Internet of Things

by Sagar Joshi
Internet of Things (IoT) is a network of connected devices that collect, share, and exchange data in real time, enabling smarter automation across systems.
Sagar Joshi
SJ

Sagar Joshi

Sagar Joshi is a former content marketing specialist at G2 in India. He is an engineer with a keen interest in data analytics and cybersecurity. He writes about topics related to them. You can find him reading books, learning a new language, or playing pool in his free time.

What is the Internet of Things (IoT)?

Internet of Things (IoT) refers to a network of physical devices embedded with sensors, software, and connectivity that enables them to collect, exchange, and act on data over the internet.

At its core, IoT connects everyday objects — such as smart home devices, wearables, industrial machines, and vehicles  so they can communicate with each other and with centralized systems. This creates an ecosystem of connected devices, real-time data, and automated decision-making.

IoT platforms typically rely on components like sensors, edge devices, cloud computing platforms, and wireless networks to capture and process data. These systems power applications in smart homes, smart cities, industrial IoT (IIoT), healthcare monitoring, and supply chain tracking.

What are the different types of Internet of Things?

The main types of Internet of Things are consumer IoT, commercial IoT, industrial IoT (IIoT), infrastructure IoT, and military IoT (IoMT). These categories are based on where connected devices are used and the purpose they serve.

  • Consumer Internet of Things (CIoT) refers to interrelated systems or objects in the context of consumer applications, use cases, and devices. Here, IoT is personally used by the consumer. The interconnected devices have unique identifiers (UID) that recognize and access entities for various purposes.
  • Commercial Internet of Things is concerned with IoT systems and devices used in businesses and enterprises. Commercial IoT devices have paved the way for today's consumer-level deployments.
  • Industrial Internet of Things (IIoT) involves sensors and devices connected to industrial computers. For example, in manufacturing and energy management, IIoT assists data collection, exchange, and analysis, improving productivity, efficiency, and other economic components. IIoT uses cloud computing to optimize process controls.
  • Infrastructure Internet of Things is a subset of Industrial Internet of Things. But due to its significance in smart infrastructure development, it's considered a different IoT type.
  • Internet of Military Things (IoMT), also known as Battlefield IoT or Internet of Battlefield Things (IoBT), uses IoT systems and devices in the military and on the battlefield. It's used to increase situational awareness, analyze risk, improve military practices and strategy, and refine response time. For example, an interconnected system connects ships, planes, and tanks.

What are the applications of the Internet of Things

The main applications of the Internet of Things (IoT) include smart homes, agriculture, smart cities, supply chain management, and healthcare. These use cases leverage connected devices, sensors, and real-time data to automate processes, improve efficiency, and enhance decision-making across industries.

  • Smart homes: Use IoT devices and sensors to automate lighting, temperature control, security systems, and energy management for improved comfort and efficiency.
  • Agriculture (smart farming): Uses IoT sensors, RFID, and data analytics to monitor soil conditions, optimize irrigation, track livestock, and improve crop yields.
  • Smart cities: Deploy connected sensors and networks for traffic management, pollution monitoring, waste management, parking systems, and disaster response.
  • Supply chain management: Uses IoT tracking devices and sensors to monitor shipments, improve logistics visibility, optimize inventory, and enhance operational efficiency.
  • Healthcare (IoT in healthcare): Enables remote patient monitoring, connected medical devices, and real-time health data tracking to improve diagnosis, treatment, and patient care.

What are some Internet of Things technologies?

The core technologies behind Internet of Things (IoT) systems include wireless sensor networks, cloud computing, big data analytics, communication protocols, and embedded systems. Together, these technologies enable connected devices to collect data, communicate over networks, and support real-time monitoring, automation, and decision-making.

  • Wireless sensor networks with distributed devices and sensors help monitor environmental and physical changes. They have end nodes, routers, and coordinators. For example, weather monitoring systems and surveillance systems.
  • Cloud computing provides a means to access applications over the internet. Users can access resources like databases, web servers, and storage from almost any location. It provides infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS).
  • Big Data analytics deals with the study of massive volumes of data, or big data. Big data is generated every minute from various sources like social media videos, digital images, sensors, and sales transaction records.
  • Communication protocols are the backbone of IoT systems as they allow network connectivity and linking to applications. Devices can exchange data over the network. They are used in data encoding and addressing schemes.
  • Embedded systems are a mix of hardware and software systems that perform specific tasks. They have a microcontroller, microprocessor, memory, networking, input-output, and storage devices. It is used in digital cameras, wireless routers, and music players.

