Role of AIoT in transforming industries and tackling environmental challenges

By Staff Report January 24, 2025 7:33 pm IST

From enhanced perception technologies to collaborative ecosystems, AIoT promotes smarter solutions that address contemporary concerns and enable a safer, more sustainable future.

In recent years, we have looked into the changing trends in the security field. As technology improved, the goal shifted from simply safeguarding our world to making it smarter. AIoT (AI-powered Internet of Things) is driving this shift, revolutionising industries far beyond security. This year, we go deeper into the trends that are propelling AIoT, demonstrating how they are altering industries and fostering a more efficient, safe, and sustainable future.

Perception technologies are adapting to varied environments and situational needs
Perception technologies are constantly evolving in order to function well in a variety of environments. AI Image Signal Processing (AI-ISP) technology, for example, has already raised the bar for image quality performance in low-light environments by dramatically decreasing image noise and resolving motion blur. Ultra High Definition (UHD) technologies are increasingly being used in large-scale monitoring scenarios that demand wide angles and detailed images. They provide faster frame rates, more contrast, and more information, making it easier to capture and analyse large, complicated situations.

Beyond the visible light spectrum, millimeter-wave radars can see through smoke, dust, and barriers, providing precise speed and direction readings that are commonly employed in traffic control. In noisy, demanding industrial settings with continuous operations, sound wave sensing allows for non-invasive equipment monitoring for early failure detection, decreasing downtime.

AIoT is bringing digitalisation to life in diverse industrial applications
Companies are increasingly using AIoT technology to solve specific operational difficulties and accelerate digital transformation. In retail, where loss prevention and keeping a competitive edge are critical, AIoT devices now give useful data such as inventory tracking, foot traffic, wait lengths, and area density. This data enables stores to adapt their offerings, optimise operations, and reduce losses. In the energy sector, however, safety is an unavoidable requirement. AIoT solutions, such as automated personal protective equipment (PPE) checks, are now using AI to speed the inspection of appropriate safety gear, eliminating manual oversight and improving workplace safety.

Furthermore, huge vision, audio, and fiber-optic models are being customised with industry-specific designs, algorithm optimisation, and model simplification. This approach seeks to develop lightweight, vertical-specific AIoT implementations that are both feasible and effective in real-world circumstances.

Furthermore, the growing use of generative AI is providing another degree of convenience and efficiency. Multimodal big models, which include text and visual data, make it considerably easier to explore and interact with information, such as when looking for a certain shipment in a logistics centre. These models provide user-friendly text-based interfaces, allowing for increasingly rapid and smooth access to necessary data, speeding decision-making and operations.

There is a significant move towards open and collaborative ecosystems
As demand for specialised AIoT solutions in fragmented industrial scenarios has grown, no single provider can cover all of the customer needs on its own. Open platforms and technologies are consequently becoming increasingly important. These enable solution providers to seamlessly integrate third-party apps, hence accelerating digital transformation across industries.

Standardised protocols help to simplify device communication, lowering development time and expenses. These protocols facilitate collaboration among various types of devices by solving concerns such as configuration complexity, scalability, and network security.

This collaborative ecosystem enables developers and integrators to construct flexible and successful AIoT systems. Simple AI training platforms are now widely available, allowing non-specialist systems integrators to train and deploy their own unique AI models. Users can simply combine and customise these AI models for activities like object identification and audio categorisation, increasing the capability of their solutions and, consequently, the value they may bring in industries ranging from industrial processes to home automation.

Building cybersecurity trust through proactive strategies and cross-industry partnerships
Cybersecurity remains a major worry in the growing AIoT world. Companies are increasingly adopting proactive, but responsive, cybersecurity tactics that prioritise early threat identification and effective response. They can examine products against a variety of standards by collaborating with specialised security testing firms, detecting and addressing vulnerabilities early on to prevent exploitation. Continuous testing guarantees that upgrades and enhancements continuously meet the highest security standards.

Transparency in communication has become critical for openly discussing security risks. Organisations are increasingly setting up security response centres and implementing sophisticated vulnerability management strategies. Again, strong collaboration is essential in this trend, with installers, system integrators, and customers all working together to ensure secure deployment and use, resulting in a more resilient and trustworthy operational framework.

AIoT becoming a game-changing catalyst for sustainability
Organisations all around the world are looking for more sustainable ways to run their businesses, and many are turning to AIoT technology to help them do so. AIoT is assisting in a variety of industries by complementing connected sensors with AI algorithms to optimise resource utilisation, reduce energy consumption, enhance waste management, and raise operational efficiency.

In building management, for example, AIoT systems are utilised to automatically alter energy use based on occupancy and weather conditions, resulting in significant cost savings and decreased carbon emissions. In transportation, technology is being utilised to improve traffic flow and minimise congestion, lowering carbon emissions. Similarly, the combination of millimeter-wave radar and water-level detection cameras enables real-time monitoring of water quality and flood management. Advancements like this demonstrate AIoT’s potential as a powerful tool for constructive change that benefits both people and the environment.

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