The use of IoT devices is making our daily lives smarter. IoT combined with artificial intelligence (AI), or artificial IoT (AIoT), is helping in automated real-time decision-making and data analysis. AI can add value to IoT through machine learning (ML) and improved decision-making. Similarly, IoT can add value to AI through connectivity and data exchange. With the rapid technological advancements, AIoT is transforming every industry, enterprise and consumer.

5G is going to be the key ingredient in driving AIoT applications. According to a Counterpoint Research study, the shipments of 5G AIoT-supported modules will grow at a CAGR of 84% between 2022 and 2030. Further, 60% of 5G IoT modules will have AI capability by 2030 for better processing and real-time decision-making.

AIoT applications

The adoption of AIoT is becoming an emerging technology trend across a wide range of industries where real-time data operation is needed, such as industrial manufacturing, robotics, logistics, healthcare, agriculture, smart cities and smart home.

Industrial manufacturing

Manufacturing relies on digital transformation to become more efficient and reduce human error. This sector needs to adopt AIoT solutions. AIoT-powered robots in factories improve the manufacturing process with excellent efficiency. They help reduce labor costs as well as time.

Smart cities

In a smart city, there are several uses of AIoT, such as traffic management and waste management. To avoid chaos and congestion on the road in a crowded city, AIoT-based drones help monitor traffic and transmit real-time traffic data for analyses through AI and for making decisions on the speed limit and timing of traffic lights, all without human interference. Therefore, real-time traffic monitoring by drones increases efficiency and reduces congestion.

Security and surveillance are other important applications for AI in smart cities. AI cameras can help police monitor illegal activities and prevent unwanted situations.

Autonomous vehicles

Self-driving cars are one of the best use cases of AIoT applications. IoT-enabled devices like cameras, radars and sonars in the car gather data and the AI system helps analyze this data within a few milliseconds so that the car can make decisions like a human. Fully autonomous vehicles will generate 1-2TB of data per hour and AI will be required to handle this amount of data and take some decisions at the edge.

Smart homes

AI in the connected home space is mainly used for voice assistant, situational awareness, automation and security. Starting from door locks, smoke alarm, surveillance and smart speakers to smart appliances such as lighting, thermostat, refrigerator, plugs, routers, meters, home controllers and vehicle chargers, many applications have already adopted AI features.

Challenges in implementing AI in IoT

As most AI applications are based on real-time decision-making, they need a high-speed data rate to communicate. 5G’s high speed and low latency will be ideal for AIoT applications. But in many regions, 5G infrastructure is still not there or is in the initial phase. Hence, it will be challenging to scale. Data management and taking the right decision at the right time by handling huge amounts of data will be another big challenge for AI adoption. Moreover, the security angle will also need to be addressed. Both hardware- and software-level security will be required for AIoT applications to keep connected devices safe.

Initiatives by module and chipset players in AI applications

With the increasing traction for 5G-based AIoT applications, module vendors like Fibocom, Quectel, Thundercomm and MeiG are stepping forward to launch AI-supported 5G IoT modules. Some module vendors are offering AI features at the hardware level while some vendors are offering AI features at the software level. Whether to use hardware- or software-level AI features depends on the application and cost of the project. Recently, Quectel announced that it would add software-level AI capability in its Rel 16-based 5G modules by partnering with NVIDIA. International module vendor Telit is also adding AI capabilities in its FM980 5G module through NVIDIA software. However, Quectel, Fibocom, MeiG and Thundercomm are already offering hardware-level 5G AI-supported modules for high-end applications such as C-V2X, AR/VR, robots, smart cities, live streaming, gaming and edge computing.

In terms of chipset players, Qualcomm is leading in the 5G AIoT chipset space. This year, it launched the world's first AI-supported 5G modem Snapdragon X70. Moreover, it has broader 5G AIoT SoC offerings with the QCM6490, Snapdragon 480, Snapdragon 690 and Snapdragon 750.

The second-largest IoT chipset player, UNISOC, is trying to gain momentum for 5G through AIoT-based SoCs. So far, UNISOC is offering AIoT features in its T770, T760 and T740 chipsets.

Recently, MediaTek launched the Genio 1200 chipset, specially designed for 5G AIoT devices. It is targeting applications such as smart home, industrial, robotics and audio/video terminals.

We expect that 2023 will provide momentum to the 5G AIoT market as the IoT market has been facing some instability lately due to inflation, supply issues and other macro factors.

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