breakdown of IoT functionality, from Deloitte. They give 5 general types of services that IoT “things” can do:
Internal state: Heartbeat- and ping-like broadcasts of health, potentially including diagnostics and additional status reporting (for example, battery level, CPU/memory utilization, strength of network signal, up-time or software/platform version).
Location: Communication of physical location via GPS, GSM, triangulation or proximity techniques
Physical attributes: Monitoring the world surrounding the device, including altitude, orientation, temperature, humidity, radiation, air quality, noise and vibration
Functional attributes: Higher-level intelligence rooted in the device’s purpose for describing business process or workload attributes
Actuation services: Ability to remotely trigger, change or stop physical properties or actions on the device.
Examples of IoT in action
There are some pretty well-known IoT products that some of you already use, including:
Nest Thermostat (and others). These allow you to control your AC from your phone, anywhere that you can connect to the Internet.
Smart lights: Same concept, but for lights. You can turn lights on/off from your phone. Phillips Hue is an example of this
Bluetooth Trackers – Tile (https://www.thetileapp.com/) is an example of a Bluetooth Tracker. Put one on that thing you always lose (i.e., car keys). The next time you lose those keys, you can find them again via an app on your phone.
Smart Home appliances – things like Google Home, Amazon Echo, and Apple HomeKit.
Smart power switches – Belkin’s Wemo Insight Wi-Fi Smart Plug is an example. They let you turn the plug (and therefore anything connected to it) on and off, set schedules for the plug, monitor energy consumption and use, etc. You can also connect it to Amazon Alexa and Google Home for hands-free voice control
Health and exercise trackers – Fitbits “fit” into this category, too.
How does IoT affect libraries?
Here are some ways libraries are already incorporating IoT technology into their libraries:
Smart Building Technology: As libraries retrofit their buildings with newer technology (or build new buildings/branches), they are starting to see more IoT-based technology. For example, some libraries can can adjust heating, cooling and lights from a smartphone app. Some newer building monitoring and security systems can be monitored via mobile apps.
RFID: RFID technology (sensors in books) is a type of IoT technology, and has been around for awhile.
Beacon Technology: There are at least two library-focused companies experimenting with Beacon technology (Capira Technologies and Bluubeam).
People counters: Check out Jason Griffey’s Measure the Future project. Here’s what he says about Measure the Future: “Imagine having a Google-Analytics-style dashboard for your library building: number of visits, what patrons browsed, what parts of the library were busy during which parts of the day, and more. Measure the Future is working to make that happen by using open-hardware based sensors that can collect data about building usage that is now invisible. Making these invisible occurrences explicit will allow librarians to make strategic decisions that create more efficient and effective experiences for their patrons.”
Library classes! Libraries are also teaching classes about the Internet of Things. These include classes focused on introducing patrons to IoT technology, and classes that focus on an aspect of IoT, like a class on making things with Arduinos or how to use your new Fitbit.
By 2020 more than 50 billion things, ranging from cranes to coffee machines, will be connected to the internet. That means a lot of data will be created — too much data, in fact, to be manageable or to be kept forever affordably.
One by-product of more devices creating more data is that they are speaking lots of different programming languages. Machines are still using languages from the 1970s and 80s as well as the new languages of today. In short, applications need to have data translated for them — by an IoT babelfish, if you will — before they can make sense of the information.
Then there are analytics and data storage.
security becomes even more important as there is little human interaction in the flow of data from device to datacentre — so called machine-to-machine communication.
a report from ISACA, a nonprofit association focused on knowledge and practices for information systems. The 2017 State of Cyber Security Study surveyed IT security leaders around the globe on security issues, the emerging threat landscape, workforce challenges and more.
53 percent of survey respondents reported a year-over-year increase in cyber attacks;
62 percent experienced ransomware in 2016, but only 53 percent have a formal process in place to address a ransomware attack;
78 percent reported malicious attacks aimed at impairing an organization’s operations or user data;
Only 31 percent said they routinely test their security controls, while 13 percent never test them; and
16 percent do not have an incident response plan.
65 percent of organizations now employ a chief information security officers, up from 50 percent in 2016, yet still struggle to fill open cyber security positions;
48 percent of respondents don’t feel comfortable with their staff’s ability to address complex cyber security issues;
More than half say cyber security professionals “lack an ability to understand the business”;
One in four organizations allot less than $1,000 per cyber security team member for training; and
About half of the organizations surveyed will see an increase in their cyber security budget, down from 61 percent in 2016.
IoT to Represent More Than Half of Connected Device Landscape by 2021
But it gets even more interesting when virtual and augmented reality meet the Internet of Things
when Second Life began, there was a lot of interest, but the toolset was limited — just because of the timeframe, not that the toolset wasn’t a good one for that period. But, things matured. I think it was, in particular, the ability to work in HD that improved things a lot. Then came the ability to bring in datasets — creating dashboards and ways for people to access other data that they could bring into the virtual reality experiment. I think those two things were real forces for change.
