The use of essential oils as raw material in formulation of by-products allows the revitalization of industries and regional economic growth. This is the reason why in this work it is described the process to design an extraction system of essential oil from subtle lemon. Main parameters required for the extraction have been considered as well as, the calculation of the obtained yield. Within the system design, distillation tank measurements, condenser, essential oils separator, mechanical part of the equipment, boiler selection and the distribution of the plant are dimensioned. The procedure manuals and equipment operating manuals were prepared for each step of the process of using this oil.

In the field of artificial intelligence, control systems for mobile robots have undergone significant advancements, particularly within the realm of autonomous learning. However, previous studies have primarily focused on predefined paths, neglecting real-time obstacle avoidance and trajectory reconfiguration. This research introduces a novel algorithm that integrates reinforcement learning with the Deep Q-Network (DQN) to empower an agent with the ability to execute actions, gather information from a simulated environment in Gazebo, and maximize rewards. Through a series of carefully designed experiments, the algorithm’s parameters were meticulously configured, and its performance was rigorously validated. Unlike conventional navigation systems, our approach embraces the exploration of the environment, facilitating effective trajectory planning based on acquired knowledge. By leveraging randomized training conditions within a simulated environment, the DQN network exhibits superior capabilities in computing complex functions compared to traditional methods. This breakthrough underscores the potential of our algorithm to significantly enhance the autonomous learning capacities of mobile robots.

Unmanned aerial vehicles (UAVs) are multidisciplinary technological tools, which are used in the military area for surveillance, reconnaissance and intelligence tasks in conflict zones. Due to its versatility and performance, this manuscript describes the implementation of a telemetry and video surveillance system to develop long-range missions in a UAV prototype. Communications subsystems and a ground station are integrated, with which an unmanned aerial system (UAS) is formed, carrying out the necessary calibrations and configurations. After a set of tests and the necessary adjustments, a long-distance mission is carried out and its energy consumption, height reached and trajectory tracking are analyzed. In addition, the video signal level obtained and the percentage of telemetry signal in each of the tests are established, which managed to be 90% with a distance greater than 4 km. They have good benefits, with a low economic investment, representing an interesting proposal for developing countries with a limited budget for their improvement.

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