UNIT 2
Fundamental IoT Mechanism & Key Technologies
Identification of IoT objects and services
Object and service identification is recognized as one of the main challenges on the way to developing global Internet of Things (IoT). In this chapter we present the current State of the Art and research trends in the area of identification and access methods for IoT objects. We describe existing IoT identification technologies, which already have practical applications, such as IPv6 addressing, EPC, ucode and HIP. We also provide an overview of solutions investigated by research projects, where two main research trends can be distinguished. The first one are advanced methods for objects discovery based on semantic web, and the second one aims to improve efficiency of IoT systems by introducing additional identifier layer. In summary, we foresee that future 5G IoT will be based on IPv6 in general, due to immensity of devices and services existed in the current Internet, with islands of non-IP solutions dedicated for specific purposes.
Structural aspects of the IoT
The IoT represents a hybrid architecture, which means it can contain different subsystem architectures. In most cases, the IoTsystems are formed by two management architectures: event-driven and time-based. Event-driven architecture sensors transmit data when they sense activity in the external
environment, for example, an alarm is triggered if the door is opened at night time. In the time-based architecture, its components continuously transmit data within a certain interval (e.g., climate control system sensors once per second read room temperature). The latter usually work repeatedly after a pause, which can be adjusted separately for each device or set up within a central management system that will send queries to endpoint devices and sensors after a period of time. One such system solution is being offered by Intel Corporation. The IoT represents a hybrid architecture, which means it can contain different subsystem architectures. In most cases, the IoT systems are formed by two management architectures: event-driven and time-based. Event-driven architecture sensors transmit data when they sense activity in the external environment, for example, an alarm is triggered if the door is opened at night time. In the time-based architecture, its components continuously transmit data within a certain interval (e.g., climate control system sensors once per second read room temperature). The latter usually work repeatedly after a pause, which can be adjusted separately for each device or set up within a central management system that will send queries to endpoint devices and sensors after a period of time [3]. One such system solution is being offered by Intel Corporation.The IoT represents a hybrid architecture, which means it can contain different subsystem architectures. In most cases, the IoT systems are formed by two management architectures: event-driven and time-based. Event-driven architecture sensors transmit data when they sense activity in the external
environment, for example, an alarm is triggered if the door is opened at night time. In the time-based architecture, its
components continuously transmit data within a certain interval (e.g., climate control system sensors once per second read room temperature). The latter usually work repeatedly after a pause, which can be adjusted separately for each device or set up within a central management system that will send queries to endpoint devices and sensors after a period of time [3]. One such system solution is being offered by Intel Corporation.The IoT represents a hybrid architecture, which means it can contain different subsystem architectures. In most cases, the IoT systems are formed by two management architectures: event-
driven and time-based. Event-driven architecture sensors transmit data when they sense activity in the external environment, for example, an alarm is triggered if the door is opened at night time. In the time-based architecture, its components continuously transmit data within a certain interval
(e.g., climate control system sensors once per second read room
temperature). The latter usually work repeatedly after a pause, which can be adjusted separately for each device or set up within a central management system that will send queries to endpoint devices and sensors after a period of time [3]. One such system solution is being offered by Intel Corporation.The IoT represents a hybrid architecture, which means it can contain different subsystem architectures. In most cases, the IoT systems are formed by two management architectures: event-driven and time-based. Event-driven architecture sensors transmit data when they sense activity in the external environment, for example, an alarm is triggered if the door is opened at night time. In the time-based architecture, its components continuously transmit data within a certain interval
(e.g., climate control system sensors once per second read room
temperature). The latter usually work repeatedly after a pause, which can be adjusted separately for each device or set up within a central management system that will send queries to endpoint devices and sensors after a period of time [3]. One such system solution is being offered by Intel Corporation
