外文文獻翻譯——基于熱釋電紅外傳感器的智能家居室內感應定位系統(tǒng)（英文）

1、S. Lee et al.: A Pyroelectric Infrared Sensor-based Indoor Location-Aware System for the Smart Home Contributed Paper Manuscript received September 1, 2006 0098 3063/06/$20.00 ©

2、 2006 IEEE 1311A Pyroelectric Infrared Sensor-based Indoor Location-Aware System for the Smart Home Suk Lee, Member, IEEE, Kyoung Nam Ha, Kyung Chang Lee, Member, IEEE Abstract — Smart home is expected to offer various

3、 intelligent services by recognizing residents along with their life style and feelings. One of the key issues for realizing the smart home is how to detect the locations of residents. Cur- rently, the research effort

4、is focused on two approaches: terminal-based and non-terminal-based methods. The terminal -based method employs a type of device that should be carried by the resident while the non-terminal-based method requires

5、 no such device. This paper presents a novel non-terminal-based approach using an array of pyroelectric infrared sensors (PIR sensors) that can detect residents. The feasibility of the system is evaluated experimental

6、ly on a test bed1 Index Terms — smart home, location-based service, pyroele- ctric infrared sensor (PIR sensor), location-recognition algorithm I. INTRODUCTION HERE is a growing interest in smart home as a way to off

7、er a convenient, comfortable, and safe residential environment [1], [2]. In general, the smart home aims to offer appropriate intelligent services to actively assist in the resident’s life such as housework, amusement

8、, rest, and sleep. Hence, in order to enhance the resident’s convenience and safety, devices such as home appliances, multimedia appl- iances, and internet appliances should be connected via a home network system, as

9、shown in Fig. 1, and they should be controlled or monitored remotely using a television (TV) or personal digital assistant (PDA) [3], [4]. Especially, attention has been focused on location-based services as a way to

10、 offer high-quality intelligent services, while considering human factors such as pattern of living, health, and feelings of a resident [5]-[7]. That is, if the smart home can recognize the resident’s pattern of livin

11、g or health, then home appliances should be able to anticipate the resident’s needs and offer appropriate intelligent service more actively. For example, in a passive service environment, the resident controls the op

12、eration of the HVAC (heating, ventilating, and air conditioning) system, while the smart home would control the temperature and humidity of a room according to the resident’s condition. Various indoor location-aware

13、systems have been devel- oped to recognize the resident’s location in the smart home or This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD) (KRF-2005-003-D00105) S. L

14、ee and K. N. Ha is with the School of Mechanical Engineering, Pusan National University, Busan 609-735, Korea (e-mail: slee@pnu.edu, 0vincent @pnu.edu). K. C. Lee is with the Department of Control and Automation Engin

15、eering, Pukyung National University, Busan 608-739, Korea (e-mail: gclee@pknu. ac.kr). smart office. In general, indoor location-aware systems have been classified into three types according to the measurement techno

16、logy: triangulation, scene analysis, and proximity methods [8]. The triangulation method uses multiple distances from multiple known points. Examples include Active Badges [9], Active Bats [10], and Easy Living [11],

17、which use infra- red sensors, ultrasonic sensors, and vision sensors, resp- ectively. The scene analysis method examines a view from a particular vantage point. Representative examples of the scene analysis method are

18、MotionStar [12], which uses a DC magnetic tracker, and RADAR [13], which uses IEEE 802.11 wireless local area network (LAN). Finally, the proximity method measures nearness to a known set of points. An example of the

19、 proximity method is Smart Floor [14], which uses pressure sensors. Alternatively, indoor location-aware systems can be classified according to the need for a terminal that should be carried by the resident. Terminal

20、-based methods, such as Active Bats, do not recognize the resident’s location directly, but perceive the location of a device carried by the resident, such as an infrared transceiver or radio frequency identi- ficatio

21、n (RFID) tag. Therefore, it is impossible to recognize the resident’s location if he or she is not carrying the device. In contrast, non-terminal methods such as Easy Living and Smart Floor can find the resident’s loc

