Las condiciones de pandemia han llevado a la educación a buscar formas alternativas de llegar a los estudiantes con un proceso formativo similar a las condiciones de la presencialidad.  Existen muchas herramientas virtuales para el aprendizaje a través de aplicativos webs, pero estos medios no reemplazan la interacción con los equipos reales. Las herramientas tecnológicas deben ser exploradas a profundidad de tal forma que permitan generar una experiencia cercana con los equipos de laboratorio. Por esta razón, en este artículo se presenta una propuesta metodológica para repotenciar laboratorios disponibles en instituciones universitarias, facilitando el acceso remoto a los dispositivos. Esta metodología integra la experiencia pedagógica y tecnológica de docentes y estudiantes y es implementada en un equipo de aire acondicionado del laboratorio de fluidos del Instituto Tecnológico Metropolitano (ITM) de Medellín.

The Internet of Things (IoT) is one of the fastest-growing research areas in recent years and is strongly linked to the development of smart cities, smart homes, and factories. IoT can be defined as connecting devices, sensors, and physical objects that can collect and transmit data across a network, enabling increased automation and better decision-making. In several IoT applications, humidity and temperature are some of the most used variables for adjusting system configurations and understanding their performance because they are related to various physical processes, human comfort, manufacturing processes, and 3D printing, among other things. In addition, one of the biggest problems associated with IoT is the excessive production of data, so it is necessary to develop methodologies to optimize the process of collecting information. This work presents a new dataset comprising almost 55 million values of temperature, relative humidity, and RSSI (Received Signal Strength Indicator) collected in two indoor spaces for longer than 3915 h at 10 s intervals. For each experiment, we captured the information from 13 previously calibrated sensors suspended from the ceiling at the same height and with a known relative position. The proposed dataset aims to contribute a benchmark for evaluating indoor temperature and humidity-controlled systems. The collected data allow the validation and improvement of the acquisition process for IoT applications.