A Seamless Virtual Emotion System with Replaceable Detection toward Proper Emotionbased IoT Services In this paper, a seamless virtual emotion system is introduced toward appropriate emotionbased services in advanced IoTenabled smart cities. The proposed system is supported by virtual emotion barrier with replaceable detection and holefree property, which recognizes human emotion using wireless signal. Also, we formally define a problem with ILP formulation whose goal is to maximize the lowest detection accuracy with weak hole in replaceable barrier in order to construct seamless replaceable holefree virtual emotion barrier ultimately. Then, a novel scheme is proposed to solve the problem. Moreover, we perform the proposed approach through extensive simulations with various scenarios and its performance is evaluated with detailed discussion.

Toward Fear Detection using Affect Recognition Affective Internet of Things (AIoT) uses sensing technology empowered with the capability of detecting or predicting the emotional or affective state of the person. Recently, personal area networks in wearable systems have received increasing attention regarding affect recognition research. The combination of marketready technology and smart integrated sensors makes wearablebased affect recognition an essential building block. In this paper we present an ongoing PhD thesis work toward a fear detection system. A reduced set of wearableready modalities sensors are extracted, including only blood volume pulse and galvanic skin resistance, from publicly available datasets oriented to affect recognition. We evaluate the feasibility of a novel, multimodal approach to recognize the emotional quadrant, based on arousal and valence scores, in which fear and other negative emotions are embedded. The results are compared with the current state of the art and outlines are given for the next steps towards a fearspecific detection system.