Performance Analysis of the MPU6050 Sensor for Room Inclination Measurement Based on the Internet of Things - Arfansyah, Fabian Faiz; Sujono, Sujono (Yayasan Kawanad, 2026)
Building safety monitoring has grown increasingly dependent on low-cost sensing solutions — and for good reason. Structural tilt, when left undetected, accumulates into deformation patterns that compromise both occupant safety and long-term building integrity. This study developed an IoT-based room inclination monitoring system by pairing an MPU6050 inertial sensor with an ESP32 microcontroller to capture, process, and transmit tilt data across three measurement axes in real time. The system computes pitch and roll angles from raw accelerometer outputs and delivers the results through a web-based interface, allowing users to record wall and floor orientations independently before calculating the combined inclination angle via the dot product method. Ten repeated trials were conducted against a calibrated 90° wall-to-floor reference angle to assess system reliability. The mean recorded angle was 88.06°, reflecting a deviation of 1.94° from the reference — a gap narrow enough to confirm basic functional validity, yet wide enough to warrant concern in precision-critical contexts. All measured values fell consistently below the 90° threshold, suggesting a systematic offset rather than random error. The absence of digital filtration — no Kalman or Complementary filter was applied to the raw data — appears to be the primary contributor to this pattern, compounded by minor sensor placement inconsistencies during testing. Future work must address calibration offset correction and signal noise attenuation before the system can be considered adequate for structural health monitoring or smart building applications.