# Low-Cost IoT and LoRaWAN-Based System for Laying Hen Identification in Family Poultry Farms
## 1 Introduction
These automated systems not only improve the efficiency and productivity of egg production but also help reduce manual labor and ensure an optimal environment for the hens [17]. From a technological perspective, a comprehensive review of these advancements can be found in [18], covering applications in 26 countries worldwide. These technologies have been categorized into five main areas: individual bird perception, behavior recognition, health monitoring, environmental monitoring, and poultry farming robots. However, family poultry farms are generally not equipped with these advanced technological systems, as their implementation represents an investment that is not economically viable. The costs associated with automation are often prohibitive for these farm owners, particularly for those whose production is intended for self-consumption. Nevertheless, some initiatives have emerged to overcome these limitations, aiming to introduce cost-effective technological solutions in small-scale poultry farming. One such example is the cooperative company Voluta, which seeks to bridge the gap between rural and urban areas to combat rural depopulation, the digital divide, and the disconnect from nature. To achieve this, the company has developed a smart farming solution that integrates sensors and actuators, enabling remote chicken coop management via a Telegram group, where all members of a community can participate [19]. A similar effort is presented in [20], which developed an IoT system to automate the feeding and watering of poultry in small farms. Our study aligns with these initiatives, introducing the development of an IoT-based system integrating LPWAN networks. The proposed system is designed to be modular, low-cost, easy to maintain, and minimally invasive, making it adaptable to the specific needs of family chicken farms. The main contribution of the developed system lies in its ability to automatically detect laying hens--a functionality that, to the best of our knowledge, has not been thoroughly explored in previous research. In the field of chicken farming, selecting the most productive birds is a fundamental process, as they are directly responsible for egg production. This need becomes even more critical considering that a form of natural selection can occur within the chicken copy: laying hens tend to peck at or even eliminate weaker birds that do not produce eggs. Therefore, it is essential to systematically and continuously identify the most suitable hens for egg laying, ensuring both efficiency and animal welfare within the production system. To carry out this process, poultry farmers employ manual handling and observation techniques. These assessments focus on various physical attributes, including the size and color of the comb, the shape of the cloaca, and the bird's overall weight [21]. Another traditional method, although only feasible in small family farms, involves the use of nesting boxes with one-way doors. Once a hen enters, it cannot leave until manually released, allowing the farmer to identify it. This approach typically requires three daily visits to the chicken copy: in the morning to activate the one-way doors, at midday to identify and release the hens, and in the evening to repeat the process and deactivate the doors. Each visit may take 30 to 45 min, making the process time-consuming and physically demanding--especially in confined or poorly ventilated environments. Furthermore, data collection in such manual processes may lack consistency, as it requires meticulous discipline from the poultry farmer. The farmer must correctly identify the hen trapped in the nesting box (usually by means of prior tagging or marking), register the event (often in a physical notebook), collect the egg, and release the hen. This routine must be performed rigorously during each visit in order to ensure data reliability. Consequently, the accuracy and consistency of the records heavily depend on the farmer's availability, attention to detail, and adherence to the protocol over time.