding in the garden while nibbling on the few first strawberries and snow peas of the season and picking the cold-tolerant spinach and kale greens of the spring garden. Getting out of the warming midday sun, I head into the woods to forage for mushrooms, ramps, dandelions, and nettles. Check on the clothes drying, catch a fish from the stream, make dinner over the fire or inside over the woodburning stove, turn on the lantern to read for a bit, and back to bed I go.

The romance of time in a mechanical world!

While I have and continue to live with a wide range of daily-use electronic devices for lighting, heating and air conditioning, cooking and cleaning, and the other staples of modern life, I come from a long family line who also keep a hold on the mechanical side of life in a range of ways. And I have a family who continues this tradition in our own ways. While we don’t live off-grid in a tiny house producing and preserving all our own food and resources, we continually explore and periodically test ideas from local rural and urban farmers and foragers.

At the same time, we’re a family who uses the Internet to explore resources such as Mother Earth News and Bryce Langston and Rasa Pescud’s Living Big in a Tiny House YouTube Channel to expand our understanding of the balance between mechanical and electronic, off-grid and on-grid, physical community and the larger online communities of practice. I’m someone who writes code, designs and builds electronics, has facilitated setup of a number of local networks and helped explore a couple community networks, and consulted on Internet choices, while also using a wide range of electronic and mechanical woodworking tools.

I live in a family and in communities that flex between the both/and of the mechanical and electronic, of the analog and digital, of the in-person and online.

From Mechanical to Programmable to “Smart”

For purposes of this discussion, we’ll consider mechanical devices as those involving pure physical processing. A common style of toilet within the United States flushes because we push down on a physical component that adjusts other physical components, thereby allowing water to leave a tank and flow through the toilet bowl. The water flows in an effective manner to remove liquid and solid waste through the physical porcelain S-shaped siphon, designed to remove wastes while physically protecting sewer gas from venting back into the room after the flush cycle has completed. Together, this represents a classic mechanical technology.

While we continue to make use of a range of mechanical devices as part of our daily lives, we have increasingly made use of electronic devices as the latter half of the 19th century experienced the advancement of electrical power generation and the eventual emergence of electrical engineering. We’ve moved from the building of wax candles or gas-soaked wicks in lanterns as a source of lighting to the incandescent light bulb providing an electrical device in which the flow of electricity can pass through a wire filament embedded within glass. More recently, we’ve seen the transition from the incandescent light bulb to light-emitting diode lamps, or LEDs, that use significantly less energy to achieve equal brightness and with greater longevity. Each of these represent simple non-programmed circuits.

But it many cases it is possible to expand the circuit to include additional components. The simple LED circuit can be constructed so as to include the necessary resistors, capacitors, transistors, and photocells such that it automatically dims or brightens depending on the amount of light currently within the area. This can be designed as a non-programmed circuit, but often is incorporated into a microcontroller or microprocessor to control the brightness of the LED based on certain levels of light as sensed by the photocell. It is now a .

The programmable circuits can become increasingly complex, as when an LED only comes on at the appropriate brightness based on current light levels when movement is detected via an integrated motion sensor. It may include built-in switches or touch sensors that can be used to determine whether to make use of the dimming and/or motion sensing functions of the program. Depending on the technology being used, it’s possible that as we observe our own or others’ uses of the technology, our behaviors are shaped by the choices being made in that use. And it may be that we begin shaping our choices to further shape behavior. The electronic devices continue on as artifacts. Over time, the programs running some of our electronic devices were further expanded to incorporate code that altered the actions of other segments of the code based on previous data collection by that software. To begin, code can be combined with a mathematical model using initial “training data” to create predictive decisions. Over time, machine learning are set up such that the software learns from new data in ways that help set up more precise predictions and corresponding actions.

The predictive analytics of machine learning has emerged from the broader exploration known as . Programming languages such as LISP started emerging in the late 1950s, helping to advance the field of AI that was also emerging at the time. As with other programming languages, AI makes active use of “if-then” Boolean logic statements, or increasingly newer Fuzzy logic with a continuum between 0 and 1, to create a knowledge base that is then used by an inference engine to draw deductions. Autonomous devices with software facilitating perception of its environment and execution of actions that maximize chances of achieving target goals are formally referred to as within AI, and popularly as today.

It might be helpful to more quickly review the Blue Unit chapter 2A: The Methodological Landscape to more fully consider the Positivist Paradigm within which the deductive logic of AI. While essential, work within the Positivist Paradigms, including machine learning and AI, are insufficient to investigate the full spectrum of data, information, knowledge, and wisdom within the information sciences. It is important to also use inductive reasoning to develop interpretive understandings of complex social phenomena, and a dialectical approach to knowledge that enables people to see hidden forms of control, domination and oppression. Only in this way is it possible to enable people, and especially those in the margins, to seek change and reform existing conditions and social order.

