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We have developed an automated surveillance system based on passive infra-red sensors. Eight sensors were installed in a hospital room. A computer automatically captured data from the sensors every night from 21:00 until 06:00 the following morning. The sensors were polled twice per second and when a sensor was activated by movement, the event and time were recorded in a data file. At the end of the surveillance period the program analysed the data and generated a report showing the activities taking place in the room and their times. Four elderly patients were observed for a total of 97 nights. A total of 1637 possible sequences of movements by the patient and the hospital staff were detected. The computer was able to identify 1450 sequences (89%) correctly, in comparison with manual analysis. Only 10 movements (0.6%) were undetected by the system; all were very short sequences (five or six activations of the sensors). The system was generally capable of detecting and classifying all major movements in the room.
Banerjee et al. (Sat,) studied this question.