STMicroelectronics is Making Everything Smarter at IoT Asia 2019

ST showcases comprehensive solutions for Connectivity, Artificial Intelligence, NFC for Smart Home and Smart Retail, and Sensors for Smart Industry

ST is also participating in a panel session to discuss the key considerations for integrating AI with existing business processes on 28 March

STMicroelectronics demonstrated its latest solutions for the Internet of Things (IoT) at IoT Asia, Singapore Expo, March 27-28, 2019. At the event, ST highlights its rich portfolio of solutions for Making Cities and Factories Smarter.

Making Cities Smarter: The NFC Experience Wall by ST is showing an integration of solutions for Smart Retail and Smart Home including an NFC tag with tamper detection for product identification and anti-cloning, an NFC sensor node to monitor environmental and motion variations, a lighting application enabled by a new NFC/RFID tag for convenient dimming configurations, and a people-tracking demo enabled by ST’s UHF reader technology.

In connectivity, ST showcases its industry-leading STM32 microcontroller (MCU) solutions for NB-IoT and 3G/2G cellular connectivity, the LoRa LPWAN (long-distance communication) offering for machine-to-machine (M2M) and IoT applications, a multiple-protocol network based on the wireless STM32WB MCU, and a smart bulb demo that is able to reach multiple IoT nodes through BLE mesh and provides a turn-key solution to monitor, control, and operate the network nodes through a smartphone.

The show highlights also include ST’s solutions for Artificial Intelligence (AI) that enable Neural Networks to run easily and fast on STM32 MCUs using the STM32CubeMX.AI. Applications showcased at IoT Asia include character recognition, human-activity detection, and object classification.

Making Factories Smarter: ST showcased a vibration-monitoring demo using a cost-effective MEMS accelerometer and IO-Link industrial connectivity. Inertial and environmental sensors connected via IO-Link are used to detect the status of the motor, making it possible to predict degradation or failures. The integrated STM32F4 MCU performs local real-time frequency and time-domain analysis for condition monitoring and early motor-failure detection.

Another industrial application demo on display shows the ultrasound detection of gas leakage using an analog MEMS microphone.