What Are IoT Communication Protocols and Standards?

How do billions of IoT devices send, receive, and act on data? They rely on communication protocols, standards, platforms, and cloud infrastructure that help information move securely and efficiently across IoT systems. In this part of our IoT Basics series, we explain the key technologies and terms behind IoT communication, from messaging protocols and APIs to edge computing, AI, and data systems.

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Last updated: May 2026

Infrastructure Needed for IoT Communications

IoT communication protocols define how devices, gateways, platforms, and applications format, transmit, receive, and act on data.

IoT communication depends on more than a network connection. Devices, gateways, platforms, cloud services, APIs, and data systems all need to exchange information reliably and securely. Together, these layers make it possible to collect data from connected devices, process it, store it, analyze it, and send instructions back to devices when needed.

In many IoT deployments, gateways play an important role between devices and cloud systems. A gateway can aggregate data from sensors, machines, and other endpoints, translate between different protocols, and forward information to cloud platforms or enterprise systems. Depending on the use case, a gateway may be a physical device, embedded software, or a virtualized function.

Cloud and edge infrastructure also shape how IoT communication works. Some data is sent to the cloud for storage, analytics, device management, and integration with business systems. Other data may be processed closer to the device, at the edge, to reduce latency, limit bandwidth use, or support local decision-making.

IoT communication protocols are selected based on the requirements of the device and application. Lightweight protocols such as MQTT, CoAP, and LwM2M are often used for constrained devices, sensor networks, and large-scale machine-to-machine deployments. Other protocols and architectures, such as AMQP, DDS, Modbus, RESTful APIs, and TCP/IP, support different requirements for messaging, interoperability, industrial communication, and internet-based data exchange.

The right communication stack depends on the use case. A smart meter, industrial sensor, connected vehicle, healthcare device, or remote asset may each require different trade-offs between bandwidth, power consumption, latency, reliability, security, processing capability, and integration with cloud or enterprise systems.

The terms below explain the main protocols, platforms, cloud concepts, AI technologies, and data terms used in IoT communication.

IoT Messaging and Communication Protocols

IoT systems rely on specialized protocols to manage data exchange, security, and device communication across diverse networks. Below are the most common IoT protocols and their typical use cases.

Message Protocols

Message protocols define how devices, applications, and systems format, send, receive, and route messages. They are used to connect physical devices and networks with applications, platforms, and middleware, making them important for IoT and M2M communication. Common IoT message protocols include MQTT, CoAP, AMQP, and DDS.

MQTT

Message Queuing Telemetry Transport

MQTT is a lightweight publish-subscribe messaging protocol used to exchange data between devices, applications, and middleware. It is widely used in IoT and M2M environments because it is designed for constrained networks and devices.

Topic / Pub-Sub

A messaging model (core to MQTT) where devices “publish” payloads to a specific “topic,” and servers or other devices “subscribe” to that topic to receive the data.

CoAP

Constrained Application Protocol

CoAP is an application layer protocol that has been designed to address the needs of HTTP-based IoT systems. HTTP is foundation of data communication for the World Wide Web but, while it is freely available and usable by any IoT device, it can consume too much power for IoT applications. CoAP has addressed this limitation by translating the HTTP model into usage in restrictive devices and network environments.

AMQP

Advanced Message Queuing Protocol

AMQP is an open standard application layer protocol used for transactional messages between servers. Main functions include receiving and placing messages in queues, storing messages and setting up a relationship between components. It is not suitable for IoT sensor devices with limited memory.

DDS

Data Distribution Service

DDS is a scalable IoT protocol that enables high-quality communication in IoT. Similar to the MQTT, DDS also works to a publisher-subscriber model. In contrast to MQTT, DDS allows for interoperable data exchange independent of the hardware and the software platform.

Modbus

A serial communications protocol for use with programmable logic controllers (PLCs) that is used to connect industrial electronic devices.

TCP/IP

The Internet Protocol suite is the computer networking model and set of communications protocols used on the Internet and similar computer networks.

IoT Device Management and Cellular Communication Concepts

Lightweight M2M / LwM2M

Lightweight M2M is a device management protocol designed for sensor networks and the demands of a machine-to-machine (M2M) environment.

