What is the Internet of Things?

Since the term "Internet of Things" was coined by Kevin Ashton in 1999, the Internet of Things (IoT) has changed from a mere vision to a tangible reality. This can be attributed to the widespread adoption of internet technologies, the rise of ubiquitous computing, and the continuous advancement of data analysis and other development drivers. By 2030, the number of connected IoT devices is projected to reach around 40 billion worldwide, according to IoT‑focused market‑research firm IoT Analytics. So, what is the Internet of Things? Let's find out!

The Internet of Things can be described as an extension of the Internet and other networks, connected to various sensors and devices (or "things"), and can even provide advanced computing and analysis capabilities for simple objects such as light bulbs, locks, and vents.

Interoperability is one of the key aspects of the Internet of Things, contributing to its growing popularity. Connected or "smart" devices — often referred to as "things" on the Internet of Things — can collect data from their environment and share data with other devices and networks. Through data analysis and processing, the device can perform its functions with little or no human interaction.

Because of the continuous increase in the number of connected devices, the Internet of Things continues to develop, adding layers to shared and processed data and generating complex algorithms, thereby increasing the level of automation. Because it can connect a variety of "things", the Internet of Things enables diverse applications for individual users and the entire industry.

How Does the IoT Work?

The "things" that make up the Internet of Things can be anything from wearable fitness trackers to self-driving cars. No matter what functions they provide to users, these devices must include the following components to operate properly within their respective IoT systems.

Sensors

Sensors collect data from the environment so the IoT system can start processing it. These devices measure observable events or changes around them. In a car, for example, sensors play many roles: a temperature sensor checks if the engine is overheating, a tire pressure sensor alerts you when your tires need more air, parking sensors help detect nearby obstacles, a fuel level sensor shows how much gas remains in the tank, and a GPS sensor tracks the vehicle's location for navigation.

Connect and Identify

Data must be transferred from the device to the rest of the IoT system, whether to a computer or another device. For this communication to occur, the device must be uniquely identifiable within the network, often through an IP address or via an IoT gateway that connects it to the Internet.

Actuators

Most IoT devices can perform their primary functions without direct physical interaction with the user. IoT devices should be able to take action based on sensor data and subsequent feedback from the network. For example, even if the user is miles away, the smart light bulb can be turned on according to the user's command. Similarly, valves in smart factories can automatically open or close based on data collected by their sensors along the production line. Although these devices are usually built with automation in mind, they must also incorporate other technologies to ensure the IoT system works properly. The links that complete the IoT system's data processing are the following components.

IoT Gateway

The IoT gateway acts as a bridge, allowing data from different devices to reach the cloud. It translates various communication protocols into a standard format so that devices can understand each other and the cloud can process their data effectively. Common network protocols include MQTT (a lightweight publish/subscribe protocol widely used in IoT systems), HTTP/HTTPS (the standard web protocol for REST APIs), CoAP (the Constrained Application Protocol designed for low-power IoT devices), and AMQP (the Advanced Message Queuing Protocol used in enterprise messaging). The gateway can also filter out unnecessary data, reducing bandwidth use and improving efficiency.

The Cloud

In many IoT systems, the cloud handles complex or long‑term analysis, which helps reduce the computational and storage burden on individual devices. However, with the rise of edge computing, more preprocessing and real‑time decisions are shifting closer to the devices, so processing is now distributed between the edge and the cloud rather than concentrated in one place.

Edge Computing

Being a foundational IoT architecture pillar, edge computing processes data locally on devices or gateways to reduce latency and cloud dependency. This enables real-time decisions for latency-sensitive applications like autonomous vehicles, industrial automation, and remote monitoring, shifting more preprocessing closer to the source. With processing now distributed between edge and cloud rather than concentrated in one place, it strengthens overall IoT system resilience and efficiency.

User Interface

The user interface presents the data collected by the device to the user and allows the user to issue the necessary commands for the device to execute. The Internet Architecture Board (IAB) issued a guidance document in March 2015 (RFC 7452), "Architectural Considerations in Smart Object Networking," which discusses four communication patterns used by the Internet of Things. These models illustrate how the connectivity of IoT devices can expand the value of each device and enhance the overall user experience:

1. Device‑to‑Device

This model describes how two or more devices connect and communicate directly. Communication between devices is usually achieved through protocols such as Bluetooth, Z‑Wave, and Zigbee. This model often appears in wearable devices and home automation systems, where small data packets are transmitted between devices or via a central hub, for example, from a door lock to a smart home controller that then triggers the light to turn on.