In their 1997 article, “An Overview of Smart Technology,” Goddard, Kemp, and Lane noted that the term “smart” for a diverse range of materials, structures, systems and technologies originated in the early 1980s, mainly via researchers working in the United States and funded through defense budgets. It was the reports of “smart” bombs and other “smart” munitions of the Gulf war in newspapers and popular science journals that brought about public awareness. From this emerged the fashionable use of “smart” technologies as part of industrial applications well beyond the original aerospace and defense uses that began in the early 1980s. Thus, while “intelligent agents” were already being developed at about the same time as part of various dedicated research groups, these academics “had been working on ‘smart’ technologies for several years without realising it!”[1]

Intelligent or smart systems include: 1) sensors used to collect associated information on environment, condition, or operating history; 2) a trainable control algorithm to read sensor data, draw inferences on that data, and alter system characteristics based on these inferences; 3) control hardware interconnecting arrays of sensors, a microprocessor running the algorithmic code, and actuators; 4) the actuators, or mechanical devices that can move or control something and thereby implement the change in configuration based on the control algorithm; and 5) structural members allowing the sociotechnical artifact or system of artifacts to perform its primary function.

Take 11 minutes to watch this deeper exploration of machine learning & artificial intelligence introduction from Carrie Anne Philbin’s Crash Course Computer Science series hosted by PBS Digital Studios:

Bringing this together, each of these terms and concepts, from circuits that are mechanical or programmable, to sociotechnical artifacts and systems, to artificial intelligence and intelligent agents, and to smart devices and technologies is shaped by and shapes individual people, scientific disciplines, research funding resources and their governmental, corporate, and non-profit funders, journalists and popular media, and many other social, cultural, political, and economic influencers. As the previous sentence is complex, so too is each individual word within it. But only in acknowledging the complexity is it possible to meaningfully enter into true works of liberation of all direct and indirect stakeholders seeking advancement of their individual and communal valued beings and doings.

Bringing Together Sociotechnical Artifacts into an Internet of Things

As we’ve seen in the Blue Unit, it is possible to bring together microcontroller-based programmed sensors with microcomputer-based processing software using data communications cables such as our UART serial cable. This can be very effective for connecting the microcontroller to the microcomputer as a single device. But a difficulty arises as control algorithms work to facilitate interdevice internetworking—that is, to facilitate two or more devices working with each other, whether or not interdevice internetworking code incorporates artificial intelligence functions and thus formally serves as intelligent agents. From farming to the home to the office cubicle to the library shelves, a growing number of independent, small microcontroller/microcomputer sociotechnical artifacts are capturing and routing volumes of data between devices. The code on these devices, while much smaller than centralized cloud computing devices and services, can be very effective at the rapid collection and analysis of data.

If we had computers that knew everything there was to know about things—using data they gathered without any help from us—we would be able to track and count everything, and greatly reduce waste, loss and cost. We would know when things needed replacing, repairing or recalling, and whether they were fresh or past their best.

Kevin Ashton, “That ‘Internet of Things’ Thing”[2]

It is here that the open protocols and processes of the Internet serve an essential role, leading researchers such as Neil Gershenfeld and others to formally advance an Internet of Things (IoT), allowing myriad devices to intercommunicate and interoperate.[3] The initial IoT concept could incorporate, but did not require, use of broadband connectivity to support much of its functionality. Key is the recognition that the circuits and software, even including a Web server, can be brought together on very low-cost microcomputers. While our educational-focused toolkit includes a $35 USD Raspberry Pi and $25 USD Circuit Playground Express, along with a range of other materials, it’s possible to build various everyday devices for as little as $1 USD. Alarmingly, many of our smart devices today are really not intelligent agents, but rather basic data gathering devices that use the Internet to communicate with proprietary controllers located in the “Cloud,” storing (and often taking ownership of) data and the information emerging from this data. Management and use of data and information of sensors, which include both known and unknown input from consumers in many cases, is determined by the commercial providers, and then returned to the devices to be implemented. Devices are indirectly interconnected via cloud platforms and software, divorced from the interdevice interconnectivity envisioned within an Internet of Things. Such conflicting meanings also appear in terms such as “smart grid,” “smart homes,” and “smart cities.”

