M2M and IoT Device Characteristics Quiz

Small, low-power embedded systems like microcontrollers with integrated networking interfaces, ideal for constrained IoT applications.

Small, low-power devices that often use microcontrollers with integrated networking interfaces and can support communication protocols like TCP/IP.

A hardware unit that can sense its environment (using sensors) and/or take actions (using actuators) in its environment.

The device's central processing unit, typically a microcontroller with varying power and memory capabilities.

The method by which the device receives power, whether it's a fixed power source, batteries, energy harvesting, or a combination.

Components that allow the device to capture data about its surroundings (e.g., temperature, light) or to interact with the environment (e.g., turning a motor on/off).

The way the device communicates with other devices or networks, including wireless connections like Bluetooth or Wi-Fi, or wired connections like Ethernet.

Software that manages the device's operations, ranging from basic loop execution to complex real-time operating systems.

Low-rate, low-power communication technologies often face signal loss due to environmental factors, technical limitations, physical constraints of devices, and maintenance challenges.

Power line communication (PLC) utilizes existing electrical power lines for data transmission.

PLC operates by modulating the electrical signals on power lines, similar to sending pulses of different strengths and frequencies.

PLC can achieve long-range communication (kilometers) with low data rates (hundreds of bits per second) by using lower frequencies. This was initially used for remote metering and is being explored for smart grids.

PLC technology has been enhanced to deliver higher bandwidth communication over power lines, moving towards broadband capabilities.

Standardization efforts for PLC are ongoing, with IEEE 1901 and ITU-T G.hn being considered for smart grid applications in the United States.

LAN (local area network) and WLAN (wireless LAN) technologies are crucial for M2M and IoT applications due to their reliability, high bandwidth, and established infrastructure.

The diversity of IoT deployment settings (factories, buildings, vehicles, etc.) necessitates flexible and adaptable technologies for communication.

In M2M and IoT, the lowest layer often consists of multiple devices that communicate with each other using short-range protocols like ZigBee or Bluetooth.

Devices in the lowest layer can use longer range communication protocols like Wi-Fi to connect beyond close proximity.

Some devices may host services like REST services for communication, allowing them to be dynamically discovered by other devices.

Devices in the lower layer may have limited resources, requiring the use of gateways to mediate communication, translate protocols, and provide extra support.

Machines or devices can communicate directly with each other or through infrastructure support to enable various applications and achieve their goals.

A service-oriented approach to M2M integration involves direct interaction with physical elements using web services or lightweight methods like REST.

Many of the services interacting with M2M devices are network-based services residing in the cloud, leveraging its scalability and other benefits.

Enterprise services benefit from cloud characteristics like virtualization, scalability, and multi-tenancy, providing advantages for M2M applications.

A family of standards for wireless local area networks (WLANs) commonly known as Wi-Fi. It defines the protocols for wireless communication between devices.

An extension of the IEEE 802.11 standard that focuses on improving data throughput, particularly for demanding applications like multimedia streaming.

A newer version of Wi-Fi designed to further enhance data throughput, primarily operating in the 5 GHz band.

An IEEE 802.11 standard aimed at enabling large networks with a focus on energy efficiency and extended range. It operates in the 1 GHz ISM band.

A low-power and low-cost wireless communication technology designed for short-range applications, often used in smart devices like smartphones and wearables.

A family of standards that define the physical and medium access control layers for low-power, low-rate wireless networks, often used in the Internet of Things (IoT).

A wireless communication protocol built on top of the IEEE 802.15.4 standard. It enables low-power, low-rate networking in applications like home automation and sensor networks.

A technique used to manage the active periods of a radio transceiver during transmission and reception, optimizing energy consumption in low-power networks.

A network protocol that enables IPv6 communication over low-power wireless networks like IEEE 802.15.4, which are commonly used in IoT applications.

A routing protocol designed for low-power and lossy networks, often found in IoT scenarios. It uses Destination Oriented Directed Acyclic Graphs (DODAGs) for efficient data routing.

A specific ICMPv6 message used in RPL networks to discover RPL instances, configure parameters, and find parent nodes.

A specialized web protocol designed for constrained environments, often used in IoT and M2M applications. It's built to work with limited resources and bandwidth.

A technique used in RPL to efficiently manage message exchange in lossy networks. It utilizes periodic updates and back-off mechanisms to balance energy consumption and data reliability.

A type of network topology employed by RPL. It resembles a directed tree structure, allowing routing from various points to a central sink or conversely, spreading information from the root to multiple nodes.

The process of analyzing and preparing M2M data for analysis, processing, and storage. This involves tasks such as data normalization, data cleansing, and data transformation. It can be applied to data at rest or in motion.

The process of working with data that is actively being generated or transmitted, often coming from sensors or devices. It involves handling real-time data streams, processing them efficiently, and making adjustments as needed.

Correcting inaccuracies in M2M data, such as removing duplicate entries, standardizing units of measurement, or filling in missing values with estimates. This ensures data consistency and reliability.

Estimating values for data that is missing or incomplete. This involves using statistical methods or intelligent algorithms to reconstruct the data based on known information.

Combining data from two or more sources or streams to create new information. Usually involves applying mathematical operations on the combined datasets.

Converting data from one format to another. This can involve changing units of measurement, encoding data differently, or restructuring the data to fit a new model.

The possibility that even when erased or removed, data might still be recoverable from electronic media due to residual magnetic or electrical traces. It poses a risk of unauthorized access to sensitive information.

Techniques designed to prevent data remanence, such as overwriting data multiple times, using degaussing to erase magnetic media, encrypting data, or physically destroying storage devices.