Usefulness to social changes
Each of these inventions, and countless others—from refrigerators and sewing machines to telephones, typewriters, and cameras—eventually settled into the mainstream of society and unleashed massive political, social, and practical changes. They became things that people use in their daily life—and to a large extent take for granted.
Innovators –> Adopters –> Laggards
The earliest adopters are referred to as innovators; the second phase is named early adopters; then come the masses followed by the laggards. This model still holds true, though over the last couple of decades the life cycle has accelerated at warp speed.
Humans and machine interaction
In the 1990s researchers theorized how human and machine could weave together a completely new form of communication and interaction via machines.
At the same time, RFID technology has matured, sensor technology has leapt forward, miniaturization has accelerated, and computer software has taken a giant leap forward. The convergence of these technologies—along with nearly ubiquitous wireless networks and cloud computing—has introduced the concept of robotic insects and animals, nanobots and microbots that can exist inside humans, and drone fleets that can accomplish tasks in the sky above.
Privacy and security
It could also create significant political and social problems by, among other things, contributing to a growing disconnect between people. It will certainly cause society to more closely examine the notion of privacy and security.
Insights with technology
In fact my router now displays a total of 19 wireless clients—each with an IP address—including computing devices, media players, home automation gear, and more. Many of these devices rely on mobile apps and all connect to the Internet of Things. For better or worse, these connected devices eliminate manual tasks and deliver entirely new ways to access digital content; gain insights; and manage locks, doors, lights, and thermostats.
IP and TCP
Born out of research on packet-based networks during the 1950s, the original ARPAnet (Advanced Research Projects Agency Network) had evolved from its humble introduction in 1969 into a far more robust Internet Protocol (IP) network (IP, along with Transmission Control Protocol, or TCP, serves as the protocol for establishing a virtual connection between devices or systems).
Over the last several years a variety of systems and platforms have emerged based on IP. In fact IP is now the standard conduit for communication, entertainment, shopping, business transactions, and an array of other tasks and activities.
Many many other devices
In the meantime these things are taking new shapes and forms. It’s no longer only computers and smartphones that connect to the Internet. The list includes parking meters, thermostats, health monitors, fitness devices, traffic cameras, tires, roads, locks, supermarket shelves, environmental sensors, even livestock and trees.
Physical-first vs Digital-first
Two basic types of connected objects exist: physical-first and digital-first, according to a May 2014 briefing paper from ABI Research, Internet of Things vs. Internet of Everything: What’s the Difference? The former consist of objects and processes that do not typically generate or communicate digital data unless augmented or manipulated whereas the ones belonging to the digital-first domain are capable of generating data, and communicating it on for further use, inherently and by design.”
Cons of physical-first objects
While many physical-first objects can be tagged using digital tools and technologies, such as RFID, they typically do not provide the same level of data and a similar level of insight. For instance, a marketer can track the way a reader uses and reads an e-book by studying every click and tap.
When an RFID chip is within range of the reader, it automatically sends a signal and data to a computer. Passive RFID is particularly compelling because it doesn’t require a power source, the tags can function for twenty years or longer, and they cost only a few cents each. A passive tag pulls the necessary power from a nearby reader.
Different types of communication
Within the Industrial Internet, communication typically takes place in three different ways: machine to machine (M2M), human to machine (H2M), and machine to smartphone (M2S) or other device, such as a tablet.
Different types of data
the Internet of Things or IoT, alters the equation from human-based data input to both human- and machine-based data input. While most data on the Internet currently takes the form of text files, messages, audio, photographs, and video files, the IoT grabs new and different data, it combines data in different ways and it allows humans and machines to gain broader and deeper insights.
Conventional diagrams of the Internet include servers and routers and so on, but they leave out the most numerous and important routers of all: people. The problem is, people have limited time, attention and accuracy — all of which means they are not very good at capturing data about things in the real world.
Networks and systems
It creates new types of networks and systems—and entirely different pathways for data, information and knowledge to travel. Along the way, and with the right input and analysis, computers and humans can decipher the codes that dictate the physics of the planet and various events.