The IoT represents a hybrid architecture, which means it can contain different subsystem architectures. In most cases, the IoT systems are formed by two management architectures: event-driven and time-based. Event-driven architecture sensors transmit data when they sense activity in the external
environment, for example, an alarm is triggered if the door is opened at night time. In the time-based architecture, its components continuously transmit data within a certain interval (e.g., climate control system sensors once per second read room temperature). The latter usually work repeatedly after a pause, which can be adjusted separately for each device or set up within a central management system that will send queries to endpoint devices and sensors after a period of time [3]. Onesuch system solution is being offered by Intel Corporatio
The IoT represents a hybrid architecture, which means it can contain different subsystem architectures. In most cases, the IoT systems are formed by two management architectures: event-driven and time-based. Event-driven architecture sensors transmit data when they sense activity in the external environment, for example, an alarm is triggered if the door is opened at night time. In the time-based architecture, its components continuously transmit data within a certain interval (e.g., climate control system sensors once per second read room temperature). The latter usually work repeatedly after a pause, which can be adjusted separately for each device or set up within a central management system that will send queries to endpoint devices and sensors after a period of time [3]. One such system solution is being offered by Intel Corporatio
IoT is a network of tiny innovations like the sensors which can be attached to possibly anything available and then make them communicate with the cloud server without any human interaction. So, the question is how to make this happen? Well the answer is to attach a sensor to a Raspberry Pi device about which we will be discussing in the coming sections. Raspberry Pi device with the installed EdgeX agent helps the users to acquire, store, process, and take actions any kind of data from the device to the cloud server.
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Figure 1
Environment characteristics
The fundamental characteristics of the IoT are as follows:
Interconnectivity:
With regard to the IoT, anything can be interconnected with the global information and communication infrastructure.
Things-related services:
The IoT is capable of providing thing-related services within the constraints of things, such as privacy protection and semantic consistency between physical things and their associated virtual things. In order to provide thing-related services within the constraints of things, both the technologies in physical world and information world will change.
Heterogeneity:
The devices in the IoT are heterogeneous as based on different hardware platforms and networks. They can interact with other devices or service platforms through different networks.
Dynamic changes:
The state of devices change dynamically, e.g., sleeping and waking up, connected and/or disconnected as well as the context of devices including location and speed. Moreover, the number of devices can change dynamically. Enormous scale: The number of devices that need to be managed and that communicate with each other will be at least an order of magnitude larger than the devices connected to the current Internet. Even more critical will be the management of the data generated and their interpretation for application purposes. This relates to semantics of data, as well as efficient data handling.
Safety:
As we gain benefits from the IoT, we must not forget about safety. As both the creators and recipients of the IoT, we must design for safety. This includes the safety of our personal data and the safety of our physical well-being. Securing the endpoints, the networks, and the data moving across all of it means creating a security paradigm that will scale.
Connectivity:
Connectivity enables network accessibility and compatibility. Accessibility is getting on a network while compatibility provides the common ability to consume and produce data.
2.2.1 Key IoT Technologies
Arduino hardware is an affordable and easy to set up option for building a basic IoT device that is supposed to perform one action, for example, read humidity sensor data. Arduino community is one of the oldest in this domain, so there won’t be a lack of support or resources. On top of that, Arduino’s functionality is easily expandable with on-top shields and multiple digital and analog general-purpose input/output pins.
Raspberry Pi is the best choice for data-heavy connected devices like hubs, gateways, datum collectors or personal cloud servers, however, it will also be a good fit for simpler IoT applications.
Particle is an all-inclusive platform that covers all bases not only for IoT prototyping but also for building a fleet of ready-to-go IoT devices. Basically, you have everything you need in one place — hardware, development environment and tools, cloud and robust support from the community. Another benefit of the Particle platform is the mesh-ready hardware and connectivity which is getting more and more popular among IoT connectivity options.
