Predictive Maintenance for Elevators in High Footfall Areas
Enabling Predictive Maintenance Solutions for Elevators in USA
Our client, operating in the US, needed a robust solution to ensure the seamless operation of elevators in high-footfall environments. With elevators in constant use 24/7, minimizing downtime through predictive maintenance was critical. The client did not have the specialized expertise to solve the issue quickly.
Our embedded engineering team was tasked with designing and implementing a BLE-based (Bluetooth Low Energy) system to continuously monitor elevator motors and predict potential failures. The solution required a BLE node for data acquisition and a gateway for data processing and transmission to the cloud.
Solution: Implementing BLE Nodes and Gateway for Predictive Maintenance
We developed a comprehensive system consisting of BLE nodes for vibration analysis and a BLE gateway for centralized data collection and processing.
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BLE Node Design & Implementation
The BLE node was designed to perform real-time vibration analysis on elevator motors, helping detect any potential anomalies before they cause breakdowns.
- IMU Sensor Data Acquisition: Using a combination of a 3-axis accelerometer, 3-axis gyroscope, and 3-axis magnetometer, the BLE node continuously captures data on motor vibrations.
- Wireless Data Transmission: The acquired data is securely sent to the gateway via BLE 5.1.
- Advanced Vibration Analysis: The node supports both time and frequency domain analysis, as well as vector analysis for precise anomaly detection.
- Over-the-Air (OTA) Updates: OTA firmware updates ensure the node is always running the latest software, minimizing maintenance disruptions.
Hardware Specifications:
- Controller: STM32 microcontroller for efficient processing.
- Wireless: BLE 5.1 for low-power, reliable communication.
Key Features:
- Time and frequency domain analysis.
- Secure BLE communication.
- BLE OTA for firmware updates.
- Auto-provisioning with the gateway for seamless deployment.
Gateway Design & Implementation
The BLE gateway aggregates data from multiple nodes and performs initial edge computing, sending processed insights to the cloud for advanced analytics.
- Data Aggregation: Multiple BLE nodes communicate with the gateway, enabling centralized monitoring of all elevators in the facility.
- Secure Data Transfer: The gateway maintains a secure BLE connection with the nodes and transfers data to the cloud via Wi-Fi, ensuring data integrity.
- Edge Computing Capabilities: The powerful quad-core ARM Cortex-A CPU supports edge processing, reducing latency and improving real-time response.
- OTA Updates via Azure IoT: Firmware updates are pushed to BLE nodes through the Azure IoT platform, ensuring a scalable and manageable system.
Hardware Specifications:
- CPU: Quad-core ARM Cortex-A
- Memory: 4GB DDR4 RAM, 64GB Flash
- Platform: Embedded Linux with BLE 5.1
Key Features:
- Secure BLE-to-Wi-Fi gateway.
- Sensor data logging in a local database for redundancy.
- Azure integration with Device Twins and auto-provisioning.
- Edge computing for real-time predictive maintenance insights.
Impact
The project successfully deployed a BLE-based predictive maintenance system, enabling real-time monitoring and analysis of elevator motors. The solution allowed for the seamless communication of multiple BLE nodes using secure BLE protocols. This implementation has significantly improved uptime and operational efficiency for elevators in high-demand environments, reducing unexpected downtime and maintenance costs.
