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UltraSense: A non-intrusive approach for human activity identification using heterogeneous ultrasonic sensor grid for smart home environment

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Abstract

Recognizing human activities non-intrusively has prevailed as a challenging and active area of research. In real life, it is a major requirement for human-centric applications like assisted living for elderly care, health-care and creating a smart home environment etc. Considering that people spend more than 90% (Klepeis et al. in J Exposure Sci Environ Epidemiol 11(3):231, 2001) of their time indoors, a proper indoor activity monitoring system will be helpful to monitor the abnormal behavior of the occupants. Existing approaches have implemented intrusive or invasive methods such as a camera or wearable devices. In this work, we present a non-invasive, non-intrusive sensing technique using an array of heterogeneous ultrasonic sensors for human activity monitoring. The ultrasonic sensors are placed in two separate deployments as sensor grids and in different positions of the door-frame. The proposed system senses a stream of events as the occupants perform different activities categorized as primary, postural and group activities. The primary activities considered are sitting, standing and fall. The postural activities are intermediate transitional states in the primary activities. These activities when performed in groups, are considered as a group activity. Other than activities it can identify different indoor movements, count room occupancy and identify occupants. Based on the collected data, the results show that the proposed system achieves an accuracy of more than 90% for detection of different activities and shows improvement over existing works. The final outcome of this work can be seen as developing the current prototype into smart ceiling panels that can be easily used in the indoor environment for human activity monitoring.

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Authors and Affiliations

  1. Dr B C Roy Engineering College, Durgapur, India

    Arindam Ghosh

  2. Jadavpur University, Kolkata, India

    Amartya Chakraborty

  3. Capgemini Technology Services India Ltd, Bangalore, India

    Dhruv Chakraborty

  4. National Institute of Technology, Durgapur, India

    Mousumi Saha & Sujoy Saha

Authors
  1. Arindam Ghosh
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  2. Amartya Chakraborty
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  3. Dhruv Chakraborty
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  4. Mousumi Saha
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  5. Sujoy Saha
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Correspondence to Arindam Ghosh.

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Ghosh, A., Chakraborty, A., Chakraborty, D. et al. UltraSense: A non-intrusive approach for human activity identification using heterogeneous ultrasonic sensor grid for smart home environment. J Ambient Intell Human Comput 14, 15809–15830 (2023). https://doi.org/10.1007/s12652-019-01260-y

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