Using Commonly Available IoT Devices to Support and Facilitate the Learning Process : Plenary Talk

Z. Balogh
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Abstract

Emotion recognition relies heavily on physiological reactions and facial expressions. The goal of the research is to design an Internet of Things (IoT) based sensor network that can monitor the emotional state of users. IoT is a network of physical objects, devices, machines and other objects with advanced electronics that includes software, sensors and network connectivity, which enables the collection and exchange of data. Using current technology, a set of measurement devices can be used to create a complex sensory network that is capable of acquiring physiological responses and recognizing emotions based on a user’s facial features using facial recognition software. It is also important to automate these devices and the acquisition of sensory data so that they can be easily used without the need for additional user input. The aim of the research is to describe an experiment in which physiological features are collected using inexpensive, common and noninvasive Internet of Things (IoT) devices and the sensory data is automatically sent to a server for further processing. A dataset is created from the measured values and descriptive statistics are used to understand and visualise them.
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使用常用的物联网设备来支持和促进学习过程:全体会议
情绪识别很大程度上依赖于生理反应和面部表情。该研究的目标是设计一个基于物联网(IoT)的传感器网络,可以监测用户的情绪状态。物联网是一个由物理对象、设备、机器和其他具有先进电子设备的对象组成的网络,包括软件、传感器和网络连接,从而能够收集和交换数据。利用目前的技术,一组测量设备可以用来创建一个复杂的感官网络,该网络能够获取生理反应,并使用面部识别软件根据用户的面部特征识别情绪。自动化这些设备和获取传感数据也很重要,这样它们就可以很容易地使用,而不需要额外的用户输入。这项研究的目的是描述一个实验,在这个实验中,使用廉价、常见和无创的物联网(IoT)设备收集生理特征,并将感官数据自动发送到服务器进行进一步处理。从测量值创建一个数据集,并使用描述性统计来理解和可视化它们。
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