In 2025, the Internet of Things (IoT) industry will step into a new phase of deep integration and value creation. Over the years, IoT technologies have evolved from basic connectivity to a robust ecosystem enriched by low-power communication protocols, advanced SoC and AI chips, and the transformative potential of AI large models. This article analyzes IoT trends and applications across four dimensions: communication protocols, system platforms, embedded hardware, and AI-driven innovations.
Communication Protocols: Advancing Efficiency and Diverse Applications
Key Trends
IoT communication standards and protocols are evolving to meet the demands of both consumer and industrial applications with higher efficiency, lower power consumption, and seamless integration.
- Matter + Thread Adoption Grows:
As a leading smart home standard, Matter is expanding rapidly, supported by Thread’s low-power, robust mesh networking capabilities. By 2025, Matter+Thread-compatible devices are expected to see a 50% year-over-year increase in shipments compared to 2024. - UWB (Ultra-Wideband) Applications Expand:
With precise positioning and secure communication, UWB is finding use beyond smart locks and asset tracking. In 2025, UWB will be widely applied in smart car keys, warehouse navigation, indoor positioning, and AR interactions, with an estimated 150 million compatible devices shipped globally. - LoRaWAN Strengthens Its Position:
Known for its ultra-low power and long-range capabilities, LoRaWAN continues to thrive in agriculture, environmental monitoring, and logistics. By 2025, the number of LoRaWAN-connected nodes is projected to exceed 2 billion globally. - Bluetooth 5.4 Gains Momentum:
The latest iteration of Bluetooth enhances bandwidth and stability, enabling high-data-rate applications in wearables, healthcare monitoring, and smart sensors.
Example Chart: Projected Device Shipments by Protocol (2023-2025)
| Protocol | 2023 | 2024 | 2025 (Forecast) |
|---|---|---|---|
| Matter + Thread | 0.8B | 1.2B | 1.8B |
| UWB | 0.6B | 1.0B | 1.5B |
| LoRaWAN | 10B | 15B | 20B |
| Bluetooth 5.4 | 15B | 20B | 26B |
(Note: Data is illustrative and based on trend projections.)
System Platforms: Tailored Solutions for Industry Needs
By 2025, IoT platforms are shifting away from generic public cloud IoT PaaS offerings toward more specialized, tailored, and sustainable solutions.
- Open Source and Modular Development:
Developers are increasingly turning to open-source frameworks and modular tools for flexible and cost-effective system integration. This approach simplifies the deployment of protocol stacks, data management modules, and AI inference engines. - Decline of Public Cloud IoT PaaS:
While public PaaS platforms excel in scalability, they often lack the adaptability required for niche industry needs. Users are moving towards private or hybrid cloud solutions, or platforms designed specifically for vertical markets. - Industry-Specific Customization and Value Creation:
Platforms are now expected to deliver direct business value. For instance, an agricultural IoT platform must demonstrably increase yield and land utilization, while logistics platforms should directly optimize inventory and transportation costs.
Comparison Table: Evolution of IoT Platforms
| Metric | Early Stage (2020-2023) | 2025 Trends |
|---|---|---|
| Deployment Model | Primarily public PaaS | Hybrid/private cloud |
| Technical Approach | Closed monolithic systems | Open-source + modularity |
| Revenue Model | Per connection/traffic | Based on data value |
| Industry Adaptability | Generalized solutions | Deep vertical integration |
| Value Realization | Indirect (via data analysis) | Direct (real-time decisions) |
(Data and trends are indicative.)
Embedded Hardware and the Evolution of SoC + AI Chips
In 2025, IoT hardware trends emphasize integration, cost-efficiency, and advanced AI capabilities.
- SoC Becomes Standardized:
Highly integrated System-on-Chip (SoC) solutions combine control, storage, sensor interfaces, and basic AI acceleration, reducing costs and simplifying designs. - Segmented Communication Modules and Low Power:
Modules tailored for specific use cases (e.g., home, wearable, industrial, healthcare) proliferate, with low power consumption a key design focus. - AI-Embedded Chips Improve and Cost Drop:
Edge AI chips are evolving from basic inference to running subsets of large models locally. By 2025, mid-range IoT devices are expected to deliver 30%-50% higher AI inference performance (TOPS metric) compared to 2023, with a 20% reduction in per-chip cost.
Chart: Performance, Power Consumption, and Cost Trends for AI Chips (Indexed to 2023)
| Metric | 2023 | 2024 | 2025 (Forecast) |
|---|---|---|---|
| Performance (TOPS) | 100 | 130 | 150 |
| Power Consumption | 100 | 90 | 80 |
| Cost | 100 | 85 | 80 |
(Improvements in performance and efficiency lower the cost of AI capabilities.)
Comprehensive AI Integration: From Consumer Devices to Industrial and Healthcare Applications
AI large models combined with IoT are driving significant transformations across consumer, industrial, and healthcare sectors.
Edge AI + Cloud AI Fusion
- From Edge Computing to "Edge Brains":
Edge AI evolves from supplementing cloud-based intelligence to becoming an independent decision-making unit. For example, smart home security cameras can detect and respond to anomalies locally without cloud reliance.
Consumer AI Explodes
- Smarter Consumer Devices:
Smart home products like speakers, TVs, and robots will actively predict user needs, offering personalized experiences. For example, a smart speaker might proactively recommend music or adjust lighting and temperature when family members arrive home. - Data-Driven Value-Added Services:
Manufacturers will use over-the-air (OTA) updates to continually enhance device AI models, improving user experiences and creating long-term value.
Industrial AI Applications
- Business Process Optimization:
Data from IoT sensors is now being used to refine production processes, optimize inventory, and enhance equipment maintenance. AI models trained on high-quality datasets enable precise predictions and actionable insights. - Data Governance and Model Optimization:
The focus shifts from hardware expansion to leveraging high-quality data to train precise models that deliver tangible business outcomes.
AI in Healthcare Devices
- AI-Powered Medical Equipment:
Devices such as smart blood pressure monitors or ECG wearables will integrate AI modules and large model assistance, providing early warnings and personalized health insights.
Data Value for Industrial AI Applications
- From Visualization to Deep Intelligence:
IoT has accumulated massive amounts of data over the years. While early use cases emphasized visualization, AI large models will unlock deeper correlations and predictive insights, enabling businesses and users to make optimal decisions in complex environments.
2025 IoT Trends Conclusion
The IoT industry in 2025 is poised for transformation across the following dimensions:
- Infrastructure: Communication protocols like Matter + Thread, UWB, LoRaWAN, and Bluetooth 5.4 are becoming more diverse and advanced. SoC and AI chip adoption is enabling smarter decision-making at the edge.
- Platforms: Open-source modular platforms and industry-specific solutions are replacing generic PaaS systems, emphasizing direct business value creation.
- AI Integration: Consumer devices are becoming smarter, while industrial and healthcare applications focus on data value extraction, process optimization, and personalized services.
- Data and Intelligence: IoT is evolving from merely "connecting things" to "understanding things," transitioning from reactive operations to proactive decision-making.
As data, models, and hardware co-evolve, IoT in 2025 will redefine connectivity, moving towards predictive, context-aware, and intelligent ecosystems. This will drive industry upgrades, enhance everyday life, and create new growth opportunities.