A dashboard could pop up, and you could select among several tools, and you could get a feed from somewhere on the Internet — maybe a video or a presentation. And you can use these things as you move through this hyper reality: The datasets you select can be manipulated and be part of the entire experience.
So, the hyper reality experience became deeper, richer with tools and data via the IoT; and with HD it became more real.
We can’t deny the fact that curriculum and the way we teach is becoming unbundled. Some things are going to happen online and in the virtual space, and other things will happen in the classroom. And the expense of education is going to drive how we operate. Virtual reality tools, augmented reality tools, and visualization tools can offer experiences that can be mass-produced and sent out to lots of students, machine to machine, at a lower cost. Virtual field trips and other kinds of virtual learning experiences will become much more commonplace in the next 5 years.
My note: I listened to the report in my car yesterday. It is another sober reminder for being proactive rather then reactive (or punitive). We must work toward digital literacy and go beyond that comfortably numb stage of information literacy.
An Experiment Shows How Quickly The Internet Of Things Can Be Hacked
We have basic security in place in modern devices that screen out the most obvious attacks. Really getting phished, if you will, is more of a problem where you are tricked in surrendering your password or username to a common service. If you plug in your webcam into your router or to your Wi-Fi, you’re relatively safe.
I think the biggest security concern for folks at home would be if their router actually is old, it might have an easily guessed password that someone could gain control. Most modern devices don’t have that problem, but that certainly is a concern for older devices.
The first step to becoming an IoT Product Manager is to understand the 5 layers of the IoT technology stack.
Devices constitute the “things” in the Internet of Things. They act as the interface between the real and digital worlds.
2. Embedded software
Embedded software is the part that turns a device into a “smart device”. This part of the IoT technology stack enables the concept of “software-defined hardware”, meaning that a particular hardware device can serve multiple applications depending on the embedded software it is running.
Embedded Operating System
The complexity of your IoT solution will determine the type of embedded Operating System (OS) you need. Some of the key considerations include whether your application needs a real-time OS, the type of I/O support you need, and whether you need support for the full TCP/IP stack.
This is the application(s) that run on top of the embedded OS and provide the functionality that’s specific to your IoT solution.
Communications refers to all the different ways your device will exchange information with the rest of the world. This includes both physical networks and the protocols you will use.
4. Cloud Platform
The cloud platform is the backbone of your IoT solution. If you are familiar with managing SaaS offerings, then you are well aware of everything that is entailed here. Your infrastructure will serve as the platform for these key areas:
Data Collection and Management
Your smart devices will stream information to the cloud. As you define the requirements of your solution, you need to have a good idea of the type and amount of data you’ll be collecting on a daily, monthly, and yearly basis.
Analytics are one of they key components of any IoT solution. By analytics, I’m referring to the ability to crunch data, find patterns, perform forecasts, integrate machine learning, etc. It is the ability to find insights from your data and not the data alone that makes your solution valuable.
The Internet of Things is all about connecting devices and sharing data. This is usually done by exposing APIs at either the Cloud level or the device level. Cloud APIs allow your customers and partners to either interact with your devices or to exchange data. Remember that opening an API is not a technical decision, it’s a business decision.
This is the part of the stack that is most easily understood by Product teams and Executives. Your end-user applications are the part of the system that your customer will see and interact with. These applications will most likely be Web-based, and depending on your user needs, you might need separate apps for desktop, mobile, and even wearables.
The Bottom Line
As the Internet of Things continues to grow, the world will need an army of IoT-savvy Product Managers. And those Product Managers will need to understand each layer of the stack, and how they all fit together into a complete IoT solution.
As the cost of sensors and the connectivity necessary to support those sensors has decreased, this has given rise to a network of interconnected devices. This network is often described as the Internet of Things and it is providing a variety of information management challenges. For the library and publishing communities, the internet of things presents opportunities and challenges around data gathering, organization and processing of the tremendous amounts of data which the internet of things is generating. How will these data be incorporated into traditional publication, archiving and resource management systems? Additionally, how will the internet of things impact resource management within our community? In what ways will interconnected resources provide a better user experience for patrons and readers? This session will introduce concepts and potential implications of the internet of things on the information management community. It will also explore applications related to managing resources in a library environment that are being developed and implemented.
Education in the Internet of Things Bryan Alexander, Consultant;
How will the Internet of Things shape education? We can explore this question by assessing current developments, looking for future trends in the first initial projects. In this talk I point to new concepts for classroom and campus spaces, examining attendant rises in data gathering and analysis. We address student life possibilities and curricular and professional niches. We conclude with notes on campus strategy, including privacy, network support, and futures-facing organizations.
