Da-hyeon Kim, Jun-ho Ahn, Journal of Internet Computing and Services, Vol. 22, No. 3, pp. 17-26, Jun. 2021
10.7472/jksii.2021.22.3.17, Full Text:
Keywords: Smart home. Intelligent, Abnormal detections, Sensor fusing, algorithm

Abstract

Recently, COVID-19 has spread and time to stay at home has been increasing in accordance with quarantine guidelines of the government such as recommendations to refrain from going out. As a result, the number of single-person households staying at home is also increasingsingle-person households are less likely to be notified to the outside world in times of emergency than multi-person households. This study collects various situations occurring in the home with lidar, image, and voice sensors and analyzes the data according to the sensors through their respective algorithms. Using this method, we analyzed abnormal patterns such as emergency situations and conducted research to detect abnormal signs in humans. Artificial intelligence algorithms that detect abnormalities in people by each sensor were studied and the accuracy of anomaly detection was measured according to the sensor. Furthermore, this work proposes a fusion method that complements the pros and cons between sensors by experimenting with the detectability of sensors for various situations.

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