The Smart Home Inflection Point Is Coming: MCUs, AI Processors, and Sensors—Three Types of Chips—Will Underpin Whole-Home Intelligence

Is the turning point for smart homes here? What is truly worth paying attention to is these chips. Original source: Semiconductor Industry Observer. Published: 2026-11-01 14:57. Author: Fang Yuan. AI chip manufacturing. Generate poster. Three types of core chips support the next generation of whole-home intelligence.

Smart speakers can understand commands, air conditioners can be controlled remotely, cameras can recognize people and pets, and robot vacuums already have the ability to plan routes autonomously. But for ordinary households, whole-home intelligence in the true sense is still not fully widespread. Devices from different brands each have their own independent control systems, users need to switch between different apps, and so-called smart linkage often remains simple operations under preset conditions.

The problem is that connecting devices to the network does not mean the devices are truly intelligent. Over the past decade or so, the smart home industry has mainly solved the problem of how devices connect to the network and how they receive remote control, while what needs to be solved in the next stage is how devices understand the environment, identify user needs, and complete coordination among different devices.

Recently, Apple gave its own new answer. On October 13, Apple officially released three home products: the smart home hub HomeView equipped with a 7-inch display, the second-generation HomePod mini, and the fourth-generation Apple TV 4K. Unlike previous simple hardware updates, Apple this time made Siri AI and Apple Intelligence important selling points, hoping to integrate entertainment, communications, personal information, and smart device control through the home hub, so that the voice assistant can transform from a simple instruction-execution tool into an intelligent interaction entry point in home scenarios.

As Apple begins to increase its investment in smart homes, companies such as Huawei, Xiaomi, and Amazon are also continuing to advance their respective home ecosystems. Behind this competition, what is worth the semiconductor industry's attention is no longer just the sales of terminal products such as smart speakers and smart screens, but the fact that the chip architecture supporting the operation of the entire home intelligence system is changing.

The next stage of smart homes is to make devices truly interconnected.

Smart home is not a new concept. From early smart lighting and smart door locks to smart speakers and robot vacuums, and now to whole-home intelligence, the industry has gone through multiple rounds of product iteration. But a long-standing problem has never been completely solved: why is it so difficult for devices of different brands and different categories to truly work together? This is related to the early development path of the smart home industry.

In the initial stage of the market, manufacturers focused more on differentiation in single-product functions. Air conditioner companies developed their own smart control systems, lighting companies built independent device management platforms, and smart speaker manufacturers built ecosystems around voice assistants. For companies, mastering device entry points, user data, and software platforms can form certain competitive barriers. But from the consumer's perspective, compatibility problems between different systems also arise. Users may buy air conditioners, lights, door locks, and cameras from different brands at the same time, only to find that these products require installing multiple apps, and some devices cannot connect to the same control platform. Even if linkage can be achieved, fixed conditions often need to be set in advance, lacking the ability to understand complex home scenarios. Therefore, what the next stage of smart homes must first solve is not how many new functions to add, but how to establish a more unified device connection and management system.

Matter is an important technical foundation in this direction. As a smart home interconnection protocol promoted by the Connectivity Standards Alliance (CSA), in June the CSA officially released Matter 1.6, further improving capabilities such as device commissioning, cross-ecosystem management, and contextual control. Among them, NFC commissioning can simplify the installation process for some devices, and the Joint Fabric mechanism provides support for multiple authorized controllers to jointly manage devices. This means that the evolution of Matter is not only about enabling devices to recognize each other, but also about trying to improve the actual experience when multiple smart home platforms jointly manage devices.

The domestic market is also advancing in a similar direction. Huawei HarmonyOS Smart Home continues to strengthen cross-device and cross-space scenario linkage, integrating lighting, air conditioning, security, and other devices into the home environment through central control screens, voice interaction, sensors, and smart control systems. Xiaomi, relying on smartphones, smart speakers, routers, and a large number of IoT terminals, continues to expand its smart home product matrix.

From Apple's home hub to Huawei's HarmonyOS Smart Home, and then to Xiaomi's smart ecosystem, although the technical paths and business models adopted by each company differ, the core competitive direction is converging: whoever can enable more devices to connect stably will have a better chance of becoming the core entry point for home intelligent services.

This also means that the value of the smart home industry is shifting from single hardware to system-level solutions. For semiconductor companies, an increase in the number of devices will certainly bring chip demand, but what is more worth noting is that as the degree of device coordination improves, the requirements for chip performance, power consumption, communication capabilities, and software-hardware adaptation are also rising simultaneously.

