Multimodal digital sensing of early-life laying hens: a pilot study integrating thermal, acoustic, optical-flow and environmental data

Early-life development profoundly shapes long-term welfare in laying hens, yet monitoring remains constrained by subjective assessment and fragmented single-modality tools. This pilot study evaluated the technical feasibility of a stratified multimodal sensing approach: thermal imaging and environmental monitoring across all five rooms ( n = 150 Lohmann LSL-Lite chicks) vs. detailed audio and video analyses limited to one representative room ( n = 30 birds) to manage annotation workload, from hatch to 20 weeks. One hundred fifty Lohmann LSL-Lite chicks were housed across five controlled rooms; thermal and environmental data were collected system-wide, whilst detailed audio and video analyses focused on one representative room to manage annotation workload. Weekly aggregated features included head and foot surface temperatures, acoustic spectral descriptors, optical-flow movement metrics around caretaker entry, and ambient conditions. Thermal imaging revealed age-related increases and stabilization of peripheral temperatures, with foot temperature showing a pronounced developmental effect (η 2 = 0.51). Acoustic features shifted systematically across weeks (all p < 0.001), consistent with vocal maturation. Optical-flow analysis revealed strong early reactivity to caretaker presence that declined markedly with development (early weeks 5–10 vs. late weeks 11–20: t = 28.12, p = 0.00126). Z -score-normalized multimodal trajectories and Pearson correlation analysis (Benjamini-Hochberg FDR, q < 0.05) demonstrated strong within-modality consistency ( r = 0.85–0.96) and selective associations between environmental humidity and acoustic features ( r = 0.65–0.70), whilst thermal, acoustic, and behavioral domains remained largely independent. This descriptive pilot—thermal and environmental data from all rooms, behavior and vocalization from one cohort—establishes baseline multimodal developmental patterns and validates parallel sensing as a foundation for future welfare-relevant monitoring in precision poultry farming.