Let us roll back to the 1970s first. In 1973, the first RFID device was patented. This device was the key enabling technology even if it does not look nor remind modern IoT devices. The low power (actually here passive) solution with a remote antenna large enough to collect energy from the electromagnetic field and power the device brought an idea of uniquely identifiable items. That somehow mimics well-known EAN barcodes and the evolution used nowadays, like QR codes, but every single thing has a different identity here. In contrast, EAN barcodes present a class of products, not an individual one. The possibility to identify a unique identity remotely became fundamental to the IoT as it's known today. RFID is not the only technology standing behind IoT. In the 1990s, the rapid expansion of wireless networks, including broadband solutions like cellular-based data transfers with their consequent generations, enabled connecting devices in various, even distant, geographical locations. Parallelly, an exponential increase in the number of devices connected to the global Internet network was observed, including the smartphone revolution that started around the first decade of the XXI century. On the hardware level, microchips and processors became physically smaller and more energy efficient yet offering growing computing capabilities and memory size increase, along with significant price drops. All those facts drove the appearance of small, network-oriented, cheap and energy-efficient electronic devices. In recent years, the development of efficient AI technologies has even boosted IoT applications.

The phrase “Internet of Things” was used for the first time in 1999 by Kevin Ashton – an expert on digital innovation. Formally, IoT was introduced by the International Telecommunication Union (ITU) in the ITU Internet report in 2005 ^[1]. The understanding and definitions of IoT have changed over the years, but now all agree that this cannot be seen as a technology issue only. According to IEEE “Special Report: Internet of Things” ^[2] released in 2014, IoT is:

It relates to the physical aspects of IoT only. The Internet of Things also addresses other aspects that cover many areas ^[3]:

• enabling technologies,
• software,
• applications and services,
• business models,
• social impact,
• security and privacy aspects.

IEEE, as one of the most prominent standardisation organisations, also works on standards related to the IoT. The primary document is IEEE P2413™ ^[4]. It covers the technological architecture of IoT as three-layered: sensing at the bottom, networking and data communication in the middle, and applications on the top. It is essential to understand that IoT systems are not only small, local-range systems. ITU-T has defined IoT as:

In the book ^[5] by the European Commission, we can read a similar description of what IoT is: “The IoT is the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment.” IoT impacts many areas of human activity: manufacturing, transportation, logistics, healthcare, home automation, media, energy saving, environment protection and many more. In this course, we will consider the technical aspects mainly.

In the IoT world, the “thing” is always equipped with some electronic element that can be as simple as the RFID tag, an active sensor sending data to the global network, or an autonomous device that can react to environmental changes. In CERP-IoT book “Visions and Challenges” ^[6] in the context of “Internet of Things” a “thing” could be defined as:

It is quite easy to find other terms used in the literature like “smart object”, “device”, or “nodes” ^[7].

One can imagine that almost everything in our surroundings is tagged with an RFID element. They do not need a power supply; they respond with a short message, usually containing the identification number. Modern RFID can achieve 6 to 7 meters of the range. Using the active RFID reader, we can quickly locate lost keys and know if we still have the butter in the fridge and in which wardrobe there is our favourite t-shirt.

If the “thing” includes the sensor, it can send interesting data about current conditions. We can sense environmental parameters like temperature, humidity, air pollution, pressure, localisation data, water level, light, noise, and movement. Using different methods and protocols, this data can be sent to the central collector that connects to the Internet and the database or cloud. There, the data can be processed, and Artificial Intelligence algorithms can be used to decide actions that could be taken in different situations. Active things can also receive control signals from the central controller to control the environment: turn on/off the heating or light, water flowers, and turn on the washing machine when there is enough sunlight to generate the required electricity or charge your electric car.

This thing does not even require the controller to make the proper decision. An autonomous vacuum cleaner can clean our house when it detects that we aren't home and the floor needs cleaning. The fridge can order our favourite beverage once the last bottle is empty.

Sensor Networks are a subset of the IoT devices used as a collaborative solution to grab data and send it for further processing. Opposite to the general IoT devices, Sensor Network devices do not have any actuators that can apply an action to the external world. The data flow is unidirectional, then.

IoT systems and embedded systems share almost the same domain. They frequently use the same microcontrollers, sensors and actuators, development software and even programming models. What differs between IoT and embedded systems is that IoT, on its principles, uses communication to send and receive data outside of its instance. Embedded systems do not have to be network-enabled or have a unique identity, while IoT devices do. Moreover, IoT systems are complex and multilayered, often introducing cloud-based parts, while embedded systems are stand-alone devices. Indeed, one can say that an IoT device is a network-enabled embedded system.

While the IoT, as a technical solution paradigm to certain problems, is relatively well understood and applied, it keeps evolving to address a more complex and diverse spectrum of tasks. It follows the trends of AI integration and advancement into hardware systems, providing close-to-problem AI capabilities - edge AI. Therefore, the new AI-enabled IoT systems provide low-latency intelligent solutions capable of online or offline training through applications of machine learning techniques. Regarding model flexibility, the microprocessors with dedicated AI co-processing or GPU (Graphical Processing Unit) have limited memory and processing speed; they significantly extend application possibilities. A good example is modern cell phones, capable of complex AI-drive tasks like photo or video editing, content generation, and other functions. The same techniques might be applied for real-time data analysis, decision-making and other IoT-specific applications.