Different smart devices may use various wireless communication protocols, such as Bluetooth, Wi-Fi, and Zigbee, which create interoperability challenges in the IoT system. The Matter protocol (launched late 2022, backed by Apple, Google, Amazon, Samsung) addresses these issues as the preferred networking layer for smart homes, with Thread as its dominant mesh networking solution. Cellular-based IoT technologies like 5G, NB-IoT (NarrowBand IoT), and LTE-M (LTE for Machines) are becoming key connectivity options for long-range, low-power, and large-scale deployments such as smart cities, asset tracking, and remote industrial sensors.

2. Device-to-Cloud

Many IoT devices connect to the cloud, frequently using wired Ethernet or Wi-Fi. After connecting to the cloud, users and related applications can access the device to execute commands remotely and push necessary software updates. Through this connection, the device can send usage and performance data that helps enhance the service or platform, for example, by refining algorithms, personalizing features, or improving reliability.

3. Device-to-Gateway

Before connecting to the cloud, IoT devices can communicate with intermediate gateway devices. The gateway can translate protocols and add an extra layer of security to the entire IoT system. For example, in a smart home, all smart devices can be connected to a hub (gateway). Although the connection protocols are different, the hub helps different devices work together.

4. Back-end Data Sharing

As an extension of the device-to-cloud model, this model allows users to access and analyse data collections from different smart devices. For example, a company can use this model to access information from all devices working in a company building, which are organized together in the cloud. This model also helps reduce data portability issues.

What are the Applications of the IoT?

Just as the Internet affects a wide range of users, so does the Internet of Things. Depending on the scale of the connection and the number of devices involved, the Internet of Things can have important and specific applications, whether for individual users or entire cities. Common applications of the Internet of Things include the following:

People and Home

People directly use IoT devices through wearable technology, such as smartwatches and fitness trackers, as well as devices that help receive and collect information in real-time. Applied to the home, IoT devices can be used to realize more interconnected, more energy-efficient, and more convenient home operations. The homeowner can also remotely access and control different aspects of the networked home through a computer or handheld smart device. Smart home devices can work autonomously to assist with daily tasks, such as adjusting thermostats or sending security alerts. Smart homes utilize devices like smart thermostats, lighting, voice-activated assistants, and security cameras.

Cars

Sensors in moving vehicles can collect real-time data about the vehicle and its surrounding environment. Self-driving cars use different sensors in combination with advanced control systems to evaluate their environment and drive autonomously.

IoT devices can be used to monitor vehicle performance, optimize routes, and track shipments in the transportation industry. Real‑time tracking of assets, monitoring environmental conditions of goods in transit, and optimizing route management are key functions of IoT in logistics. Commercial asset tracking and fleet management are among the largest IoT use cases: one analysis of the IoT‑based asset tracking and monitoring market finds that the Transportation and Logistics vertical alone accounts for 23.7% of the market, highlighting its leading role in IoT‑driven operations.

Factories

With the application of the Internet of Things in factories, manufacturers can automate repetitive tasks and access information in any part of the entire manufacturing process. The information provided by the sensors on the factory's machinery helps design methods that make the entire production line more efficient and less prone to accidents.

Enterprises

On a larger scale, with the adoption of IoT technology, companies can be more cost-effective, efficient and productive. For example, office buildings can install sensors to monitor elevator traffic or overall energy consumption. Different industries naturally have different IoT applications: in the healthcare industry, IoT devices can be used to obtain real-time and accurate updates on patient conditions, while in the retail industry, IoT devices can be used to help shoppers locate products and monitor inventory.

Healthcare

Wearable devices monitor vital signs such as heart rate, sleep patterns, and physical activity. IoT devices can be used to enable remote health monitoring and emergency notification systems. Remote Patient Monitoring includes devices that track blood sugar levels and alert patients to dangerous levels via smartphones.

Retail

Retailers use IoT for automated inventory tracking and checkout‑free shopping. Smart shelves with RFID tags monitor stock in real time and trigger reorders to avoid shortages. Several major retailers deploy cashierless stores where sensors and computer vision automatically detect items taken by customers and finalize payments via linked accounts, significantly shortening checkout times and eliminating traditional queues. Beacons in these stores enable personalized promotions, while environmental sensors optimize energy use and help preserve perishable goods, contributing to measurable reductions in inventory shrinkage through improved visibility and loss prevention.

Agriculture

IoT devices can be used in agriculture to monitor soil conditions, weather patterns, and crop growth. Sensors measure soil moisture and weather patterns to automate irrigation, helping farmers significantly reduce water usage compared with traditional irrigation methods.

