IoT and Deep Learning for Livestock Management

Abstract

Livestock management is a critical issue for the farming industry as proper management including their health and well-being directly impacts the production. It is difficult for a farmer or shed owner to monitor big herds of cattle manually. This chapter proposes a layered framework that utilizes the power of internet of things (IoT) and deep learning (DL) to real-time livestock monitoring supporting the effective management of cattle. The framework consists of sensor layer where sensor-rich devices or gadgets are used to collect various contextual data related to livestock, data processing layer which deals with various outlier rejections and processing of the data followed by DL approaches to analyze the collected contextual data in detecting sick and on heat animals, and finally, insightful information is sent to shed owner for necessary action. An experimental study conducted is helpful to make wise decisions to increase production cost-effectively. The chapter concludes with the different future aspects that may be further explored by the researchers.