## 2 Foundational Concepts
### IoT in Advanced Networks  
The IoT encompasses vast networks of interconnected physical objects and devices, enabling them to collect, exchange, and act upon data, often without direct human intervention [24,25]. This ecosystem is characterized by its massive scale and significant heterogeneity in terms of hardware capabilities, power sources, connectivity, and the types of data generated in real time [6], as summarized in Table 2. To better understand the context for integrating advanced AI, it is useful to consider key IoT sub-domains:* Massive IoT (MIoT): This segment focuses on connecting a very large number of low-cost, low-power devices (e.g., in smart metering or environmental monitoring) that typically transmit small amounts of data infrequently. Key challenges include ensuring scalability to billions of devices, long battery life, and managing connectivity for devices with severely limited local processing capabilities. The data, while individually small, can be voluminous in aggregate [26]. * Industrial IoT (IIoT): Applied in sectors like manufacturing and energy, IIoT prioritizes high reliability, low latency, and robust security for critical operations such as predictive maintenance and process automation. IIoT systems often generate large volumes of high-frequency, time-sensitive data from sophisticated sensors and machinery, frequently necessitating a strong trend towards edge computing for localized processing and real-time analytics [27]. * Artificial Intelligence of Things (AIoT): AIoT signifies the convergence of AI technologies with IoT infrastructure, aiming to embed AI capabilities, including machine learning and potentially Large Language Models (LLMs), into IoT devices, edge gateways, or associated platforms. This facilitates intelligent decision-making and autonomous operations across diverse applications (e.g., smart homes, intelligent transportation). A primary challenge in AIoT is managing the computational demands of AI models on typically resource-constrained IoT hardware [28]. \begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Characteristic** & **Massive IoT (MIoT)** & **Industrial IoT (IIoT)** & **Artificial Intelligence of Things (AIoT)** & **General Consumer IoT** \\ \hline Primary Goal & Wide-scale, low-cost data collection from numerous simple devices [29] & High-reliability, low-latency control and monitoring of critical industrial processes & Enhanced automation, intelligent decision-making, and adaptive behavior through AI/ML at the edge/device & Convenience, automation, and enhanced user experience in daily life \\ \hline Typical Applications & Smart metering, environmental monitoring, asset tracking, smart agriculture (large-scale sensor networks) & Manufacturing automation (PLCs, SCADA), predictive maintenance, robotics, process control, smart grids & Smart surveillance (intelligent video analytics), autonomous vehicles/drones, advanced robotics, personalized healthcare monitors, smart retail & Smart home devices (lights, thermostats, speakers), wearables (fitness trackers), connected appliances \\ \hline Data Types and Volume & Small data packets, often infrequent; high volume due to massive device numbers; primarily sensor readings (temperature, humidity, location, status) & Time-series sensor data (vibration, pressure, temperature), control signals, machine status, production data; moderate to high volume per device, often continuous & Multimodal data (video, audio, sensor fusion, text), complex features extracted by AI models; volume varies greatly depending on AI task [30] & User commands (voice, app), sensor data (activity, environment), media streams; volume varies, can be high for media \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of IoT characteristics. Across these varied IoT deployments, and particularly as AIoT applications become more sophisticated, the inherent resource limitations (such as CPU, memory, battery, and power budgets) of many end devices and even edge nodes represent a primary bottleneck.