[영어 리포트] (과학기술) 스마트cctv의 발전과정

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목차

1. Introduction
2. Methodology
3. Results & Findings
4. Discussion
5. Abstract
6. Reference

본문내용

Human identification and activity recognition technologies can be used for a variety of purposes, such as remotely monitoring an unhealthy senior or an intruder at home. Recently, advancement of wireless sensor has made it possible to construct an effective sensor network at a low cost, where human identification is feasible.
Lately, there have been many studies on human identification and activity recognition. For example, Hoque et al. (2015) developed an anomaly detection system which detects anomalies in daily in-home activities by utilizing the spatial and temporal data of the resident's normal behavior. Also, there was a study in which Emi & Stankovic (2015) developed an activity recognition system in multiple-resident homes using passive sensors.
I decided to make a CCTV which identifies intruder using human identification technique found in the studies. There are many home CCTVs in market place, but there is no CCTV which can distinguishes between intruder and resident. So I devised a CCTV which can determine who the intruder is and track his location by using PIR sensor(Passive InfraRed). In this study, I introduced two algorithms which can identify the intruder with reference to previous studies. Also, I verified that the algorithm of the previous study was effective while testing whether my two algorithms work well

참고 자료

Emi, I. A., & Stankovic, J. A. (2015, October). Sarrima: Smart ADL recognizer and resident identifier in multi-resident accommodations. In Proceedings of the conference on Wireless Health (p. 4). ACM.
Hoque, E., Dickerson, R. F., Preum, S. M., Hanson, M., Barth, A., & Stankovic, J. A. (2015, June). Holmes: A comprehensive anomaly detection system for daily in-home activities. In Distributed Computing in Sensor Systems (DCOSS), 2015 International Conference on (pp. 40-51). IEEE.