AIoT - The Intersection of Artificial Intelligence and IoT
Nov 10, 2023
AIoT, or the amalgamation of Artificial Intelligence (AI) with the Internet of Things (IoT), is driving innovation in the electronics industry. According to one IC manufacturer, it will become the largest segment in the microcontroller market within the next ten years.[1]
The advent of IPv6 (Internet Protocol version 6) opened up an almost unimaginably large address space for IoT devices - enough unique addresses to individually identify every grain of sand on Earth many times over. This removes any practical limitation on the number of IoT devices.
With concepts such as smart cities, smart industry, smart transportation and smart homes, billions of IoT devices are being deployed. The challenge is managing this vast number of sensors streaming data or requesting instructions. The volume of information can overwhelm remote data servers or SCADA (Supervisory Control and Data Acquisition) systems.
With concepts such as smart cities, smart industry, smart transportation and smart homes, billions of IoT devices are being deployed. The challenge is managing this vast number of sensors streaming data or requesting instructions. The volume of information can overwhelm remote data servers or SCADA (Supervisory Control and Data Acquisition) systems.
Using AIoT Systems to Manage Big Data with Intelligence
AIoT enables self-organizing systems to create local processing loops where data from multiple sensors is collected, analyzed, and acted upon—without requiring top-level intervention (Figure 1).
Fig. 1: AIoT concept block diagram
The IoT network is responsible for data collection and communication, while machine learning (AI) provides real-time pattern recognition, predictive analytics, and automated responses.
Key advantages of AIoT include:
- Scalability - More sensors can be added without overwhelming the network
- Real-time pattern recognition - Edge computing processes data locally, reducing transmission delays
- Faster reaction times - System responses occur within milliseconds rather than seconds
- Fault tolerance - AI identifies inaccurate or missing data and bypasses defective nodes
- Fewer human errors - Automated decision-making reduces reliance on manual inputs
These advantages will lead to across-the-board innovations in many ‘smart’ systems, from smart cities that will continuously monitor and analyze real-time traffic flow data to recognize accidents, prioritize emergency vehicles and optimize public transport, to smart grids that can optimize grid balancing, load sharing and the integration of renewable energy and energy storage systems into the system, to smart healthcare that uses wearables to monitor and predict medical emergencies, to smart industry, with effective just-in-time supply chain management, optimized production lines and condition-based maintenance, to name just a few buzzwords.
AIoT and The Role of Smart Power Supplies
Reliable power is critical for AIoT deployments. While some propose energy harvesting or long-life batteries as solutions, these approaches have significant limitations. A million IoT sensors powered by ten-year batteries would require replacing 275 batteries per day—an impractical solution.An AC/DC power supply is not just a power source—it becomes an active component of the AIoT system when integrated with a digital communication interface such as the PM-bus protocol.
PMBus - Digital Power Supply Control for AIoT
The PMBus protocol, an extension of the I²C (Inter-Integrated Circuit) standard, enables remote power supply monitoring, voltage adjustments, and fault detection with low-cost implementation.
Fig. 2: RACM1200-V power supply monitoring signals and timing
Key Benefits of PMBus for AIoT:
- Remote power control - Switch power supplies on/off or place them in standby mode
- Voltage and current adjustments - Modify output levels based on AI predictions
- Real-time diagnostics - Monitor temperature, input line conditions, and error codes
- Fault prevention - AI can anticipate load peaks and preemptively adjust power settings
PMBus for AI-Driven Power Management
AI algorithms can detect usage patterns and dynamically optimize power supply settings. For example, in battery charging applications, an AI system can:- Reduce thermal cycling by maintaining stable operating temperatures
- Adjust fan speeds based on real-time power demand
- Prevent overload shutdowns by preemptively switching power modes
Fig. 3: PM-bus signal. Each line can only be pulled down, relying on resistors to pull up the signal lines back up to VDD. With higher bus capacitances, the rise time of the signal gets longer.
While PMBus allows up to 127 devices on a single bus, excessive capacitance can degrade signal integrity. The solution is PMBus repeater ICs, which segment power supply groups into manageable clusters (Figure 4).
Fig. 4: PM-Bus repeater IC powered from the ‘always on’ 5V auxiliary output.
These repeaters, powered by an "always-on" 5V auxiliary output, enable:
- Extended bus length for large AIoT installations
- Low-power operation for continuous remote monitoring
- LoRa integration for long-range wireless control
Smart Power Supply Interfaces: Enhancing AIoT Performance
Bus-controllable power supplies, like the RACM1200-V, feature digital communication interfaces that provide:- Multicolor LED status indicators for instant diagnostics
- Pre-warning alerts for voltage fluctuations and over-temperature conditions
- Programmable thresholds to give AI systems time to react before faults occur
AIoT and the Future of Smart Power Management
AIoT is transforming industries with intelligent automation, real-time analytics, and self-optimizing networks. As a global leader in AC/DC and DC/DC conversion, RECOM is actively developing PMBus-enabled power supplies to support the next generation of AIoT systems.[1] Remi El-Ouazzane „A Tsunami of TinyML Devices is Coming”, EE Times, 07.28.2023
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