Remote weight monitoring system for an intensive animal farm

Abstract

Livestock production today has to combine several requirements such as food safety, animal welfare, animal health, environment and sustainability in a wide sense. The consequence is a growing need to monitor many variables during the production process. However, the number of animals in a farm has increased so much that visual observation cannot be done continuously during 24 hours a day [1]. Livestock production today is no longer limited to obtaining economic goals. Modern Society is concerned about food safety and quality, efficient and Sustainable animal farming, healthy animals, guaranteed animal wellbeing and acceptable environmental impact of livestock production [2]. As a consequence, there is a growing need to monitor many variables during the entire production process in order to satisfy these targets. In the past, livestock management decisions have been based almost entirely on the observation, judgment and experience of the farmer [3]. The remote weight monitoring system is a digital measurement system for checking and registering the weight of the animals during their growth. The system connects directly to the measurement device and displays the result automatically. The load cell is applied as the measurement sensor. The interface allows the users to interact with the system. A software user interface along with the signal conditioning and data acquisition hardware is fabricated. The system is now a user friendly and less costly and thus there is a great potential for this system to be used on numerous farms. The system is composed of both hardware and software. The hardware part is the electronic scale designed and programmed using the Arduino technology. It measures and displays the animal weight in Arduino. The software part is an application that reads and records the measured weight. The software compiles and evaluates the data collected and shows the level of uniformity. I recommend it to be used by farmers for the proper decision management in order to increase productivity.