What are the standards used in the Internet of Things?

IoT standards are protocols that enable connected devices to communicate, share data, and operate securely across networks. Common standards include 6LoWPAN, ZigBee, LiteOS, OneM2M, and AMQP, which support interoperability, low-power communication, and scalable IoT systems.

  • IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) is a low-power network where every node has its IPv6 address.
  • ZigBee is a low-power, low-data rate wireless network used to create personal area networks and is widely used in industrial settings.
  • LiteOS is an operating system similar to Unix employed in wireless sensor networks. It supports smartphones, wearables, and smart homes.
  • OneM2M is a global standard, machine-to-machine service layer that can be embedded in software and hardware to connect devices. It applies to all industry verticals.
  • Advanced Message Queuing Protocol supports various messaging applications and communication patterns. 

What are the benefits of the Internet of Things?

The main benefits of Internet of Things (IoT) are improved efficiency, higher productivity, better decision-making, increased safety, and stronger customer experiences. By connecting devices, sensors, and systems, IoT helps organizations automate workflows, collect real-time data, and respond faster to changing conditions.

  • Efficiency: Automates processes, reduces manual effort, and improves operational performance with connected devices and smart sensors.
  • Productivity: Frees up human resources by handling repetitive tasks, allowing focus on higher-value work.
  • Better decision-making: Provides real-time data insights from IoT devices to support faster, data-driven decisions.
  • Safety: Uses sensors and monitoring systems to detect risks, prevent failures, and improve workplace and system safety.
  • Customer experience: Enhances service quality through real-time tracking, personalization, and better inventory and service management.

What are the limitations of the Internet of Things?

The main limitations of Internet of Things (IoT) include security risks, data privacy concerns, high implementation costs, interoperability challenges, and reliance on network connectivity.

  • Security risks: Connected devices increase the attack surface, making IoT systems vulnerable to cyberattacks, hacking, and unauthorized access.
  • Data privacy concerns: Continuous data collection raises concerns about how sensitive user and operational data is stored, used, and protected.
  • High implementation costs: Initial setup, infrastructure, device deployment, and maintenance can be expensive, especially at scale.
  • Interoperability issues: Different devices, platforms, and standards may not work seamlessly together, creating integration challenges.
  • Network dependency: IoT systems rely heavily on stable internet and network connectivity, which can impact performance and reliability if disrupted.

What is the difference between IoT and IIoT?

The main difference between IoT and IIoT is that IoT is designed for consumer and commercial connected devices, while IIoT is built for industrial environments that require greater reliability, durability, and operational precision.

IoT IIoT
Internet of Things (IoT) refers to a network of connected devices used in consumer, commercial, or everyday environments to collect, exchange, and act on data over the internet. Industrial Internet of Things (IIoT) refers to the use of connected sensors, machines, and systems in industrial environments to monitor operations, collect real-time data, and improve automation and efficiency.
Primarily designed for retail, business, and general-use applications such as smart homes, wearables, and connected consumer devices. Built for industrial applications and requires more robust design parameters to support reliability, safety, and large-scale operational performance.

Frequently asked questions about the Internet of Things

Have unanswered questions? Find answers below.

Q1. What are examples of IoT?

Common examples of Internet of Things include smart home devices, wearable technology, connected cars, industrial sensors, and smart city systems. Devices like smart thermostats, fitness trackers, RFID-enabled supply chain trackers, and remote patient monitoring systems use IoT sensors and connectivity to collect real-time data and automate tasks.

Q2. Is IoT replaced by AI?

IoT is not replaced by artificial intelligence (AI); instead, IoT and AI work together to create smarter systems. IoT devices collect real-time data through sensors, while AI analyzes that data to enable automation, predictive analytics, and intelligent decision-making in applications like smart homes, healthcare, and industrial IoT (IIoT).

Q3. What skills are needed for IoT?

Key skills needed for IoT include embedded systems development, networking and communication protocols, cloud computing, data analytics, and cybersecurity. Knowledge of IoT platforms, sensor integration, edge computing, and real-time data processing is also essential for building and managing connected device ecosystems.

Q4. What programming languages are used in IoT?