From networking to AI services, three types of chips are worth attention.

If the previous stage of smart homes mainly solved device networking and remote control, then after AI enters the home, the industry's demand for chips is no longer limited to communications and basic control. A complete smart home system needs to accomplish at least three basic tasks: connecting different devices, perceiving the home environment, and analyzing and making decisions based on the collected information. Corresponding to the semiconductor industry chain, MCUs and wireless connectivity chips, AI processors, and sensors constitute three types of foundational hardware worth attention.

The first is the chips responsible for connectivity and control. Products such as smart lighting, door and window sensors, smart switches, and temperature and humidity monitoring devices generally do not require particularly powerful computing capability, but they need to operate stably over the long term while minimizing power consumption and manufacturing cost as much as possible. Therefore, MCUs remain indispensable core components for a large number of smart home terminals. MCUs are mainly responsible for executing preset control logic, reading sensor data, managing peripherals, and completing basic task scheduling. As the demand for device networking increases, some products also integrate wireless communication capabilities such as Wi-Fi, Bluetooth, and Thread, forming more highly integrated wireless SoCs.

A typical example here is the wireless connectivity chip maker Espressif Systems. The company's products cover technologies including Wi-Fi, Bluetooth, Thread, and Zigbee, and it also provides Matter-related chip solutions. In the first three quarters of 2026, the company achieved operating revenue of 2.370 billion yuan, up 23.94% year on year. It also noted in its third-quarter report that overall demand in the smart home industry performed steadily, and that the expansion of IoT application scenarios was an important backdrop for its performance growth. On the product side, the ESP32-S31 launched by the company this year entered mass production in July. The chip adopts a dual-core RISC-V architecture, integrates connectivity capabilities including Wi-Fi 6, Bluetooth 5.4, Thread, and Zigbee, and adds hardware support related to image processing and human-machine interaction, reflecting that wireless connectivity chips are extending toward more complex terminal applications.

The control logic of traditional smart homes is relatively simple. For example, when the temperature exceeds a set value, the air conditioner starts; when human activity is detected, the lights turn on. Such tasks can be completed through MCUs and preset rules. But when devices need to understand natural language, analyze camera images, identify abnormal behavior, or determine household scenarios based on data from multiple sensors, the computational complexity increases significantly. At this point, AI SoCs, NPUs, and dedicated coprocessors begin to play a role. Taking home cameras as an example, traditional products mainly complete video capture, encoding, and transmission, whereas after adding AI computing capability, devices can complete some tasks locally, such as human detection, pet recognition, and abnormal activity analysis, reducing ineffective video uploads and the pressure on cloud computing. A smart hub can combine user instructions, device status, and environmental information to complete more complex task scheduling.

Rockchip is a domestic chip company worth attention in this field. Its portfolio covers product lines including AIoT application processors, vision processors, and coprocessors. In May, it launched the new-generation mid-range AIoT processor RK3572, which integrates a 4TOPS computing-power NPU and targets applications such as smart cameras, video analysis, and multimedia terminals; the RK182X series coprocessors have also entered mass production and are used in combination with the RK3588 in AI TVs, supporting on-device multimodal models, image recognition and analysis, and offline voice interaction. In addition, vision processors such as the RV1126B and RV1106 mainly target smart camera and machine vision scenarios. It can be seen that Rockchip is expanding the local AI computing capability of terminal devices through combinations of main control chips and coprocessors.

The third category is sensors responsible for perceiving the environment. If communication chips solve how information is transmitted between devices, and AI processors solve how information is analyzed, then sensors are the entry point through which the entire system obtains external information. Traditional smart homes mainly rely on users actively inputting instructions, or on triggering preset actions through a single parameter such as temperature or humidity. But true scenario intelligence requires the system to understand multiple changes in the home environment.

For example, judging whether a room is occupied may be limited if it relies only on ordinary infrared human presence sensors; determining whether an elderly person has fallen, whether a user is in a sleep state, or whether there is abnormal activity in a room may require comprehensive judgment combining millimeter-wave radar, infrared sensors, cameras, and other environmental data. This also brings new application space for chips related to MEMS sensors, environmental sensors, image sensors, and millimeter-wave radar. Among them, temperature and humidity, light, and air quality sensors can be used for environmental monitoring and automatic adjustment of home appliances; image sensors are responsible for collecting visual information; and millimeter-wave radar can obtain information such as target distance, speed, and motion state through electromagnetic wave reflection, giving it application value in scenarios such as non-contact human presence detection and fall detection.