What Does The Internet of Things Mean to a Museum? Robert Weisberg, Senior Project Manager, Publications and Editorial Department; Metropolitan Museum of Art;
What does the Internet of Things mean to a museum? Museums have slowly been digitizing their collections for years, and have been replacing index cards with large (and costly, and labor-intensive) CMS’s long before that, but several factors have worked against adopting smart and scalable practices which could unleash data for the benefit of the institution, its collection, and its audiences. Challenges go beyond non-profit budgets in a very for-profit world and into the siloed behaviors learned from academia, practices borne of the uniqueness of museum collections, and the multi-faceted nature of modern museums which include not only curator, but conservators, educators, librarians, publishers, and increasing numbers of digital specialists. What have museums already done, what are they doing, and what are they preparing for, as big data becomes bigger and ever more-networked? The Role of the Research Library in Unpacking The Internet of Things Lauren di Monte, NCSU Libraries Fellow, Cyma Rubin Fellow, North Carolina State University
The Internet of Things (IoT) is a deceptively simple umbrella term for a range of socio-technical tools and processes that are shaping our social and economic worlds. Indeed, IoT represents a new infrastructural layer that has the power to impact decision-making processes, resources distribution plans, information access, and much more. Understanding what IoT is, how “things” get networked, as well as how IoT devices and tools are constructed and deployed, are important and emerging facets of information literacy. Research libraries are uniquely positioned to help students, researchers, and other information professionals unpack IoT and understand its place within our knowledge infrastructures and digital cultures. By developing and modeling the use of IoT devices for space and program assessment, by teaching patrons how to work with IoT hardware and software, and by developing methods and infrastructures to collect IoT devices and data, we can help our patrons unlock the potential of IoT and harness the power of networked knowledge.
Lauren Di Monte is a Libraries Fellow at NC State. In this role she develops programs that facilitate critical and creative engagements with technologies and develops projects to bring physical and traditional computing into scholarship across the disciplines. Her current research explores the histories and futures of STEM knowledge practices.
I’m not sure if the IoT will hit academic with the wave force of the Web in the 1990s, or become a minor tangent. What do schools have to do with Twittering refrigerators?
Here are a few possible intersections.
Changing up the campus technology space. IT departments will face supporting more technology strata in a more complex ecosystem. Help desks and CIOs alike will have to consider supporting sensors, embedded chips, and new devices. Standards, storage, privacy, and other policy issues will ramify.
Mutating the campus. We’ve already adjusted campus spaces by adding wireless coverage, enabling users and visitors to connect from nearly everywhere. What happens when benches are chipped, skateboards sport sensors, books carry RFID, and all sorts of new, mobile devices dot the quad? One British school offers an early example.
New forms of teaching and learning. Some of these take preexisting forms and amplify them, like tagging animals in the wild or collecting data about urban centers. The IoT lets us gather more information more easily and perform more work upon it. Then we could also see really new ways of learning, like having students explore an environment (built or natural) by using embedded sensors, QR codes, and live datastreams from items and locations. Instructors can build treasure hunts through campuses, nature preserves, museums, or cities. Or even more creative enterprises.
New forms of research. As with #3, but at a higher level. Researchers can gather and process data using networked swarms of devices. Plus academics studying and developing the IoT in computer science and other disciplines.
An environmental transformation. People will increasingly come to campus with experiences of a truly interactive, data-rich world. They will expect a growing proportion of objects to be at least addressable, if not communicative. This population will become students, instructors, and support staff. They will have a different sense of the boundaries between physical and digital than we now have in 2014. Will this transformed community alter a school’s educational mission or operations?
The jigsaw classroom is a research-based cooperative learning technique invented and developed in the early 1970s by Elliot Aronson and his students at the University of Texas and the University of California. Since 1971, thousands of classrooms have used jigsaw with great success.
Divide students into 5- or 6-person jigsaw groups.
The groups should be diverse in terms of gender, ethnicity, race, and ability.
Appoint one student from each group as the leader.
Initially, this person should be the most mature student in the group.
Divide the day’s lesson into 5-6 segments.
For example, if you want history students to learn about Eleanor Roosevelt, you might divide a short biography of her into stand-alone segments on: (1) Her childhood, (2) Her family life with Franklin and their children, (3) Her life after Franklin contracted polio, (4) Her work in the White House as First Lady, and (5) Her life and work after Franklin’s death.
Assign each student to learn one segment.
Make sure students have direct access only to their own segment.
Give students time to read over their segment at least twice and become familiar with it.
There is no need for them to memorize it.
Form temporary “expert groups” by having one student from each jigsaw group join other students assigned to the same segment.
Give students in these expert groups time to discuss the main points of their segment and to rehearse the presentations they will make to their jigsaw group.
Bring the students back into their jigsaw groups.
Ask each student to present her or his segment to the group.
Encourage others in the group to ask questions for clarification.
Float from group to group, observing the process.
If any group is having trouble (e.g., a member is dominating or disruptive), make an appropriate intervention. Eventually, it’s best for the group leader to handle this task. Leaders can be trained by whispering an instruction on how to intervene, until the leader gets the hang of it.
At the end of the session, give a quiz on the material.
Students quickly come to realize that these sessions are not just fun and games but really count.