Neil Gershenfeld provides an excellent introduction to the opportunities and challenges of this sociotechnical space within this four-minute segment of a World Sciences Festival panel, on which one of the “fathers of the Internet,” Vint Cerf, also sat, and who joins in some humorous bantering at the start:

For Neil Gershenfeld and the team at the Center for Bits and Atoms, this has meant bringing together the computer and physical sciences to explore how to turn data into things and things into data, by creating location fabrication facilities, Fab Labs, and a global network for training people and sharing knowledge, a Fab Academy, thereby digitizing fabrication in the same way that we digitized communication over the last two decades. In so doing, the purpose is to shift the focus from plumbing and power to safety and convenience, from pills to proper medication. To do this, it requires shifting focus to the local edges rather than a centralized cloud, exploring the boundaries between the digital and physical worlds.[4] Over the last five decades, the digital revolutions of computing and communication have transformed the world by enabling unprecedented productivity, and have catalyzed remarkable changes in everyday life while also providing opportunities for enormous wealth generation. But with the exciting possibilities for some people have come the exclusion and downward impacts for others. As Neil Gershenfeld, Alan Gershenfeld, and Joel Cutcher-Gershenfeld note in their 2017 book Designing Reality: How to Survive and Thrive in the Third Digital Revolution:

The negative aspects of the first two digital revolutions are not simply accidents. Nor were they driven by some unseen hand. Decisions made (and not made) and priorities set (and not set) early on, as the technologies were being developed and introduced to the market, have had lasting effects. We built breakthrough digital communication capabilities, but we failed to build in cultural norms, feedback loops, and algorithms that could have reinforced civil discourse. We created incredibly efficient new models of digital commerce, but have also introduced new threats to privacy and security. We value the advances made possible with digital automation, even as we struggle with impacts of lost jobs due to technology. (p. 5)

For the Gershenfelds and others within the community of the Fab Lab movement, this third, fabrication revolution brings together the virtual world of bits and the physical world of atoms in innovative ways in which we can find another chance to shape our societies. Digital fabrication provides new possibilities for enabling self-sufficient local communities beyond dependency on the centralized cloud of today. In so doing, it also opens up potentials for global sustainability for everyone, rather than just the fortunate few.

Gartner is a global research and advisory firm that has developed the Gartner Hype Cycle model to inform its customers, senior leaders across the enterprise, regarding technology hype versus commercial viability. This can be another helpful way to more broadly recognize the ongoing shaping and reshaping of sociotechnical artifacts over an extended period. Initially, innovation of emerging technologies leads to early proof-of-concept stories and increasing publicity of a product. However, as this often still requires further research and development, increasing wide use of the product can lead to a “Peak of Inflated Expectations” as success stories begin to be accompanied by increasing stories of failure. In many cases, interest continues to wane until the product reaches a “Trough of Disillusionment.” Only through ongoing development and testing do we reach a “Slope of Enlightenment” leading to a “Plateau of Productivity.” View the Gartner Top 10 Strategic Technology Trends for 2020 video to see an example of this methodology in practice, with indications that we are slowly moving from a BITNET of Things, as noted by Gershenfeld, to an increasing plateau of productivity that includes both the edge and the cloud, each in its own way.

Also compare the highlights within this 2020 Gartner Top 10 Strategic Technology Trends to their Press Release introducing the Top 10 Strategic Technology Trends for 2023, which adds to their optimize, scale, and pioneer themes that of sustainability.

“However, in 2023, delivering technology will not be enough. These themes are impacted by environmental, social and governance (ESG) expectations and regulations, which translate into the shared responsibility to apply sustainable technologies. Every technology investment will need to be set off against its impact on the environment, keeping future generations in mind. ‘Sustainable by default’ as an objective requires sustainable technology,” said David Groombridge, Distinguished VP Analyst at Gartner.

To consider the possibilities and pitfalls of the Internet of Things through a critical lens is to recognize the many seen, unseen, and unforeseen dangers, as Richard Milner brings forward in “Race, Culture, and Researcher Positionality.”[5] Furthermore, it is to question “Whose Culture Has Capital?”[6] as asked by Tara Yosso, a question that we explored at the end of the Blue Unit in chapter 4A: Sharing our Counterstories. It is essential that we continually bring not only our positivist and interpretive meta-theoretical assumptions, but also our critical meta-theoretical assumptions into the methodological landscape. For the alternative is to use the normative investigations based on deductive reasoning in its evaluations of our sociotechnical artifacts, such as the Turing test many have adopted to determine whether a computer running artificial intelligence software can “think.”[7]

Lesson Plan

Ultimately, choice between cloud services, local servers and server farms, or the Internet of Things and smart devices does not require either “this or that” decisions. In many cases, strategic decision making, design, and implementation may reveal that a combination of several different networked information systems is the ideal practical path to facilitate functional diversity in achieving valued beings and doings for the broadest range of stakeholders. The first objective of this session is therefore to introduce us to the concepts and terms, the technical components, and the sociotechnical codifications underlying these networked information artifacts and systems, helping advance the existence and sense of choice, as well as our ability to more effectively execute and achieve that choice to advance our valued beings and doings. While these activities can be done using many types of computers and server farms, we’ll make use of the Raspberry Pi computer throughout to especially advance a greater sense of the choices we do have but often are unaware of having given we are often directed into consumptive patterns of a specific product line. Indeed, some of these activities throughout this book using the Raspberry Pi have evolved from earlier works in communities for whom the sharing of data and information needed to be carefully controlled in acknowledgement that access beyond a room or a carefully controlled local area network could put an individual or groups life at risk. Low-cost Linux-based general-purpose computing devices can provide freedom and safety within environments in which individual or societal dangers otherwise would create barriers to liberating actions.

