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HomeArticle/ FeaturesTop 5 trends for the AIoT industry in 2025

Top 5 trends for the AIoT industry in 2025

In recent years, we have explored the evolving trends in the security landscape. As technology has advanced, the focus has broadened from merely securing our world—to making it smarter. AIoT (AI-powered Internet of Things) is leading this transformation, revolutionizing industries beyond security. This year, we dive deeper into the trends driving AIoT, showing how they are reshaping industries and fostering a more efficient, secure, and sustainable future.

  • Perception technologies are adapting to varied environments and situational needs

Perception technologies are continuing to evolve to operate efficiently in diverse conditions. AI Image Signal Processing (AI-ISP) technology, for example, has already set a high bar on image quality performance in low-light conditions by significantly reducing image noise and addressing motion blur. For large-scale monitoring scenarios that require wide angles and detailed images, Ultra High Definition (UHD) technologies are becoming the norm. They offer faster frame rates, improved contrast, and richer details, making it easier to capture and analyze vast, complex scenes.

Beyond the visible light spectrum, millimeter-wave radars see through smoke, dust, and obstacles, providing precise speed and direction measurements widely used in traffic management. In noisy, harsh industrial settings with continuous operations, meanwhile, sound wave sensing enables non-invasive equipment monitoring for early fault detection, reducing downtime.

  • AIoT is bringing digitalization to life in diverse industrial applications

Companies are increasingly adopting AIoT technologies to address specific operational challenges and speed up digital transformation. In retail, where loss prevention and maintaining a competitive edge is crucial, AIoT devices now provide valuable data such as inventory tracking, foot traffic, queue lengths, and area density. This information helps stores tailor their offerings, optimize operations, and mitigate losses. In the energy sector, meanwhile, safety is a non-negotiable requirement. AIoT solutions, such as automated personal protective equipment (PPE) checks, now use AI to streamline the inspection of proper safety gears, reducing manual oversight and enhancing workplace safety.

Furthermore, the development of large vision, audio, and fiber-optic models is being tailored with industry-specific designs, algorithm optimization, and model simplification. This trend aims to create lightweight, vertical-specific AIoT deployments that are practical and effective in real-world scenarios.

Additionally, the increasing adoption of generative AI is adding an extra layer of ease and efficiency. Multimodal large models, which integrate text with visual data, make it much simpler to search and interact with information such as when people are locating a particular package in a logistics center. By providing user-friendly text-based interfaces, these models are delivering increasingly rapid and seamless access to needed data, streamlining decision-making and operational processes.

  • There is a significant move towards open and collaborative ecosystems

As the demand for tailored AIoT solutions in fragmented industrial scenarios has increased, no single company can meet all the user demands on their own. Open platforms and tools are therefore becoming essential. These enable solution providers to seamlessly integrate third-party applications in order to accelerate digital transformation across industries.

To further support this, standardized protocols are simplifying device communication, reducing development time and costs. These protocols make it easier for all types of devices to work together, addressing issues like configuration complexity, scalability, and network security.

This collaborative environment helps developers and integrators create flexible and effective AIoT solutions. Simple to use AI training platforms are now becoming widely available, which allow non-specialist systems integrators to train and deploy their own custom AI models. Users can easily combine and customize these AI models for tasks like object detection and audio classification, enhancing the functionality of their solutions and, therefore, the value they can add in sectors ranging from industrial processes to home automation.

  • Building cybersecurity trust through proactive strategies and cross-industry partnerships

Cybersecurity remains a critical concern in the expanding AIoT landscape. Increasingly, companies are adopting proactive, yet responsive, cybersecurity approaches, which focus on rapid threat detection and effective response. By partnering with specialized security testing firms, they are able to evaluate products against a wide range of standards, identifying and tackling vulnerabilities early to prevent exploitation. Continuous testing ensures updates and enhancements consistently meet the highest security benchmarks.

Transparent communication has become crucial for openly addressing security concerns. Increasingly, organizations are setting up security response centers and deploying robust vulnerability management programs. Again, close collaboration is key to this trend, with installers, system integrators, and customers all working together to ensure secure deployment and use, leading to a more resilient and trusted operational framework.

  • AIoT becoming a game-changing catalyst for sustainability

Organizations worldwide are seeking more sustainable ways to operate and conduct business, and many are turning to AIoT technologies to do this. By augmenting connected sensors with AI algorithms, AIoT is helping to optimize resource use, cut energy consumption, improve waste management, and boost operational efficiency in numerous industries.

In building management, for example, AIoT systems are being used to automatically adjust energy use based on occupancy and weather conditions, leading to significant cost savings and lower carbon emissions. In transport, the technology is being used to optimize traffic flow and reduces congestion, cutting carbon emissions in the process. Similarly, the combination of millimeter-wave radar and water-level detection cameras allows for real-time analysis of water quality and flood control. Advancements such as these highlight AIoT’s potential as a powerful tool for positive change, benefiting both people and the planet.

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