Cities

The combined use of different IoT devices can cover cities and public areas. IoT devices can collect data from and influence their environment to help manage various aspects of urban governance, such as traffic control, resource management, and public safety.

IoT helps municipalities create more sustainable and livable urban environments through various applications. Intelligent traffic management in cities uses sensors at intersections to adjust traffic light timing in real time, reducing congestion and emissions.

What are the Current Issues with the IoT?

The Internet of Things (IoT) is a relatively new and developing technology. Therefore, it will be affected by some major issues, especially when more devices are expected to come online in the next few years. The following are a few aspects where the Internet of Things continues to face some problems.

Standards and Regulations

While broadening the scope of applications, more and more connected devices make the standardization and supervision of the Internet of Things a complicated and annoying process. Standardization and regulatory issues can range from technical issues to legal issues. For example, due to the lack of IoT standards, fragmentation is a technical issue faced by users. Different smart devices may use various wireless communication protocols, such as Bluetooth, Wi-Fi, Zigbee, and 5G, which hinder communication within the IoT system. On the other hand, the lack of regulation highlights existing Internet-related issues and adds another layer of complexity to these issues.

Regulatory and legal challenges are emerging as IoT devices become more widespread, requiring compliance with various data protection and privacy regulations. California Senate Bill No. 327 requires manufacturers of connected devices to equip them with reasonable security features to protect against unauthorized access. Determining responsibility is an example: if there are deficiencies and violations related to the use of IoT devices, the lack of supervision will make it difficult to determine the responsibility. Standards and regulations affect the overall quality of services provided by IoT technology, and therefore involve all IoT stakeholders, whether they are individual users, equipment manufacturers, or organizations that integrate technology into their processes.

Privacy

Privacy awareness grows with the increase in the diversity of personal information shared on the Internet. The Internet of Things further complicates this problem because it expands the types of data recorded and shared via the Internet. Since the Internet of Things works better by obtaining as detailed a view of the environment as possible, it makes a trade-off between user privacy and service quality. It is difficult to determine the point at which data collection should be restricted or completely stopped due to user privacy issues, especially under the automated nature of most IoT systems like EPAM's secure platforms.

Security

The rapid development of IoT has allowed billions of devices to connect to the network, leading to various security issues. The existing framework for IoT security is often insufficient, leading to vulnerabilities in connected devices. The IoT's rapid growth has created new vulnerabilities for companies, with millions of endpoints potentially exposed to attacks.

When it comes to the processing of data and information, there are always security issues. The Internet of Things increases its security challenges by accessing various personal information and tight integration with individual and organizational activities. These characteristics of the Internet of Things make this technology a viable target for cybercriminals. In addition, any damage, attack, or vulnerability of a single IoT device or system will weaken the overall security of the related network.

Other security threats related to IoT technology include:

• The homogeneity of mass-produced smart devices means the proliferation of the same possible vulnerabilities.

• As the need for human intervention is reduced, the automation of IoT systems makes it more difficult to detect attacks.

• The environment in which IoT devices are deployed makes these devices vulnerable to unforeseen physical threats, and attackers may directly tamper with the devices.

• The interconnectivity of the Internet of Things system makes every part of the system a means of data leakage and lateral network attacks, which may spread to other affected networks.

How Can the Use of the IoT be Secured?

Different types of IoT devices and systems face varying risks, but ensuring their security is a shared responsibility across manufacturers, service providers, and users. Strengthening IoT security requires a mix of standards-based design, continuous monitoring, and adaptive defense strategies.

Key Security Standards and Frameworks

IoT security best practices are now guided by globally recognized standards. The U.S. National Institute of Standards and Technology (NIST) outlines foundational cybersecurity activities for IoT device manufacturers in NIST IR 8259, "Foundational Cybersecurity Activities for IoT Device Manufacturers," with NIST IR 8259A providing the specific technical baseline capabilities, including secure device identity, data protection, patchability, and incident response. The ETSI EN 303 645 standard from the European Telecommunications Standards Institute defines cybersecurity requirements for consumer IoT, including secure credential management, software integrity, and data minimization. For industrial environments, the IEC 62443 series provides a layered approach to protect industrial control and automation systems, emphasizing defense-in-depth principles and system certification at multiple security levels.

Common Attack Vectors and Threat Examples

IoT devices are exposed to a range of attacks due to limited computing resources and inconsistent patching. The Mirai botnet attack of 2016 showed how poorly secured consumer IoT devices could be hijacked to launch large-scale DDoS attacks. Other common threats include:

• Man-in-the-middle (MitM) attacks, where adversaries intercept data transmissions between devices and cloud services.

• Firmware tampering or supply chain attacks, which insert malicious code during manufacturing or update processes.

