Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
Browse
Search Results
- Effect of different agricultural ecosystems of the north-eastern Mexican territory on power degradation of radio frequency waves on LoRa-based communication applications(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024) Assad Santos, Alan; Camacho León, Sergio; emimmayorquin; Vidal Rosas, Alejandro; School of Engineering and Sciences; Campus Monterrey; Rodriguez Corbo, FidelThe increasing demand for crop production driven by human overpopulation, high meat and dairy consumption, and biofuel demands imposes a substantial increase in agricultural productivity by 2050. Rather than expanding agricultural land, enhancing crop yields emerges as a sustainable solution. Smart farming, an evolved form of Precision Agriculture, integrates Internet-of-Things (IoT) technologies to facilitate strategic decision-making in agriculture. This study focuses on evaluating the performance of the LilyGo LoRa T3S3 on diverse agricultural environments of the north-eastern Mexican territory, varying parameters such as distance from gateway to transmitter, transmitter height, transmitter output power, and spreading factors. Insights gained emphasize the significance of environmental considerations in communication architecture design for smart farming applications. Measurement of energy consumption across spreading factors determines optimal sensor deployment strategies, which are vital for sustainable farming practices. The coverage maps derived from experiments provide actionable guidance for sensor placement in agricultural landscapes, facilitating effective monitoring of soil properties, moisture levels, crop health, and environmental conditions. This research advances efficient and sustainable sensor deployment in smart farming, empowering farmers to optimize crop yields and foster sustainable agricultural practices for the future.
- Autonomous navigation in agriculture, a comparative study between 2D and 3D LiDAR’s in greenhouses(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-04) Ledesma Rangel, Juan Manuel; Aragón Zavala, Alejandro; dnbsrp; Gómez Espinosa, Alfonso; EIC Escuela de Ingeniería y Ciencias; Campus Monterrey; Escobedo Cabello, Jesús ArturoAutonomous navigation is no longer a car-only application. Over the past years, more and more areas have come to autonomous navigation to automate some tasks and simplify processes. Agriculture is a clear example of this with self-driving trucks that harvest or plant crops; self-driving drones to oversee big cultivation fields; and, of course, mobile robots too. Integrating Robotics with Agriculture can reduce exposure from human workers to chemicals or adverse conditions which can damage their health and reduce costs in both workforce and maintenance. This work shows a comparative study of a mobile robot that can navigate autonomously in a greenhouse using two different types of LiDARs, paving the way for future developments that use this platform as a base. Robotics Operating System (ROS) is used on a Jackal robot equipped with wheel encoders, GPS, and an IMU; the last three sensors are fused together for improved odometry. An RPLiDAR A3 from SLAMTEC is used as the 2D LiDAR, and a VLP16 from Velodyne is used as a 3D LiDAR. Both simulated and real-world tests are developed to calibrate and compare LiDARs regarding the computational load, safety, and performance to test the hypothesis that autonomous navigation in greenhouses differs between 2D and 3D LiDARs. Tests and their analysis revealed that each type of LiDAR is better at certain scenarios, accepting the initial hypothesis. Some future implementations are also outlined, intended to guide the reader into the next steps if the decision to follow this project is decided.