Poultry-Edge-AI-IoT System for Real-Time Monitoring and Predicting by Using Artificial Intelligence

Abstract

Poultry farms have played a significant role throughout human history, in feeding the growing population. A good environment is a perfect condition for the growth of poultry, preventing disease, and effective production. The temperature higher and the humidity favor the growth of bacteria and hence the production of ammonia (NH3) by the decomposition of organic matter. Ammonia (NH3), car-bon monoxide (CO), and carbon dioxide (CO2), Methane (CH4), hydrogen sulfide (H2S) are poisonous gases that can cause poultry diseases and mortality. The combination of Artificial Intelligence (AI), Internet of Things (IoT), and Edge Computing offer efficient and intelligent stand-alone systems of monitoring in real-time, predicting, and advanced automation. The paper aims to monitor in real-time and predict poultry barns' environmental conditions using a Deep Learning algorithm, known as the E-GRU (Encoder Gated Recurrent Unit). An intelligent system called Poultry-Edge-AI-IoT has been developed to gather, hash, store, pretreat, filter, knowledge extract, and transmit information from a heterogeneous wireless sensor network. The Poultry-Edge-AI-IoT system is based on IoT, AI, and Edge Computing for the detection of potential stress, the harmful gas concentration, and the prediction of poultry barns' environmental conditions. The system is modular and upgradeable. The experiment results demonstrated that the Poultry-Edge-AI-IoT system is able to collect correctly the poultry barn environment information, to monitor the potentially harmful gas levels (CH4, H2S, NH3, CO, CO2), and predict the harmful gas levels in the near future.