A second objective as we decodify these materials of this session then is to recognize that the data and information being collected is not just of things. It is often data and information about human and more-than-human persons and their activities. Individually and collectively, people have shaped the devices and systems which collect data and facilitate information processing for a range of objectives. In this process, we gather data on people’s actions and behaviors within various social and environmental contexts which we also are observing. How we reflect upon, investigate, and act upon this determines the form of power that is used: power within ourselves to advance our power over others, or power within others to advance power within all, to every extent possible. How the artifacts are shaped—and how we are shaped by them —also influences how we go on to shape things and persons alike. Considering how we can use our newly developing social justice storytelling skills within a data, information, knowledge, and wisdom pyramid to incorporate diverse wisdom in ways that advance knowledge in support of self-sufficient local communities and global sustainability for everyone is essential as we move forward within the information sciences.

As a reminder, the Lesson Plan found in the Introduction of the book, think of our travel through the many session of this book as pre-season training activities within a sports metaphor. Each is meant to strengthen a different aspect of ourselves and ourselves in relation to others. As with pre-season training, by the end of the Rainbow Unit we will have not reached the finish line, but rather the end of pre-season training. In entering the Rainbow Unit, use these four sessions to further advance a clearer and stronger person-centered community inquiry mindset and to also push even further within your action-reflection collective leadership practices to develop stronger muscle memory so that these methods are an active part of your daily practices as an information science professional moving forward.

Essential Resources:

Additional Resources:

Key Technical Terms

  • Terms associated with more complex , including ,  , , and
  • The major data transport layers of the , including the Physical & Data Link Layers, the Network Layer, the Session & Transport Layers, and the Application & Presentation Layers
  • The , and  standards that make up the core of the TCP/IP suite
  • The   and that together with the  make up the base components of the World Wide Web
  • Key concepts such as the Internet of Things, BITNET of Things, and

Professional Journal Reflections:

  1. Review your original list of devices from the opening Background Knowledge Probe. How does it need to be revised, if at all? Why or why not?
  2. In what ways do you have greater control than you previously thought over your devices? Less control? Why?
  3. How do we recodify the concepts, terms, and technologies of microcontrollers and microcomputers, of smart and intelligent devices, technologies, and systems, of the Internet of Things/Bitnet of Things, so as to advance a more just society for all, and especially for those marginalized and oppressed?

  1. N. D. R. Goddard, R. M. J. Kemp, and R. Lane, “An Overview of Smart Technology,” Packaging Technology and Science 10, no. 3 (1997): 129.;2-C.
  2. Kevin Ashton, “That ‘Internet of Things’ Thing,” RFID Journal, June 22, 2009,
  3. Neil Gershenfeld, Raffi Krikorian, and Danny Cohen, “The Internet of Things,” Scientific American, October 2004,
  4. Neil Gershenfeld and Jim Euchner, “Atoms and Bits: Rethinking Manufacturing,” Research-Technology Management 58, no. 5 (September 2015): 16–23.
  5. Milner, H. Richard. “Race, Culture, and Researcher Positionality: Working Through Dangers Seen, Unseen, and Unforeseen.” Educational Researcher 36, no. 7 (October 2007): 388–400.
  6. Tara J. Yosso, “Whose Culture Has Capital? A Critical Race Theory Discussion of Community Cultural Wealth,” Race Ethnicity and Education 8, no. 1 (March 2005): 75.
  7. Britannica, The Editors of Encyclopaedia. “Turing test”. Encyclopedia Britannica, 13 Mar. 2023, Accessed 13 April 2023.


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A Person-Centered Guide to Demystifying Technology, 2nd Edition Copyright © 2023 by Martin Wolske Copyright © 2023. Copyright “Ideating and Iterating Code: Scratch Example” © 2020 Betty Bayer and Stephanie Shallcross. Copyright “Introducing the Unix Command Line” © 2020 Martin Wolske, Dinesh Rathi, Henry Grob, and Vandana Singh. Copyright “Security and Privacy” © 2020 Sara Rasmussen. Copyright “Storytelling in the Information Sciences” © 2023 Yingying Han and Martin Wolske. This book is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License, except where otherwise noted.

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