IoT-Leveraged Living Spaces
From preventive maintenance for appliances to voice-controlled lighting, the subsystems that comprise a modern Smart Home continue to evolve. Providing the building blocks for these implementations, IC vendors are keeping pace with specialized MCUs, sensors platforms and embedded software to meet diverse requirements.
By Jeff Child, Editor-in-Chief
The evolution of Smart Homes is about more than pure convenience. Smart Home technologies are leveraging IoT concepts to improve energy efficiency and security, thanks to intelligent, connected devices. The topic encompasses things like power-saving motor control systems, predictive maintenance, cloud-based voice assistance, remote monitoring and more.
Clearly the market is an attractive one. According to the latest Smart Home Device Database from market research firm IHS Markit, the global Smart Home market is forecast to grow by nearly a factor of five to reach more than $192 billion in 2023, up from $41 billion in 2018 (Figure 1). The report says that the fastest-growing device types in the market include lighting, smart speakers and connected major home appliances.
While it’s impossible to cover all the bases of Smart Home technology in a single article, here we’ll examine the microcontrollers (MCUs), analog ICs and special function chips that MCU vendors are developing to address Smart Home system designs.
An important piece of Smart Home technology is the idea of outfitting major home appliances with sophisticated maintenance features. With that in mind, in January Renesas Electronics launched its Failure Detection e-AI Solution for motor-equipped home appliances, featuring the Renesas RX66T 32-bit MCU. This solution with embedded AI (e-AI) enables failure detection of home appliances—such as refrigerators, air conditioners and washing machines—due to motor abnormality (Figure 2).
Property data showing the motor’s current or rotation rate status can be used directly for abnormality detection, making it possible to implement both motor control and e-AI–based abnormality detection with a single MCU. Using the RX66T eliminates the need for additional sensors, thereby reducing a customer’s bill of materials (BOM) cost.
When a home appliance malfunctions, the motor operation typically appears abnormal when running and being monitored for fault detection in real-time. By implementing e-AI-based motor control-based detection, the failure detection results can be applied not only to trigger alarms when a fault occurs, but also for preventive maintenance. For example, e-AI can estimate when repairs and maintenance should be performed, and it can identify the fault locations. This capability provides home appliance manufacturers the means to boost maintenance operations efficiency and improve product safety by adding functionality that predicts faults before they occur in their products.
The solution uses the Renesas Motor Control Evaluation System and an RX66T CPU card. This hardware is combined with a set of sample program files that run on the RX66T MCU as well as a GUI tool that enables collecting and analyzing property data indicating motor states. In order to detect faults, it is necessary to learn the characteristics of the normal state. Using the GUI tool, system engineers can immediately begin developing AI learning and optimized fault detection functionality. Once the AI models are developed, the e-AI development environment (composed of an e-AI Translator, e-AI Checker and e-AI Importer) can be easily used to import the learned AI models into the RX66T. …
Read the full article in the October 351 issue of Circuit Cellar
(Full article word count: 3115 words; Figure count: 9 Figures).
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