Ultra-Wideband Radar-Based Sensing Poultry Litter Moisture Content Monitoring System

High litter moisture content (LMC) in poultry houses is a primary driver of footpad dermatitis, elevated ammonia emissions, and bacterial proliferation. These conditions directly compromise broiler welfare and productivity. Existing monitoring methods, including oven-drying, contact-based sensors, and near-infrared spectroscopy, suffer from invasiveness, single-point limitation, or surface-only measurement. This study investigates ultra-wideband (UWB) impulse radar as a non-contact sensing modality for estimating the LMC of cedar wood shaving bedding under controlled laboratory conditions. A four-phase experimental program was conducted. Phases 1–3 characterized signal–moisture relationships across 0–50% LMC, manure simulant contamination, and bedding structural changes (loose, compacted, caked). Phase 4 tested whether UWB radar can estimate litter LMC when a stationary broiler body obstructs the beam under combined contamination and structural conditions. A progressive feature engineering approach and an SVC-gated mixture-of-experts regression architecture were used to address each confounding factor. Full technical details are provided in the Methods Section. Under clean conditions, the baseline model achieved R2=0.97 and RMSE = 2.48% LMC. Under combined realistic conditions (manure contamination, caked bedding, centered carcass), the full pipeline achieved R2=0.91 and RMSE = 4.53% LMC, with 98.8% bird detection accuracy from the radar signal alone. These laboratory findings suggest that the UWB radar can sense litter moisture through a stationary broiler body. The results support its potential as the sensing core of a non-contact monitoring system for precision poultry farming.

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Publication Details

Journal
Animals
Published
2026-04-30
DOI
https://doi.org/10.3390/ani16091382
Primary Topic
RFID technology advancements
Type
article
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article

Ultra-Wideband Radar-Based Sensing Poultry Litter Moisture Content Monitoring System

Shungeng Zhang, Zi Wang, Zhenyu Qi, Guoming Li et al.
Animals
RFID technology advancements
article

Ultra-Wideband Radar-Based Sensing Poultry Litter Moisture Content Monitoring System

Shungeng Zhang, Zi Wang, Zhenyu Qi, Guoming Li, Tanvir Ahmed, Haotang Li, Sen He
article en

Abstract

High litter moisture content (LMC) in poultry houses is a primary driver of footpad dermatitis, elevated ammonia emissions, and bacterial proliferation. These conditions directly compromise broiler welfare and productivity. Existing monitoring methods, including oven-drying, contact-based sensors, and near-infrared spectroscopy, suffer from invasiveness, single-point limitation, or surface-only measurement. This study investigates ultra-wideband (UWB) impulse radar as a non-contact sensing modality for estimating the LMC of cedar wood shaving bedding under controlled laboratory conditions. A four-phase experimental program was conducted. Phases 1–3 characterized signal–moisture relationships across 0–50% LMC, manure simulant contamination, and bedding structural changes (loose, compacted, caked). Phase 4 tested whether UWB radar can estimate litter LMC when a stationary broiler body obstructs the beam under combined contamination and structural conditions. A progressive feature engineering approach and an SVC-gated mixture-of-experts regression architecture were used to address each confounding factor. Full technical details are provided in the Methods Section. Under clean conditions, the baseline model achieved R2=0.97 and RMSE = 2.48% LMC. Under combined realistic conditions (manure contamination, caked bedding, centered carcass), the full pipeline achieved R2=0.91 and RMSE = 4.53% LMC, with 98.8% bird detection accuracy from the radar signal alone. These laboratory findings suggest that the UWB radar can sense litter moisture through a stationary broiler body. The results support its potential as the sensing core of a non-contact monitoring system for precision poultry farming.

AnimalsVol. 16(9)
University of Arizona (US), University of Georgia (US), Augusta University (US)
Openalex Percentile: Top 7%
RFID technology advancements
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