22、ation without such devices. However, Easy Living can be regarded to invade the resident’s privacy while the Smart Floor has difficulty with extendibility and maintenance. This paper presents a non-terminal based loca

23、tion-aware system that uses an array of pyroelectric infrared (PIR) sensors [15], [16]. The PIR sensors on the ceiling detect the presence of a resident and are laid out so that detection areas of adjacent sensors ov

24、erlap. By combining the outputs of multiple PIR sensors, the system is able to locate a resident with a reasonable degree of accuracy. This system has inherent advantage of non-terminal based methods while avoiding p

25、rivacy and extendibility, maintenance issues. In order to demonstrate its efficacy, an experimental test bed has been constructed, and the proposed system has been evaluated experimentally under various experimental c

26、onditions. This paper is organized into four sections, including this introduction. Section II presents the architecture of the PIR sensor-based indoor location-aware system (PILAS), and the location-recognition algo

27、rithm. Section III describes a resident-detection method using PIR sensors, and evaluates the performance of the system under various conditions using an experimental test bed. Finally, a summary and the conclusions

28、are presented in Section IV. T S. Lee et al.: A Pyroelectric Infrared Sensor-based Indoor Location-Aware System for the Smart Home 1313music. In addition, the temperature of the shower water can be set automatically fo

29、r the resident. B. Location-recognition algorithm In order to determine the location of a resident within a room, an array of PIR sensors are used as shown in Fig. 3. In the figure, the sensing area of each PIR sensor

30、is shown as a circle, and the sensing areas of two or more sensors overlap. Consequently, when a resident enters one of the sensing areas, the system decides whether he/she belongs to any sensing area by integrating

31、the sensing information collected from all of the PIR sensors in the room. For example, when a resident enters the sensing area B, sensors a and b output ‘ON’ signals, while sensor c outputs ‘OFF’ signal. After collec

32、ting outputs, the algorithm can infer that the resident belongs to the sensing area B. According to the number of sensors and the arrangement of the sensors signaling ‘ON’, the resident’s location is deter-mined in t

33、he following manner. First, if only one sensor outputs ‘ON’ signal, the resident is regarded to be at the center of the sensing area of the corresponding sensor. If the outputs of two adjacent sensors are ‘ON’, the re

34、sident’s location is assumed to be at the point midway between the two sensors. Finally, if three or more sensors signal ‘ON’, the resident is located at the centroid of the centers of the corresponding sensors. For

35、example, it is assumed that the resident is located at point 1 in the figure when only sensor a signals ‘ON’, while the resident is located at point 2 when sensors a and b both output ‘ON’ signals. The location accur

36、acy of this system can be defined the maximum distance between the estimated points and the resident. For example, when a resident enters sensing area A, the resident is assumed to be at point 1. On the assumption tha

37、t a resident can be represented by a point and the radius of the sensing area of a PIR sensor is 1 m, we know that the location accuracy is 1 m because the maximum error occurs when the resident is on the boundary of

38、sensing area A. Alternatively, when the resident is in sensing area B, the resident is assumed to be at point 2, and the maximum location error occurs when the resident is actually at point 3. In this case, the error

39、 is 2 / 3m which is the distance between points 2 and 3. Therefore, the location accuracy of the total system shown in Fig. 3 can be regarded as 1 m, which is the maximum value of the location accuracy of each area. S

40、ince the number of sensors and the size of their sensing areas determine the location accuracy of the PILAS, it is necessary to arrange the PIR sensors properly to guarantee the specified system accuracy. b cA Bsensi

41、ng areaPIR sensor aC1 23Fig. 3. The location-recognition algorithm for PIR sensors. Cell #1Location decisionCell #2 Cell #nResident detection home networkR.T R.TSmart Home ServerVirtual map generatorGenerating a

42、virtual mapWriting the resident’s locationTracking the resident’s movementInstant ServiceMoving pattern predictorDB Pattern GeneratorExternal monitor home network Room TerminalPIR sensor1 PIR sensor2 PIR sensormHome app