Modern commercial poultry farming typically occurs indoors, where partial or complete environmental control is employed to enhance production efficiency. Maintaining optimal conditions, such as temperature, relative humidity, carbon dioxide, and ammonia levels, is essential for ensuring bird comfort and maximizing productivity. Monitoring the conditions of poultry houses requires reliable and intelligent management systems. This study introduces a Wireless Monitoring and Control System developed to regulate environmental conditions within poultry facilities. The system continuously monitors key parameters via a network of distributed sensor nodes, which transmit data wirelessly to a centralized control unit using Wi-Fi. The control unit processes the incoming data, stores it in a database, and adjusts actuators accordingly to maintain ideal conditions. A web-based dashboard allows users to monitor and control the environment in real time. Field testing confirmed the system’s effectiveness in keeping conditions optimal, supporting poultry welfare and operational efficiency.

The management and maintenance of industrial equipment is indispensable in business environments, as it corresponds to a significant portion of a company's budget. Therefore, the use of a system that monitors the equipment and alerts managers when maintenance, repair and/or replacement tasks are required, lowers costs related to these tasks and the equipment involved. Based on this premise, the Smartool digital platform described in this paper was developed. It can store, process and alarm maintenance managers, considering data acquired from equipment, its monitoring points, sensors, and associated measurements. The platform is composed of two main software applications. A backend application where Condition-Based Maintenance (CBM) strategies are implemented using Machine Learning (ML) algorithms, and a frontend web application where the user can choose the strategy to be used in predicting the next maintenance of a given equipment. In terms of business logic, the platform executes these algorithms to access the condition of the equipment, its evolution, and the prediction of how it will evolve in each period, to help users decide about the ideal moment for maintenance. The developed platform was designed to be generic and scalable and can be used for any type of equipment and measurements, allowing also for easy addition of new algorithms and/or maintenance strategies. The solution developed allows the management of existing equipment in an organization, as well as checking its operating status and calculating forecasts of how it may evolve in terms of maintenance/replacement needs.