IoT in infancy
The ideas are limited only by human imagination and creativity. Because the IoT is still in its infancy, there are many technical and engineering issues to tackle, including developing better and longer lasting batteries for mobile devices, building smaller devices and packing more sensors into existing smartphones and other devices, identifying ways to embed sensors in everything from clothing to machinery, perfecting miniaturization, developing better algorithms to sort through all the data and keep the signal-to-noise ratio low, and developing standards and platforms that enable data sharing and widespread compatibility.
Smartphone in 1993, mainstream in 2003, innovative and easy to use in 2007-2013
It wasn’t until the 1990s—with the advent of modern cellular technology and smaller and lighter handsets—that mobile phones began to filter into the mainstream of society. The first attempt to build a digital smartphone came from IBM in 1993.
One thing that distinguishes connected devices is that they can continuously report about usage, operating behavior, conditions, and other information. Simply put: they generate a lot of data that can be analyzed and acted upon.
Combining many fields
Some disciplines—namely fields such as astronomy, meteorology, oil and gas exploration, and engineering—have long relied on huge datasets to solve problems and build models. The IoT exponentially increases the number of data sources along with the volume, velocity, and variety of data. Suddenly it’s not only about computers collecting and generating data and storing the data in tidy databases. The IoT encompasses satellites, parking meters, vending machines, television sets, point-of-sale terminals, gas pumps, food packages, household appliances, light switches, restrooms, and supermarket shelves.
Today’s smartphones can already “hear” and “feel” at a basic level. They possess built-in microphones, cameras, GPS chips, accelerometers, gyroscopes, and other sensors that can act and react to a wide range of environmental factors and conditions. Together, they create far more intelligence in the device and transform it from a phone into a multifunction computer that transforms our world.
Using Bluetooth, near-field communication (NFC), RFID, and other wireless technologies, researchers are also exploring the use of nanosensors and optical fibers to peer inside collapsed buildings, industrial machinery, and the human body. There’s further a growing focus on networks of smart objects or sensors—possibly numbering in the millions or billions—that interact with each other and behave in a context-aware manner.
Some refer to this connected business world as Industry 4.0, alluding to the fourth wave of disruptive industrial innovation (previous waves include mechanization, mass production, and the introduction of computers and electronics), or simply smart industry or smart manufacturing.
Physical and digital worlds
But both share the common goal of blending and blurring the physical and virtual worlds as well as the distinctions between human and machine in order to generate far greater intelligence than any single machine or device can produce.
Putting a price to information
Information technology consulting firm Gartner in fact predicts that information assets and data will appear on the balance sheets of corporations within the next few years.
The predictable pathways of information are changing: the physical world itself is becoming a type of information system. … These networks churn out huge volumes of data that flow to computers for analysis. When objects can both sense the environment and communicate, they become tools for understanding complexity and responding to it swiftly.
The data derived from a connected physical world could also extend to physical infrastructure and public safety. With connected bridges, tunnels, and roadways it’s suddenly possible to understand when a structure is approaching a state of failure. This makes it much easier to prioritize risks and repairs. What’s more, with the right software and dashboard in place, it’s possible to view data across an entire physical infrastructure.
They are able to detect overheated axel bearings, wheel damage, vibration problems, and other issues as trains whiz past at full speed. “We are able to take the equipment out of use before major damages occur,” says Lennart Andersson, RFID project manager.
Changing system and pricing
In addition a vast network of sensors can provide immediate feedback about changing conditions. This is particularly valuable for managing limited or scarce resources, such as energy or water. A growing number of utilities are in fact introducing smart meters that track and display real-time consumption patterns. These meters also provide tools for viewing variable rates and taking advantage of nonpeak pricing. In the future smart utility grids would allow homeowners and businesses including large data centers that consume vast amounts of electricity to tap into sophisticated algorithms to optimize usage, save energy, and trim costs.
Today’s automobile and airplane collision avoidance systems which produce audible alarms and in some cases take corrective action are an example of AI in action. However, in the future these capabilities will continue to advance.
Too often in the past, various systems and devices did not communicate or play nicely with one another. What’s more, without clouds that make sharing and syncing data far less complicated, fast and seamless data sharing simply wasn’t possible.