Arduino
Arduino is an open-source prototyping platform based on easy-to-use hardware and software. Arduino boards are able to read inputs – light on a sensor, a finger on a button, or a Twitter message – and turn it into an output – activating a motor, turning on an LED, publishing something online. With the ease of programming and the plug and play nature of Arduino based system, it quickly became loved by many in the hardware space. The early Arduino boards, were mostly general-purpose microcontrollers which were connected to the internet using GSM and WiFi modules, but as the IoT began to Open up, boards with special features that support the IoT were developed. Boards like the Arduino 101(developed with Intel), the MKR1000, Arduino WiFi Rev 2 and the MKR Vidor 4000 which is the first Arduino board based on an FPGA Chip.
2.2.2 Device Intelligence
Artificial intelligence, as we all know, comes in handy with another technology under its umbrella — Machine Learning or ML. Often used interchangeably, the terms AI and ML work on the principle of developing software programs that possess intelligence. This intelligence allows them to analyze data and make decisions similar to how a human brain does the same. Since the essence of IoT devices is to gather data and make use of it, placing data obtained from physical devices through machine learning and artificial intelligence allows us to expand upon those processes. The Internet of Intelligent Things (IoIT) uses artificial intelligence to bring more value to the IoT domain by better interpreting data obtained from connected devices. Here's how:
The devices connected in an IoT network are linked via sensors and actuators wrapped with software and hardware to provide humans with logical inputs. The foundation of IoT is machine learning and artificial intelligence because it allows these devices to make sense of the data collected through them. When a set of connected devices collect raw data and combine it, the software programs enabled with machine intelligence capabilities take this data and analyze them. After thorough analysis, the output obtained contains valuable information.
2.2.3 Communication capabilities
There are 6 IoT Communication Protocols/ Technology, let us look each one of them.
a. Bluetooth
An important short-range IoT communications Protocols / Technology. Bluetooth, which has become very important in computing and many consumer product markets. It is expected to be key for wearable products in particular, again connecting to the IoT albeit probably via a smartphone in many cases. The new Bluetooth Low-Energy (BLE) – or Bluetooth Smart, as it is now branded – is a significant protocol for IoT applications. Importantly, while it offers a similar range to Bluetooth it has been designed to offer significantly reduced power consumption.
b. Zigbee
ZigBee is similar to Bluetooth and is majorly used in industrial settings. It has some significant advantages in complex systems offering low-power operation, high security, robustness and high and is well positioned to take advantage of wireless control and sensor networks in IoT applications. The latest version of ZigBee is the recently launched 3.0, which is essentially the unification of the various ZigBee wireless standards into a single standard.
c. Z-Wave
Z-Wave is a low-power RF communications IoT technology that primarily design for home automation for products such as lamp controllers and sensors among many other devices. A Z-Wave uses a simpler protocol than some others, which can enable faster and simpler development, but the only maker of chips is Sigma Designs compared to multiple sources for other wireless technologies such as ZigBee and others.
d. Wi-Fi
WiFi connectivity is one of the most popular IoT communication protocol, often an obvious choice for many developers, especially given the availability of WiFi within the home environment within LANs. There is a wide existing infrastructure as well as offering fast data transfer and the ability to handle high quantities of data. Currently, the most common WiFi standard used in homes and many businesses is 802.11n, which offers range of hundreds of megabits per second, which is fine for file transfers but may be too power-consuming for many IoT applications.
e. Cellular
Any IoT application that requires operation over longer distances can take advantage of GSM/3G/4G cellular communication capabilities. While cellular is clearly capable of sending high quantities of data, especially for 4G, the cost and also power consumption will be too high for many applications. But it can be ideal for sensor-based low-bandwidth-data projects that will send very low amounts of data over the Internet.
f. NFC
NFC (Near Field Communication) is an IoT technology. It enables simple and safe communications between electronic devices, and specifically for smartphones, allowing consumers to perform transactions in which one does not have to be physically present. It helps the user to access digital content and connect electronic devices. Essentially it extends the capability of contactless card technology and enables devices to share information at a distance that is less than 4cm.
