IoT-based monitoring platform for indoor thermal comfort data collection

• Autor(a) principal: Almeida, Ana Laura Costa
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/29446
• topic: Dataset; Thermal comfort; IoT; Device monitoring; Sensor data gathering; Alert system

Considering the noticeable climatic changes from past years, a general interest in finding solutions to reduce the environmental footprint has been growing. Among the major sources of energy consumption in domestic buildings, climate control is placed at top positions. In order to achieve a balance between the energy consumption levels and the occupants’ thermal comfort, several studies have been conducted all over the world regarding users’ behavior and their thermal comfort perception. It is within this scope that this dissertation addresses comfort monitoring. The study proposed in this project focuses on retrieving thermal comfort data based on the Portuguese families lifestyle and the Mediterranean climate. This dissertation aims to collect a good quality dataset that can be later analysed in order to extract useful information about how to develop effective solutions that are able to reduce the energy consumption levels without compromising the thermal comfort levels that householders are used to. In order to collect the dataset, certain long-term indoor measurements were collected, such as temperature, humidity and motion detection, through Zig- Bee sensors. These measurements were sent and stored in an open-source IoT platform, responsible for monitoring the data collection process and generating alerts when it detects a failure that cannot be solved without user intervention. The measurements are sent from the sensors to the IoT platform through a gateway, which acts as an intermediary for protocol translation and also implements monitoring functionalities. As a result of the study, data from 15 houses were collected during, approximately, 8 months, but the study is still running. The resulting dataset has undergone preliminary analysis, for the quality obtained and the developed data collection process point of view.