Setting up device
Setting up the device is fairly simple and straightforward. A user enters the manufacturer and model number of the unit, the software checks a database and automatically programs the remote and then sets it up all the devices to operate in harmony with one another.
Later, the firm adapted the X10 interface to work with personal computers. Although the X10 protocol demonstrated what was possible using home automation, it never took off and, over the years, has drifted into relative obscurity on the home automation front. It was simply too expensive and too clunky.
The platform, which uses 128-bit encryption to protect data, can transmit signals through intermediate ZigBee devices to reach more distant devices—thus creating a mesh network (where all devices or nodes can relay data to the network). This makes ZigBee best suited for applications that use low data rates and only intermittent transmissions.
$100s of dollars instead of $1000s
However, a new breed of systems typically costing hundreds or a few thousand dollars rather than hundreds of thousands of dollars is now entering the picture. Moreover these systems are becoming smarter, cheaper, more interconnected, and better.
Further into the future, autonomous vehicles will likely navigate smart road networks and respond to traffic congestion and other issues by automatically rerouting traffic for optimal capacity and speed. These systems would also allow cars to follow closer to one another and thus increase the capacity of roads.
Mass transit vs ownership
The way we think about cars could change dramatically in the years ahead. Self-driving cars could create more of a mass transit mindset rather than the current ownership model.
Beyond the social and psychological ramifications, there are a number of technical and practical tripping points. Among them: interruptions to physical Internet access, component failures within systems, software bugs that generate errors and noise, data sharing across systems and organizations, coping with proprietary and competing systems, and dealing with upgrades, patches, and obsolescence.
The start of making sense
Although much of the plumbing for the Internet of Things is already in place ubiquitous and pervasive communications networks, sensors that can detect activities and events in the surrounding environment, and computers that can sift through massive amounts of data and transform bits and bytes into information and knowledge society is only beginning to connect devices in any meaningful way.
Not just automation
The real gains from connected devices do not derive from using a smartphone app to start a car’s engine or adjust the temperature in a house via the web. It’s when vast networks of devices share data and put the data to work in ways that push past evolutionary gains and into the revolutionary category.
Just as proprietary networking protocols from the likes of IBM, Novell, Bay Networks, Cisco Systems, and others, eventually vanished in favor of a common standard, Internet Protocol (IP), proprietary, and closed IoT systems must eventually give way to a more open environment in order for society to realize the maximum benefits. Businesses that cling to proprietary products eventually discover they are at risk of becoming irrelevant or obsolete.
World of proprietary IoT
Likewise, in a proprietary IoT world filled with islands of connected devices, it’s next to impossible for a homeowner to manage a collection of lights, security devices, a thermostat, lock systems, a garage door, and other machines and gadgets from a central app or control panel.
Already some companies are reaping enormous productivity gains and cost savings by switching on connected devices and systems. Global aircraft manufacturer Airbus, for example, has developed a smart factory system that makes it possible to track tools, logistics media, and wing production in real time using RFID. Among other things, the system provides insight into steps, processes, and workflows that contain inefficiencies. It also makes it possible to locate tools and equipment at any given moment. The firm already tracks more than 3,000 parts per plane using passive RFID tags along with other technology.
Not engineering, but making sense of it
The biggest challenges associated with incorporating sensors into the IoT isn’t so much in engineering new capabilities from breathalyzers in smartphones to RFID tags that can detect rancid food or detect minute concentrations of explosives in public places, it’s building the smart systems that can accumulate the data, sort through it instantly and validate results in the specific context of a situation.
Context-aware sensing capabilities—driven by the next generation of software and algorithms—would change the way machines operate and people view and use personal devices.
Examples of urban use cases
The same types of gains are possible in the industrial sector. Indeed they are already beginning to take shape. In Finland, for example, sensors in trash bins now send a message to a truck when a pickup is required. This has led to a 40 percent savings in waste collection costs. In Nice, France, a smart parking system alerts drivers about open spots on a real-time basis. The system has already reduced traffic congestion and CO2 emissions.