2.2.4 Mobility support, Device Power
Machine-to-machine communication is often used for remote monitoring. In product restocking, for example, a vending machine can message the distributor's network, or machine, when a particular item is running low to send a refill. An enabler of asset tracking and monitoring, M2M is vital in warehouse management systems (WMS) and supply chain management (SCM).
Utilities companies often rely on M2M devices and applications to not only harvest energy, such as oil and gas, but also to bill customers -- through the use of smart meters -- and to detect worksite factors, such as pressure, temperature and equipment status.
M2M apps
In telemedicine, M2M devices can enable the real time monitoring of patients' vital statistics, dispensing medicine when required or tracking healthcare assets.
The combination of the IoT, AI and ML is transforming and improving mobile payment processes and creating new opportunities for different purchasing behaviours. Digital wallets, such as Google Wallet and Apple Pay, will most likely contribute to the widespread adoption of M2M financial activities.
Smart home systems have also incorporated M2M technology. The use of M2M in this embedded system enables home appliances and other technologies to have real time control of operations as well as the ability to remotely communicate.
M2M is also an important aspect of remote-control software, robotics, traffic control, security, logistics and fleet management and automotive.
2.2.5 Sensor Technology
IoT − Sensors
The most important hardware in IoT might be its sensors. These devices consist of energy modules, power management modules, RF modules, and sensing modules. RF modules manage communications through their signal processing, WiFi, ZigBee, Bluetooth, radio transceiver, duplexer, and BAW.
Actuators
Another type of transducer that you will encounter in many IoT systems is an actuator. In simple terms, an actuator operates in the reverse direction of a sensor. It takes an electrical input and turns it into physical action. For instance, an electric motor, a hydraulic system, and a pneumatic system are all different types of actuators.
Participatory sensing technology:
2.2.6 RFID technology
RFID (radio-frequency identification) and NFC (near-field communication) provide simple, lowenergy, and versatile options for identity and access tokens, connection bootstrapping, and payments.
RFID technology employs 2-way radio transmitter-receivers to identify and track tags associated with objects.
2.2.7 Satellite Technology.
Custom engineered space-based communication seems to be the only feasible solution to the problem of interconnecting IoT devices scattered across the globe. Satellite technology has the potential to support the development of the IoT sector. Satellites can easily handle such wide-spread connectivity challenge. The speed of data transaction for such high loads might prove to be a problem. It is, however, just a matter of time before innovative solutions spring up.
Satellite operators are already collaborating to bring forth such services and hardware that can unleash the full potential of IoT. They are developing satellite-based solutions that can be easily integrated into hybrid networks that combine fiber, wireless networks, and satellite. Once IoT is empowered with a global network of billions of interconnected devices, it will usher in sweeping changes with impact to business model transformation and new capabilities.
Currently, narrowband providers (L band operating frequency range 1–2 GHz in the radio spectrum) are being used for IoT connectivity purposes. But advancement in high-throughput Ku-band and Ka-band satellite connections have created a broadband expressway in space. The global nature of satellite systems and the ability to broadcast to multiple points at the same time makes it the most efficient signal delivery on earth. Satellite transmissions can work seamlessly with terrestrial networks to attain global coverage.
LEO, GEO, and ATG Satellites
Among Low Earth Orbit (LEO), Geosynchronous Earth Orbit (GEO), and Air-to-Ground (ATG) networks, commercially, GEO is the best option currently. There are many technical challenges in connecting a non-GEO constellation to a vehicle or device, especially the terminal products. This task primarily requires a hybrid solution with the ability to innovate the satellite ecosystem. Satellite operators are investing in meta-material-based antenna technology to develop Flat Panel Antennas (FPAs). Such antenna and terminal products will be no bigger than a laptop in size, and would provide mobility, content delivery, and wireless backhaul. Meanwhile, researchers are working on a new model as well. It combines the advantages of GEO and LEO satellites. These hybrid fleets will bring the polar regions under broadband coverage. This model will help in layering bandwidth for high-density traffic regions and applications that require redundancy
Key Takeaways
References
