Assortment of Tech Solutions Enable the Smart Home

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.

Figure 1
According to research from 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.

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.

Aware Appliances

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).

Figure 2
The Failure Detection e-AI Solution with embedded AI (e-AI) enables failure detection of home appliances—such as refrigerators, air conditioners and washing machines—due to motor abnormality.

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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MCU-based Solution Enables Offline Facial Recognition

NXP Semiconductors has unveiled what it claims is world’s first MCU-based solution for adding offline face and expression recognition capabilities to smart home, commercial and industrial devices. Built on NXP’s latest crossover MCU, the i.MX RT106F, running FreeRTOS, the new MCU-based face recognition solution enables original equipment manufacturers (OEMs) to quickly, easily and inexpensively incorporate face, expression and emotion recognition into a diverse range of IoT products.

The i.MX RT106F leverages NXP’s OASIS face processing engine and uses a neural network to perform face detection, recognition and anti-spoofing, without the need for cloud connectivity. OEMs can take advantage of NXP’s hardware and software-based platform to offer advanced human machine interface (HMI) capabilities that can anticipate and personalize the end user’s experience with smart edge devices such as smart appliances, thermostats, lighting, alarms and power tools.

The MCU-based face recognition solution bundles everything required to implement accurate, low latency face and expression recognition using an ultra-small form factor that fits into existing applications. The self-contained platform includes production ready pre-certified hardware and software tools, and NXP’s fully integrated OASIS face processing engine for face and expression recognition with camera and display drivers. In addition to creating the easiest path to adding these capabilities to MCU-based devices, the all-inclusive offering clears away any need for specialized expertise, supply chains or logistics.

NXP is now engaging with OEMs to provide early access to the evaluation and development kit for this solution, and broad market availability is expected to begin in Q1 2020. More information can be found at www.nxp.com/mcu-face-recognition

NXP Semiconductors www.nxp.com

MPU Targets AI-Based Imaging Processing

Renesas Electronics has now developed a new RZ/A2M microprocessor (MPU) to expand the use of artificial intelligence (e-AI) solutions to high-end applications. The new MPU delivers 10 times the image processing performance of its predecessor, the RZ/A1, and incorporates Renesas’ exclusive Dynamically Reconfigurable Processor (DRP), which achieves real-time image processing at low power consumption. This allows applications incorporating embedded devices–such as smart appliances, service robots, and compact industrial machinery–to carry out image recognition employing cameras and other AI functions while maintaining low power consumption, and accelerating the realization of intelligent endpoints.
Currently, there are several challenges to using AI in the operational technology (OT) field, such as difficulty transferring large amounts of sensor data to the cloud for processing, and delays waiting for AI judgments to be transferred back from the cloud. Renesas already offers AI unit solutions that can detect previously invisible faults in real time by minutely analyzing oscillation waveforms from motors or machines. To accelerate the adoption of AI in the OT field, Renesas has developed the RZ/A2M with DRP, which makes possible image-based AI functionality requiring larger volumes of data and more powerful processing performance than achievable with waveform measurement and analysis.

Since real-time image processing can be accomplished while consuming very little power, battery-powered devices can perform tasks such as real-time image recognition based on camera input, biometric authentication using fingerprints or iris scans, and high-speed scanning by handheld scanners. This solves several issues associated with cloud-based approaches, such as the difficulty of achieving real-time performance, assuring privacy and maintaining security.

The RZ/A2M with DRP is a new addition to the RZ/A Series lineup of MPUs equipped with large capacity on-chip RAM, which eliminates the need for external DRAM. The RZ/A Series MPUs address applications employing human-machine interface (HMI) functionality, and the RZ/A2M adds to this capability with features ideal for applications using cameras. It supports the MIPI camera interface, widely used in mobile devices, and is equipped with a DRP for high-speed image processing.

Renesas has also boosted network functionality with the addition of two-channel Ethernet support, and enhanced secure functionality with an on-chip hardware encryption accelerator. These features enable safe and secure network connectivity, making the new RZ/A2M best suited for a wide range of systems employing image recognition, from home appliances to industrial machinery.

Samples of the RZ/A2M with DRP are available now. The RZ/A2M MPUs are offered with a development board, reference software, and DRP image-processing library, allowing customers to begin evaluating HMI function and image processing performance. Mass production is scheduled to start in the first quarter of 2019, and monthly production volume for all RZ/A2M versions is anticipated to reach a combined 400,000 units by 2021.

Renesas Electronics | www.renesas.com

Integrated Wi-Fi System in Package Module

EconaisThe EC19W01 is a small, smart, highly integrated 802.11b/g/n Wi-Fi system in package (SiP) module. The module is well suited for home automation and smart appliances; Wi-Fi audio speakers and headphones; wireless sensors and sensor networks; wireless monitoring (audio and video); smart appliances; health care and fitness devices; wearable devices; security, authentication, and admittance control; lighting; building/energy/industrial management/control; cloud-connected devices; remote control, data acquisition, and monitoring; and machine-to-machine (M2M) and Internet of Things (IoT) design.

The EC19W01’s features include an integrated 32-bit processor to support application customization, on-board flash and antenna, low power consumption, support for Serial-to-Wi-Fi and SPI-to-Wi-Fi, wireless transmit/receive rates of up to 20 Mbps, and a small 14-mm × 16-mm × 2.8-mm footprint.

Contact Econais for pricing.

Econais, Inc.
www.econais.com