Context-aware computing types:
In a May 2013 research paper published in IEEE Communications Surveys and Tutorials, Charith Perera, Arkady Zaslavsky, and Dimitros Georgakopolous6 point out that context-aware computing takes the form of three types of interaction:
- personalization, which revolves around a user setting preferences and systems responding to them accordingly (e.g., programming a home automation system);
- passive context-awareness, where a system monitors the environment and offers appropriate options to users (e.g., receiving a coupon when entering a store);
- active context-awareness, where a system continuously monitors an environment or situation and acts autonomously (e.g., if a system detects a gas leak, it automatically notifies the utility that a problem exists).
By connecting it to the Internet, weather data could be used to adjust watering levels based on whether rain is forecast. But the same system connected across a city could further improve forecasting, water management, and utility costs. Rather than each system optimizing conditions independently, the entire network of homes and businesses operates together, and thus more efficiently.
Human factors experts refer to this as the “automation paradox.” As automated systems become increasingly reliable and efficient, the more likely it is that human operators will mentally “switch off” and depend on the automated system. And as the automated system becomes more complex, the odds of an accident or mishap may diminish, but the severity of a failure is often amplified.
Motorists, airplane pilots, and train operators are all prone to becoming overly reliant on automated systems and growing more complacent about using their skills and alertness to avoid dangerous situations. Worse, designers sometimes rely on a wrong set of assumptions or an incomplete universe of facts to build a system.
Human error == forced to act like machines
In fact Norman, one of the world’s leading design experts, argues that machine logic doesn’t always jibe with the human brain. “If you look at ‘human error’ it almost always occurs when people are forced to think and act like machines,” he warns.
UX in IoT
The history of technology is littered with mediocre user interfaces, arcane operating controls, and performance failures. The maturation of any technology takes time, tweaking, adjusting, and fixing. Consider it no surprise, then, that home automation and connected devices have been around in one form or another for more than a quarter century.
Single failure or systemic failure
It’s one thing for a single connected vehicle to malfunction. It’s entirely another for an entire transportation network to fail. The latter would result in massive gridlock and widespread collisions—along with injuries, fatalities, widespread chaos, and severe economic consequences.
Novelty of technology vs staleness
Moreover the novelty of any new technology eventually wears thin. What was at first fresh and exciting eventually becomes mundane, even bothersome or oppressive. A good example is e-mail, which is a growing burden for many people. Today many recipients find themselves buried under piles of messages and a heavy dose of spam and malware.
Not all technology experts and economists agree. Many point out that the same problems occurred during the transition into the industrial age during the late 1800s and early 1900s. Some amount of disruption and displacement is painful but healthy, they argue. However, it’s important to recognize that the Internet of Things dwarfs past technology advances. As self-serve technologies accelerate, automation takes hold, robots advance, and nanotechnology moves from the realm of science fiction to science fact, it’s apparent that society is hitting a tipping point where humans are engineering our own obsolescence in a great many areas.
Data generated and insights
The ability to peer into the spaces between objects, people, and other things, is just as profound as the objects themselves. The data generated by the IoT will provide deep insights into physical relationships, human behavior, and even the physics of our planet and universe. Real-time monitoring of machinery, people, and the environment creates a model for reacting to changing conditions and relationships—faster, better, and smarter.
IoT in Medicine
It’s virtually impossible to find a piece of paper anywhere in the facility. Doctors transfer files and information to pharmacies and patients electronically. What’s more, it’s possible to locate the nearest device or medical equipment because everything is tagged with RFID and visible on the network. It’s also possible to track blood supplies and other essential items in real time and anticipate when there’s a need to place an order.
Challenges in living with IoT
John and Mary are likely to encounter numerous other systems during the course of a day and into the evening. They might also have to deal with annoyances and problems, such as privacy settings and potential fraud within their e-payment system. But their lives will certainly be far different than ours today. Technology systems will be more deeply and broadly woven into their daily existence.
Saving natural disasters
Connected devices will also lead to safer and better vehicles, industrial machines, and perhaps even an ability to predict earthquakes, floods, and other events. Likewise far more energy-efficient and environmentally sound practices will take shape in our homes and businesses.