Exploring Spatial Patterns in Sensor Data for Humidity, Temperature, and RSSI Measurements

被引:0
|
作者
Botero-Valencia, Juan [1 ]
Martinez-Perez, Adrian [2 ]
Hernandez-Garcia, Ruber [3 ,4 ]
Castano-Londono, Luis [5 ]
机构
[1] Inst Tecnol Metropolitano ITM, Fac Engn, Grp Sistemas Control & Robot, Calle 73 76A-354, Medellin 050034, Colombia
[2] Inst Tecnol Metropolitano ITM, Fac Engn, Grp Mat Avanzados & Energia, Calle 73 76A-354, Medellin 050034, Colombia
[3] Univ Catolica Maule, Res Ctr Adv Studies Maule CIEAM, Ave San Miguel 3605, Talca 3480094, Chile
[4] Univ Catolica Maule, Lab Technol Res Pattern Recognit LITRP, Ave San Miguel 3605, Talca 3480094, Chile
[5] Univ Antioquia, Fac Engn, Calle 70 52-21, Medellin 050010, Colombia
关键词
temperature; relative humidity; RSSI; Internet of Things (IoT); indoor climate;
D O I
10.3390/data8050082
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
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页数:13
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