Poultry Farm Intelligence: An Integrated Multi-Sensor AI Platform for Enhanced Welfare and Productivity

2025-10-17

AI Summary

Small- and medium-scale poultry farms face challenges in concurrently enhancing animal welfare, environmental compliance, and production efficiency, largely hindered by the lack of low-cost, integrated intelligent monitoring tools—leading to continued reliance on manual inspection. This study proposes a modular, cost-effective multi-sensor AI platform that pioneers the integration of edge computing with prescription-based AI, enabling a paradigm shift from reactive response to proactive anomaly预警. The platform innovatively employs evolutionary algorithms to optimize camera placement and fuses synchronized audio-video streams with feeding data, achieving 100% real-time egg counting via a lightweight edge vision model (Raspberry Pi 5). It further integrates time-series forecasting with an environment-aware recommendation system to jointly optimize welfare and productivity. Field trials demonstrate its high robustness in anomaly detection and reliable short-term yield prediction performance.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: Multi-modal Vision
• Machine Learning: Learning on the Edge & Model Compression

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Poultry farming faces increasing pressure to meet productivity targets while ensuring animal welfare and environmental compliance. Yet many small and medium-sized farms lack affordable, integrated tools for continuous monitoring and decision-making, relying instead on manual, reactive inspections. This paper presents Poultry Farm Intelligence (PoultryFI) - a modular, cost-effective platform that integrates six AI-powered modules: Camera Placement Optimizer, Audio-Visual Monitoring, Analytics & Alerting, Real-Time Egg Counting, Production & Profitability Forecasting, and a Recommendation Module. Camera layouts are first optimized offline using evolutionary algorithms for full poultry house coverage with minimal hardware. The Audio-Visual Monitoring module extracts welfare indicators from synchronized video, audio, and feeding data. Analytics & Alerting produces daily summaries and real-time notifications, while Real-Time Egg Counting uses an edge vision model to automate production tracking. Forecasting models predict egg yield and feed consumption up to 10 days in advance, and the Recommendation Module integrates forecasts with weather data to guide environmental and operational adjustments. This is among the first systems to combine low-cost sensing, edge analytics, and prescriptive AI to continuously monitor flocks, predict production, and optimize performance. Field trials demonstrate 100% egg-count accuracy on Raspberry Pi 5, robust anomaly detection, and reliable short-term forecasting. PoultryFI bridges the gap between isolated pilot tools and scalable, farm-wide intelligence, empowering producers to proactively safeguard welfare and profitability.

Problem

• Optimizing camera placement for full poultry house coverage
• Automating welfare monitoring through audio-visual data analysis
• Predicting production metrics and providing operational recommendations

Innovation

• Evolutionary algorithms optimize camera placement for coverage
• Edge vision model automates real-time egg counting
• AI integrates forecasts with weather for recommendations