Towards Ambient Affective Intelligence and Interaction in Smart Environments

该计划提出了在智能环境（例如智能家居）中研究环境情感智能和交互的新概念。该范式是情感计算和环境智能的交叉点。情感计算指的是对人类情感的建模和识别，而环境智能是一种范式，从硬件的角度关注传感器和处理器与日常设备的无缝集成，从算法和交互的角度关注以人为中心、响应性、适应性、个性化和预期。该项目的总体目标是将这两个概念结合在一起，为智能环境及其元素创造一个新的范例，使其普遍和持续地意识到用户的情感状态，并相应地做出反应/交互。为了实现这一目标，我们将利用各种可穿戴和物联网（IoT）传感和驱动系统。我们将首先使用数据融合和模式分类技术开发用于连续和实时多模态情感计算的鲁棒算法。随后，我们将开发学习、自适应和预测模型，使智能环境中的元素能够动态响应用户的情感状态。最后，我们将研究这种范式对用户的影响，并将随着时间的推移对这种人在环智能环境的性能进行建模。我们的工作将为智能算法和系统的发展做出重大贡献，如可穿戴设备、物联网设备和智能家居。此外，对用户情绪和精神状态的无所不在的分析和理解，以及开发响应性、适应性和预测性的方法来与用户交互并影响他们的情感状态，将带来更好的产品、用户体验和最终的生活质量，最终将使加拿大人受益。

This program proposes research on the novel concept of ambient affective intelligence and interaction in smart environments (e.g. smart homes). The paradigm is at the cross-section of affective computing and ambient intelligence. Affective computing refers to modeling and recognition of human emotions while ambient intelligence is a paradigm that focuses on seamless integration of sensors and processors into everyday devices from a hardware perspective, and focuses on human-centricity, responsiveness, adaptiveness, personalization, and anticipation from an algorithm and interaction perspective. The overall goal of the program is to bring these two concepts together and create a new paradigm for smart environments and their elements to be pervasively and continuously aware of affective states of users, and react/interact accordingly.In order to achieve this objective, we will utilize a variety of wearable and Internet of things (IoT) sensing and actuation systems. We will first develop robust algorithms for continuous and real-time multimodal affective computing using data fusion and pattern classification techniques. Subsequently, we will develop learning, adaptive, and predictive models that allow for elements within the smart environment to dynamically respond to the affective states of users. Finally, we will study the impact of this paradigm on users and will model the performance of this human-in-the-loop smart environment over time. Our work will significantly contribute to the development of intelligent algorithms and systems such as wearables, IoT devices, and smart homes. Additionally, ubiquitous analysis and understanding of emotions and mental states of users, and developing responsive, adaptive, and predictive methods for interacting with users and influencing their affective states, will result in better products, user experience, and eventual quality of life, which will ultimately benefit Canadians.