MTC

Machine Type Communications

Machine Type Communications is a descriptive term for fully automatic data generation, exchange, processing and actuation among intelligent machines, with low or no intervention by humans.

Artificial Intelligence in IoT

AI

Artificial Intelligence

Artificial intelligence is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition and decision-making. AI also enables machines to learn from experience.

Machine learning

Machine learning is a method of data analysis that automates construction of analytical models, based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.

Deep learning

A machine learning technique that teaches computers to learn by example.

Computer vision

A part of computer science working to enable computers to see, identify and process images in a manner similar to human vision.

Neural networks

A computer system modelled on the human brain and nervous system that is designed to help machines reason more like humans.

IoT Platforms, APIs, and Network Configuration

IoT Platform

An IoT platform is a software suite that connects devices, networks, applications, and data systems. It helps manage communication, security, device operations, data collection, and analytics across an IoT deployment.

API

Application Programming Interface

An API is a set of rules and tools that allows software applications, platforms, and systems to exchange data or trigger functions securely and consistently.

Northbound / Southbound API

Southbound APIs communicate downwards to the physical devices/gateways; Northbound APIs communicate upwards to enterprise software, cloud applications, or databases.

RESTful API

Also referred to as a RESTful web service a RESTful API is based on representational state transfer (REST) technology, an architectural style and approach to communications often used in web services development.

SOAP API

Simple Object Access Protocol (SOAP) is a communication protocol for the exchange of information between various operational systems using Extensible Markup Language (XML).

APN

Access Point Name

APN is a mandatory gateway setting that translates communications between a cellular network and the internet, assigning the device its IP address.

Cloud, Edge, and Software Management

Cloud computing

Cloud computing uses remote servers, storage, and software services accessed over the internet to process, store, and manage data without requiring all infrastructure to run locally.

Edge computing

Edge computing brings data processing and storage closer to the device or data source, helping reduce latency, limit bandwidth use, and support local decision-making.

Fog computing

Also known as edge computing or fogging, Fog computing is a term created by Cisco that refers to extending cloud computing to the edge of an enterprise’s network.

Hybrid cloud

A cloud computing environment that uses a mix of on-premise, private cloud and third-party, public cloud services with orchestration between the two platforms.

Firmware / FOTA

A specific class of computer software that provides the low-level control for the device’s specific hardware. FOTA refers to the capability of upgrading firmware over-the-air.

OTA Updates

Over-the-Air Updates

Distributing new data remotely to devices. Sub-categories include FOTA (Firmware), SOTA (Software application level), and POTA (SIM Profile).

Open source

Describes software for which the original source code is freely available and can be redistributed or modified.

Peer-to-peer

Peer-to-peer computing or networking is a distributed application architecture that partitions tasks or workloads between peers. Peers are equally privileged, equipotent participants in the application.

Flow-based programming

A type of dataflow programming in which programme steps communicate with each other by transmitting data through some kind of channel. The channels are managed by the larger system, leaving the connected components free to focus on processing input and producing output.

Java / JSON

Java is a general-purpose programming language. JSON, or JavaScript Object Notation, is a lightweight text-based data format used to structure and exchange data between systems.

IoT Data and Industrial Systems

Big data

Amounts of data that are so large that traditional technologies cannot handle their transfer or analysis. Certain IoT technologies specialize in handling and transferring big data as it is seen as key to large companies’ goal to maximize efficiency.

Data filtration / filtering

Describes a wide range of strategies for refining data sets so they provide what a user, or set of users, needs without including other data that can be repetitive, irrelevant or even sensitive.

Data janitor

A data janitor is a person who takes large amounts of big data and condenses it into information that businesses can act upon.

DDDM

Data Driven Decision Making

An approach to business governance that values decisions that can be backed up with verifiable data.

Hadoop

An open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems.

Blockchain

A growing list of records, called blocks, which are linked using cryptography. For use as a distributed ledger, a blockchain is typically managed by a peer-to-peer network collectively adhering to a protocol for inter-node communication and validating new blocks.

Pervasive computing

Also called ubiquitous computing

The embedding of computational capability into everyday objects to make them effectively communicate and perform useful tasks in a way that minimizes the end user’s need to interact with computers.

SCADA

A computer system for gathering, analyzing and controlling real-time data.