Common programming languages used in IoT include C, C++, Python, Java, and JavaScript. These languages are used for embedded systems programming, device communication, cloud integration, and data processing in IoT applications, along with frameworks and platforms that support real-time and low-power environments.

Ready to explore IoT devices? Learn how connected devices collect, share, and act on data to improve automation and real-time decision-making.

Internet of Things Software

This list shows the top software that mention internet of things most on G2.

Particle offers a suite of hardware and software tools to help you prototype, scale, and manage your Internet of Things products.

Microsoft Defender for IoT is a comprehensive security solution designed to protect Internet of Things (IoT and operational technology (OT environments. It offers real-time asset discovery, vulnerability management, and cyberthreat protection for industrial infrastructures, including industrial control systems (ICS and OT networks. By providing complete visibility into all IoT and OT assets, Defender for IoT enables organizations to manage security posture effectively and reduce the cyberattack surface area. Its agentless, network-layer monitoring ensures seamless integration with existing systems without impacting performance. Key Features and Functionality: - Context-Aware Visibility: Gain comprehensive insights into all IoT and OT assets, including device details, communication protocols, and behaviors. - Risk-Based Security Posture Management: Identify and prioritize vulnerabilities using a risk-prioritized approach to minimize the cyberattack surface. - Cyberthreat Detection with Behavioral Analytics: Utilize IoT and OT-aware behavioral analytics and machine learning to detect and respond to cyberthreats effectively. - Agentless Monitoring: Deploy non-invasive, passive monitoring that integrates seamlessly with diverse industrial equipment and legacy systems. - Unified Security Operations: Integrate with Microsoft Sentinel and other security information and event management (SIEM systems for centralized monitoring and governance. Primary Value and Problem Solved: Defender for IoT addresses the critical need for robust security in IoT and OT environments, which are often vulnerable due to unpatched devices, misconfigurations, and lack of visibility. By providing real-time asset discovery, continuous monitoring, and advanced threat detection, it empowers organizations to proactively manage risks, ensure compliance, and protect critical infrastructure from evolving cyberthreats. This solution enables seamless integration with existing security operations, fostering a unified approach to IT and OT security.

Golioth makes it easy for hardware and firmware engineers to connect custom hardware to a full-featured cloud without needing to be a cloud expert. Golioth works best with products that are ready to scale. We enable excellent prototyping capabilities and our scalable cloud infrastructure means you can grow your product as soon as you’re ready. Golioth is ready-made for projects using Cellular, WiFi, and Thread connectivity. Application verticals run the spectrum from asset tracking to low-power sensor networks.

InfluxDB is the open source time series database

Azure Time Series Insights is a fully managed analytics, storage, and visualization service for managing IoT-scale time-series data in the cloud. It provides massively scalable time-series data storage and enables you to explore and analyze billions of events streaming in from all over the world in seconds.

SAP Analytics Cloud is a multi-cloud solution built for software as a service (SaaS) that provides all analytics and planning capabilities – business intelligence (BI), augmented and predictive analytics, and extended planning and analysis – for all users in one offering.

UiPath enables business users with no coding skills to design and run robotic process automation

IF This Then That. Diversely-integrated API automation platform.

• Harness data with broad functionality and unlimited scalability. IBM Informix is a secure embeddable database, optimized for OLTP and Internet of Things (IoT) data. Informix has the unique ability to seamlessly integrate SQL, NoSQL/JSON, time series and spatial data. Everyone from developers to global enterprises can benefit from its reliability, flexibility, ease of use and low total cost of ownership. • Optimize business decisions Perform analytics close to data sources to enhance local decision making. Access business intelligence faster with enhanced integration with various tools and applications. • Eliminate downtime Ensure always-on operations across your grid environment. Upgrade, maintain and configure the grid with no downtime. Successfully meet service-level agreements. • Improve development agility Support both structured and unstructured data with a hybrid database system for enhanced flexibility and easier development. • IBM Informix is available on-premise and on the IBM Cloud. IBM Informix on Cloud offers the complete feature set of on-premises Informix deployments. Run your OLTP queries and workloads on an optimized instance and use the Informix warehouse accelerator to configure in-memory query acceleration for predictive analytics. Get the benefits of Informix without the cost, complexity and risk of managing your own infrastructure. IBM Informix V14.10 enhances all editions, bringing improvements to performance, security, administration, and core database capabilities including support for online transaction processing (OLTP) and replication workloads, timeseries and spatial data. Discover why many of the world’s most innovative companies depend on IBM Informix.

