Identification of human activity considering social interactions and group dynamics non-intrusively has been one of the fundamental problems and a challenging area of research. In real life, it is required for designing human-centric applications like assisted living, health care, and creating a smart home environment. As human beings spend 90% of time indoors, such a system will be helpful to monitor the behavioral anomalies of the inhabitants. Existing approaches have used intrusive or invasive methods like camera or wearable devices. In this work, we present a device-free, non-invasive, and non-intrusive sensing framework called HumanSense using an array of heterogeneous sensor grid for human activity monitoring. The sensor grids, comprising the ultrasonic and sound sensors, have been deployed for collective sensing combining a person’s physical activity and verbal interaction information. The proposed system senses a stream of events when the occupant(s) perform different physical activities categorized as atomic and group activities like sitting, standing, and walking. Simultaneously, it also tracks person-person verbal interactions such as monologue and discussion. Both information are then integrated into a single framework to understand the overall behavioral scenario of the indoor environment. The experimental results have shown that HumanSense can detect different activities with accuracy more than 90% and also improves overall identification accuracy compared to existing works. Our developed system can be further evolved into ready-to-deploy smart sensing panels which can be effective for human activity monitoring in an indoor environment.

非侵入性地考虑社会互动和群体动力学来识别人类活动一直是基本问题之一，也是研究的一个挑战领域。在现实生活中，需要设计以人为中心的应用程序，例如辅助生活，医疗保健以及创建智能家居环境。随着人类在室内度过90％的时间，这种系统将有助于监控居民的行为异常。现有方法已使用侵入性或侵入性方法，例如照相机或可穿戴设备。在这项工作中，我们提出了一种称为HumanSense的无设备，非侵入性和非侵入式传感框架使用一系列异类传感器网格进行人类活动监控。包括超声和声音传感器在内的传感器网格已经被部署用于结合人的身体活动和言语交互信息的集体感知。当乘员执行分类为原子活动和小组活动（例如坐着，站着和步行）的不同体育活动时，提出的系统可感知事件流。同时，它还跟踪人与人之间的口头互动，例如独白和讨论。然后将这两种信息集成到单个框架中，以了解室内环境的整体行为情况。实验结果表明，HumanSense可以检测不同活动的准确性超过90％，并且与现有作品相比，可以提高总体识别准确性。我们开发的系统可以进一步发展为可立即部署的智能传感面板，可有效监控室内环境中的人类活动。