Taking some scenario solutions from Huawei HarmonyOS Smart Home as an example, it has already applied perception technologies such as millimeter-wave radar to functions including sleep-state auxiliary detection and fall event detection, and links them with lighting, air conditioning, and other devices. This change means that sensors are no longer merely auxiliary components of a single home appliance, but are gradually becoming an important foundation for the whole-house smart system to obtain environmental information.

It should be emphasized that sensors themselves do not directly complete complex scenario judgments. They are responsible for collecting information, and algorithms, processors, and control systems still need to participate afterward. Therefore, future competition in smart homes will not be a standalone upgrade of any single type of sensor, but coordination among multiple perception technologies and computing platforms.

03 As AI enters the home, where are the opportunities for domestic chips?

Take home cameras as an example. If every frame analysis had to be uploaded to the cloud, it would not only increase network bandwidth and server computing costs, but could also raise privacy concerns. For devices such as door locks, security systems, and environmental monitoring, some tasks also need to be completed as promptly as possible. Edge computing can process some data locally on the device or on a home gateway, reducing dependence on continuous network connections and narrowing the scope of sensitive information transmission. At the same time, the cloud can still handle tasks such as complex model inference, knowledge updates, and cross-device data management.

Apple's HomeView design also reflects this approach. It is equipped with the A18 chip and uses Secure Exclaves to isolate and process camera and microphone data, while allowing Siri requests to use on-device processing or Private Cloud Compute depending on the task type. This shows that even Apple, which emphasizes personal privacy, has not confined all AI capabilities to the local device, but is exploring the combination of edge hardware and cloud computing. For domestic semiconductor companies, this shift also brings new development opportunities.

China has a relatively complete smart home terminal manufacturing system. From smart lighting and appliance controllers to cameras, smart door locks, and home gateways, a large number of local brands and supply chain companies participate. The continuous upgrading of terminal products provides a broad application entry point for MCU, wireless connectivity chip, AI processor, and sensor companies. Second, the development of edge AI provides chip companies with room for product upgrades. In the past, some smart home products did not have high computing requirements, and competition among manufacturers was more focused on cost, power consumption, and basic functions. As local voice recognition, visual analysis, and complex scenario control gradually land, chip companies can increase product added value by improving integration, optimizing energy efficiency, and developing dedicated AI acceleration modules.

Layouts by companies such as Rockchip and Espressif are precisely a reflection of this industrial change. At the same time, the domestic smart appliance MCU and smart controller industry is also continuing to develop, and related companies have the opportunity to benefit from appliance intelligence and control system upgrades.

However, it should also be noted that market opportunities in smart homes will not automatically translate into performance growth for chip companies. Consumers' willingness to pay for whole-house intelligence is still constrained by cost and actual experience. For ordinary households, if a smart system requires replacing a large number of appliances, installing complex central control equipment, and entails high subsequent maintenance costs, market adoption will be difficult to advance quickly. Only when intelligence can genuinely improve the living experience will consumers be willing to keep paying for it.

Second, the smart home industry has obvious ecosystem attributes. Even if chip companies have products with good performance, without a mature software development environment, protocol adaptation capabilities, and customer support systems, it will be difficult for them to quickly enter mainstream terminal supply chains. Standards such as Matter can lower the threshold for interconnection, but they cannot eliminate differences among manufacturers in product design, system adaptation, and service experience. There is another issue that is easily overlooked: the life cycle of home devices is usually long. When consumers buy an air conditioner or refrigerator, they often expect to use it for many years. If a smart home platform cannot provide continuous software updates, stable device compatibility, and long-term security maintenance, even if the hardware itself has AI capabilities, it will be difficult to form a truly reliable home smart system.

04 Conclusion

For the semiconductor industry, the next round of opportunities in smart homes may not lie in a single hit home appliance, but in the hardware architecture upgrade of the entire home system. The inflection point for smart homes may be arriving, but it will not be driven merely by an AI speaker or a home hub. What truly determines the pace of industry development is whether underlying chips, communication standards, software ecosystems, and terminal demand can form a combined force. For domestic semiconductor companies, this is both a new market opportunity and a test of upgrading from a single-component supplier to a system-level solution provider.

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