GridDB is a database that offers both speed and scaling for mission critical big-data applications.

Cisco Packet Tracer is a comprehensive network simulation tool developed by Cisco Systems, designed to facilitate the learning and teaching of complex networking concepts. It enables users to create, configure, and troubleshoot virtual networks, providing a realistic environment for practicing networking skills without the need for physical hardware. This software is particularly beneficial for students and professionals preparing for Cisco certifications such as CCNA and CCNP. Key Features and Functionality: - Network Simulation: Allows the creation of network topologies by adding and configuring devices like routers, switches, and end devices through a user-friendly drag-and-drop interface. - Protocol Support: Supports a wide range of protocols across various layers, including HTTP, FTP, SMTP, DNS, DHCP, TCP/IP, RIP, OSPF, EIGRP, BGP, and more, enabling comprehensive network behavior simulation. - Multiuser Collaboration: Facilitates collaborative learning by enabling multiple users to connect and work on the same network topology simultaneously over a real network. - Activity Wizard: Provides tools for instructors to create customized learning activities, set up scenarios, and offer feedback, enhancing the educational experience. - Cross-Platform Compatibility: Available on multiple operating systems, including Windows, Linux, and macOS, ensuring accessibility for a broad user base. Primary Value and User Solutions: Cisco Packet Tracer addresses the challenge of limited access to physical networking equipment by offering a virtual environment where users can practice and develop their networking skills. It serves as an invaluable educational resource, allowing learners to experiment with network configurations, understand protocol behaviors, and troubleshoot issues in a risk-free setting. By simulating real-world networking scenarios, Packet Tracer helps users build a solid foundation in networking principles, preparing them for real-world applications and certification exams.

IBM® Db2® is the database that offers enterprise-wide solutions handling high-volume workloads. It is optimized to deliver industry-leading performance while lowering costs.

With Infoblox DNS Firewall you gain proactive network protection against fast-evolving, elusive malware threats that exploit DNS to communicate with command and control (C&C) servers and botnets.

Check Point Infinity is the only fully consolidated cyber security architecture that provides unprecedented protection against Gen V mega-cyberattacks as well as future cyber threats across all networks, endpoint, cloud and mobile. The architecture is designed to resolve the complexities of growing connectiviity and inefficient security

Process Mining powered by ARIS allows you to understand your business like never before. Improve your processes constantly and embrace innovation continuously to keep up and stay relevant.

Solve planning and scheduling problems using optimization modeling tools and powerful CPLEX Optimizer and CP Optimizer solvers to make better business decisions

Privacy1's Zero Trust Data Protection solution offers a comprehensive approach to safeguarding personal data by applying privacy-aware security directly to the data assets. This method shifts the focus from traditional perimeter defenses to a data-centric strategy, ensuring that sensitive information remains protected regardless of its location within the system. By encrypting data and implementing purpose-specific access controls, Privacy1 enables organizations to manage data access based on legal purposes, approved systems, and authorized personnel. This approach not only enhances data security but also ensures compliance with privacy regulations and builds trust with customers. Key Features and Functionality: - Consistent Protection: Maintains a uniform level of data security as information moves across various systems, regardless of differing perimeter security measures. - Purpose Control: Allows access to sensitive personal data solely for specific legal purposes, ensuring that data usage aligns with organizational policies and regulatory requirements. - Privacy Awareness: Integrates privacy considerations into data protection, enabling control over data usage across the organization from a legal standpoint. - Data Encryption: Ensures that data is encrypted, making it accessible only to legitimate systems and users for authorized purposes, both at rest and during transit. - Automated Privacy Rights Management: Facilitates the automation of data subject rights requests, such as access, erasure, and consent management, reducing manual overhead and enhancing compliance. Primary Value and Problem Solved: Privacy1's Zero Trust Data Protection addresses the critical challenge of data breaches and unauthorized access by implementing a data-centric security model. By encrypting data and enforcing purpose-specific access controls, it ensures that even if perimeter defenses are compromised, the data remains unreadable and secure. This solution not only mitigates the risk of data misuse but also simplifies compliance with privacy regulations, reduces operational costs associated with manual data protection processes, and enhances customer trust by demonstrating a commitment to data privacy and security.