We engineered a sensor-to-cloud monitoring pipeline that helps factory operators identify machine wear before failure occurs.
Designing for Rugged Environments
Factory floors are filled with electromagnetic interference. We designed custom sensor nodes built on STM32 microcontrollers, routing telemetry over RS-485 Modbus backplanes to a central LoRaWAN gateway. The gateway pushes data packets to AWS IoT Core for analysis.
Code Snippet
// Python snippet: Running FFT on vibration data stream
import numpy as np
def analyze_vibration(raw_data, sample_rate):
n = len(raw_data)
fft_vals = np.fft.fft(raw_data)
fft_freqs = np.fft.fftfreq(n, 1/sample_rate)
peak_freq = fft_freqs[np.argmax(np.abs(fft_vals))]
return peak_freq
# Used to detect shift in mechanical resonant frequencies.Frequently Asked Questions
What communication frequency was used?
We selected LoRaWAN (868/915 MHz) for its high penetration through metal structures and low power consumption.