What is AI in IOT (Internet of Things)?

March 19, 2025

AI in IoT is like a brain for smart devices, analyzing data and automating tasks. It upgrades connected systems into smarter, more responsive networks.

The term Internet of Things, or IoT, is a collective network of devices, or things or physical objects equipped with sensors, software and various other technologies, enabling connectivity and data exchange with other devices and systems over the internet.
A collection of technologies building computers and machines in a way that can learn, act and reason equivalent to human intelligence is considered as Artificial Intelligence (AI).
Integrating AI in IoT enhances the capabilities of IoT systems. Transitioning from conventional IoT, which majorly emphasizes basic data collection and connectivity, to AI-driven IoT, where AI facilitates data processing in real-time, predictive analysis, personalized user experience and autonomous decision-making, the technology has by far achieved a milestone.

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Advantages of AI in IoT

AI in IoT enhances automation, improves data analysis, and enables predictive maintenance, making systems smarter and more efficient. It helps optimize resource usage, detect anomalies, and improve decision-making. However, challenges like security risks and high implementation costs must be considered as well. But for now, let’s concentrate on the advantages.

1. Automated Task

The synergy between AI and IoT automates the intricate tasks which were previously performed by humans. Robots equipped with sensors and AI algorithms can now complete such tasks with utmost accuracy. Not only does this automation process increase productivity, but it also minimizes the risk of human error.

2. Predictive Maintenance

AI-powered IoT sensors track the real-time performance of equipment, detecting potential challenges way before they occur. This approach assists industries cut downtime, lower maintenance costs and extend the lifespan of equipment. For instance, AI-driven IoT for predictive maintenance, reducing costs and enhancing efficiency was utilized in Hyderabad Metro, in March 2024.

3. Enhanced User Experience

AI-driven IoT devices make use of Artificial General Intelligence (AGI) to learn from user behavior to enhance their experience with a company’s software or services as is exemplified through smart assistants improvising over time by acknowledging user preferences, making their responses more accurate and dedicated.

4. Quality Control

This integration also helps in quality control as AI detects patterns that may signal defects or faults, allowing loopholes to be fixed quickly so that only the top-notch products and services reach end customers.

5. Ensures Workers and Equipment Safety

Continuous remote monitoring assists in real-time issue detection, particularly in dangerous environments. It enables quick emergency responses, avoiding costly accidents while safeguarding company’s data and employee well-being.

Concerns Associated with AI in IoT

Integrating AI into IoT devices comes with various issues and challenges that must be addressed during design and implementation. Data privacy, security vulnerabilities, and ethical concerns are major factors that require attention. Also, AI models may demand high computational power, impacting efficiency to some extent. Few key considerations include:

1. Unclear Targets

Organizations excited about developing AI-powered IoT might overlook feasibility, resulting in budget overruns and dissatisfied stakeholders. Optimized research and expert’s consultancy would ensure that the ideas align with business goals and customer needs.

2. Inadequate Data

AI algorithms require a piled-up data to offer work accuracy. The data inadequacy or the privacy rules restricting its use would demand other potential approaches such as using pre-trained AI models, creating new data from existing ones, or using artificial data to bridge the gap.

3. Ensuring Software Security

Many AI-powered IoT projects fail as a result of overlooked security risks in data, devices, servers, and networks, leading to potential leakage of data. Cyber threats are increasing day-by-day, making IoT systems even more vulnerable to sophisticated attacks.

4. Ethical Concerns

AI in IoT can potentially raise concerns regarding privacy and safety. For example, it might collect and analyze personal data without permission or be used to unfairly influence people. The lack of clear regulations further complicates ethical decision-making in AI-driven IoT systems.

5. Unstable and Unreliable

IoT systems must be reliable and stable, but their complexity can cause performance issues, so regular monitoring, maintenance, and backup mechanisms are essential. Moreover, unexpected failures or downtime can disrupt critical operations.

Applications of AI in IoT

AI and IoT are major drivers of modern innovation with vast potential for growth. From smart homes to industrial automation, their synergy enhances efficiency, decision-making, and predictive capabilities. Their integration unseals new possibilities across various industries and everyday life. Let’s get into the details here:

1. Agriculture

AI-powered IoT is bringing a revolution in Indian agriculture by offering real-time updates on weather, soil, and crops. In Khutbav village, Maharashtra, this technology increased crop yields by 40% and cut water and pesticide costs by 50%.

2. Smart Home Automation

Integrating AI models with real-time data, smart assistants can understand user needs, retrieve information, and act accordingly. For example, if a user says, “The living room feels hot,” the AI can check the temperature using IoT sensors and automatically adjust the AC to maintain comfort based on past preferences.

3. Healthcare

AI in IOT improves healthcare by enabling remote patient monitoring and customized treatments. They collect real-time health data, helping with early diagnosis and better patient care, making healthcare more accessible.

4. Consumer Electronics

At the Mobile World Congress 2025, companies unveiled AIoT innovations like Xiaomi’s modular camera phone and Huawei’s tri-fold smartphone, demonstrating the rising trend of AI-powered IoT devices to enhance user experiences.

5. Living Intelligence

The fusion of AI, biotechnology, and advanced sensors, called Living Intelligence, enables systems to sense, learn, and adapt. This integration is driving innovations in industries like personalized education and healthcare.

6. Edge Computing

Integration of AI with edge computing enables faster data processing near the source, lowering delays and improving response times. This is especially useful for real-time applications like autonomous vehicles and smart cities.