• Credential stuffing and brute-force attacks, exploiting default or weak passwords in mass-produced devices.

Mitigation Strategies and Design Patterns

Security should be embedded at every stage of an IoT system's lifecycle — from design to deployment. Key measures include:

• Secure boot mechanisms that verify the integrity and authenticity of firmware at startup, preventing execution of unauthorized code.

• Hardware-based device attestation that confirms a device's identity and trustworthiness before it connects to the network.

• Zero-trust architecture for IoT networks, ensuring no device is inherently trusted and enforcing continuous authentication, authorization, and monitoring.

• End-to-end encryption (TLS/DTLS) for secure data transport and mutual authentication between devices and cloud endpoints.

• Ongoing vulnerability management with digitally signed firmware updates and centralized patch orchestration.

Collaborative Security Responsibility

IoT manufacturers can adopt "security by design" principles aligned with NIST IR 8259A profiles. Service providers should apply continuous threat monitoring, intrusion detection, and analytics for anomaly detection at the edge. End-users — especially enterprises — should segment IoT networks, enforce access control policies, and use strong identity management.

To drive alignment across the industry, the IoT Security Foundation (IoTSF) continues to publish frameworks and compliance guidance to strengthen resilience, ensuring that as IoT ecosystems scale, they remain secure, transparent, and trustworthy.

Future Trends in IoT

The Internet of Things (IoT) is changing how we live and work, becoming one of the most important trends shaping technology and the economy today. According to IoT Analytics, there were 21.1 billion internet-connected devices worldwide by the end of 2025, powering everything from smart cities and homes to healthcare and industrial systems — with numbers projected to exceed 24 billion by the end of 2026. With this massive growth comes an explosion in data, which means new ways of managing and handling information are more important than ever.

Having strong security is key, but it isn't enough on its own — organizations also need to manage data responsibly. These devices produce huge amounts of information, which needs to be carefully collected, stored, and processed. To keep data safe and ensure users trust them, companies should put strong strategies in place, like anonymizing personal information, limiting who has access to it, and managing the data's lifecycle (from when it's first collected to when it's no longer needed). This also helps them stay in line with regulations and laws.

AI and Machine Learning in IoT

Artificial intelligence (AI) and machine learning (ML) also play a huge role in making IoT smarter. These technologies can figure out patterns in all the data coming from these devices to provide insights and make predictions. For example, they can alert companies when machines need repairs, spot unusual activity, and even offer customized services to users.

Digital Twins in IoT

Digital twin technology is emerging as one of the most impactful trends in IoT, especially in industrial and urban environments. A digital twin is a virtual representation of a physical asset, system, or process that uses continuous, real‑time data from IoT sensors to mirror its behavior, performance, and condition.

In practice, IoT devices stream data into the twin, which runs simulations and analytics to detect patterns, predict failures, and test "what‑if" scenarios without risking the physical system. Insights from the digital twin can then be sent back to the real‑world asset as control commands or configuration changes, enabling more precise optimization, reduced downtime, and better decision‑making across factories, power grids, buildings, vehicles, and even entire cities.

Blockchain for IoT Security

Another interesting development is blockchain technology, which enhances IoT network security through tamper-resistant distributed ledgers. Blockchain enables secure device-to-device interactions and decentralization, reducing reliance on single points of failure, while lightweight protocols like IOTA or permissioned chains address scalability challenges for resource-constrained IoT devices. This approach helps mitigate key security and privacy risks in IoT ecosystems.

IoT Data Governance and Ethics

IoT generates massive data volumes requiring robust governance frameworks covering ownership, consent management, sovereignty, and compliance with GDPR and emerging RCC standards. While privacy risks are noted superficially, organizations must implement pervasive ethical controls as regulatory landscapes mature through the EU AI Act and the US Cybersecurity Improvement Act mandates. This builds ecosystem trust for scalable deployments.

Sustainability and Environmental Impact of IoT

IoT plays a dual role: it enables energy efficiency and environmental monitoring (via always-on devices and data centers), but also contributes to the use of rare earth minerals and e-waste. Approaches like green IoT design would add significant value.​

The potential economic impact of IoT is enormous. According to Grand View Research, the global IoT market will reach about USD 2.65 trillion by 2030, growing at a compound annual growth rate of roughly 11.4% from 2024. Big contributions will come from industries like factory automation and healthcare. For instance, IoT can make manufacturing more efficient by predicting when machinery will break down, and it can improve healthcare through tools like remote patient monitoring. These advancements highlight how IoT can drive innovation, make systems more efficient, and even bring benefits to society as a whole.