Part Details for LPS22HB by STMicroelectronics

This solution combines specific ST motion and environmental sensors and the performance STM32F4 MCU and STM32MP157 MPU in a Condition Monitoring and Predictive Maintenance framework that connects multiple sensor nodes to a central data lake such as a Cloud service.<p>Critical vibration data from the three axes ISM330DLC IMU is processed locally on the STM32F4 microcontroller to generate frequency and time domain data, while the LPS22HB and HTS221 sensors provide temperature, pressure and humidity data. The data from up to four sensor nodes are routed through a concentrator to an Edge gateway node based on the STM32MP157 where all the data is consolidated for subsequent processing on server-based or cloud-based systems.<p>In order to expose the potential of a cloud-based solution, we provide a Predictive Maintenance Dashboard application from which Edge gateway nodes running the AWS IoT Greengrass service and AWS IoT core can be provisioned, so that condition monitoring sensor data can be plotted and triggers can be configured as part of your end-to-end Predictive Maintenance solution.

This ultra-low power sensor node features the BlueNRG-2 Bluetooth Low Energy system-on-chip and a suite of ultra-low-power ST sensors, including a magnetometer, gyroscope, accelerometer, pressure, temperature and humidity, MEMS microphone and time-of-flight sensor. It is an ideal solution for applications ranging from smart home to smart agriculture, supply chain management, asset tracking and other industrial applications.<p>The BlueNRG-2 BLE SoC monitors environmental pressure, humidity and temperature sensor data, as well as motion data from the accelerator, gyroscope and magnetometer, which can be processed by firmware on the Cortex M0 core to provide functionality such as event detection and even object tracking in 3D space through powerful MEMS sensor fusion algorithms.<p>The Soc can also transmit obstacle distance information from the embedded time-of-flight sensor data.<p>The MEMS microphone allows audio and music transmission over Bluetooth low energy with appropriate firmware running on the core.<p>The ultra-low power features of each device and BLE connectivity allow a completely wireless node powered by a standard CR2032 coin battery, with the possibility of joining many nodes in extended BLE mesh networks.<p>The solution includes comprehensive firmware with ready-to-use examples, and a BLEsensor app for Android and iOS mobile devices completes the package with data visualization and node control functionality.

This Condition Monitoring and Predictive Maintenance framework combines smart sensor nodes that collect vibration, ultrasound and environmental data with Wi-Fi or cellular connectivity to a central data lake such as a Cloud service.<p>Critical vibration data is processed locally on an STM32L4+ microcontroller by combining 3-axis acceleration data from a 6kHz IIS3DWB vibration sensor and ultrasound data up to 80kHz from a MP23ABS1 microphone sensor, in order to generate frequency and time domain analyses such as FFT, RMS, and Peak Acceleration. Environmental pressure, temperature and humidity data is also collected by the LPS22HB and HTS221 sensors embedded on the node.<p>The very low power requirements of the MCU and the sensors allow for compact, battery-operated nodes driven by the STBC02 battery charger.<p>The STM32L4+ microcontroller supports wireless data transmission through an additional Wi-Fi module such as the Inventek ISM43362.M3G-L44, or via a cellular modem such as the Quectel BG96, which supports LTE Cat M1 and NB-IoT connectivity with a plastic Micro-SIM (3FF).<p>ST provides a Predictive Maintenance Dashboard application based on AWS IoT core and other AWS services to provision nodes, plot data, and configure triggers as part of an end-to-end solution