Abstract
Tractor operations during tillage are a major source of occupational noise exposure in agriculture, posing significant risks to operators’ hearing health and wellbeing. This study uses smart monitoring system in analyzing tractor noise levels during tillage operations. Real-time noise measurements were collected from an experimental field measuring 160 m × 38 m (4,480 m²), divided into three blocks with nine subplots at the implement-soil interaction zones. Noise data was acquired using a wireless sound level meter and an iPhone 15 Pro Max. High-resolution noise maps were generated using ArcGIS 10.3.1 (ESRI, USA) with the Inverse Distance Weighting (IDW) interpolation method, providing detailed spatial noise distribution. During tillage operations (ploughing, harrowing, and ridging), the tractor operator maintained forward speeds of 5, 7, and 9 km/h to assess noise variations. The results indicate that engine speed and implement dynamics are the dominant noise contributors with levels 71.30 dB, 79.00 dB, and 81.70 dB at a speed of 5, 7 and 9 km/h, were within the Global standard for safe noise exposure limits to protect workers, but higher than NESREA (2009) recommended noise limits. At setback distances of 5 m, 10 m, and 15 m, the noise levels decreased from 71.30 dB to 70.9 dB and finally to 54.00 dB. This indicates that the noise on farm personnel becomes harmless at a distance of 15 m and beyond. The noise maps developed for the different tillage operations illustrate how noise levels vary with setback distance. As the distance increases, noise levels decline across all tractor speeds, supported by high coefficients of determination (R²) ranging from 0.77 for ploughing to 0.93 for both harrowing and ridging operations. This study demonstrates that smart noise monitoring systems can improve safety, reduce hearing risks, and ensure compliance with noise regulations in mechanized agriculture.
Keywords
Tillage Operation, Noise Assessment, Setback Distance, Noise Mapping, Smart Monitoring
Citations
IRE Journals:
Pene Barikuma, Kanee Baridakara, Saue Friday Raphael "Noise Level Assessment of Tractors in Operation: A Smart Approach to Tillage Activities" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 539-546 https://doi.org/10.64388/IREV9I9-1714862
IEEE:
Pene Barikuma, Kanee Baridakara, Saue Friday Raphael
"Noise Level Assessment of Tractors in Operation: A Smart Approach to Tillage Activities" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1714862
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