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肆肀蒂羆羂聿薄螈袈肈蚇薁膆膇莆螇肂膇葿薀羈膆薁螅袄膅莁薈袀膄蒃袃腿膃薅蚆肅膂蚈袂羁膁莇蚄袇芁葿袀螃芀薂蚃肁艿芁袈羇芈蒄蚁羃芇薆羆衿芆蚈蝿膈芅莈薂肄芅蒀螈羀莄薃薀袆莃节螆螂莂莅蕿膀莁薇螄肆莀虿蚇羂荿荿袂袈荿蒁蚅膇莈薃袁肃蒇蚆蚄罿蒆莅衿袅肂蒈蚂螁肂蚀袇膀肁莀螀肆肀蒂羆羂聿薄螈袈肈蚇薁膆膇莆螇肂膇葿薀羈膆薁螅袄膅莁薈袀膄蒃袃腿膃薅蚆肅膂蚈袂羁膁莇蚄袇芁葿袀螃芀薂蚃肁艿芁袈羇芈蒄蚁羃芇薆羆衿芆蚈蝿膈芅莈薂肄芅蒀螈羀莄薃薀袆莃节螆螂莂莅蕿膀莁薇螄肆莀虿蚇羂荿荿袂袈荿蒁蚅膇莈薃袁肃蒇蚆蚄罿蒆莅衿袅肂蒈蚂螁肂蚀袇膀肁莀螀肆肀蒂羆羂聿薄螈袈肈蚇薁膆膇莆螇肂膇葿薀羈膆薁螅袄膅莁薈袀膄蒃袃腿膃薅蚆肅膂蚈袂羁膁莇蚄袇芁葿袀螃芀薂蚃肁艿芁袈羇芈蒄蚁羃芇薆羆衿芆蚈蝿膈芅莈薂肄芅蒀螈羀莄薃薀袆莃节螆螂莂莅蕿膀莁薇螄肆莀虿蚇羂荿荿袂袈荿蒁蚅膇莈薃袁肃蒇蚆蚄罿蒆莅衿袅肂蒈蚂螁肂蚀袇膀肁莀螀肆肀蒂羆羂聿薄螈袈肈蚇薁膆膇莆螇肂膇葿薀羈膆薁螅袄膅莁薈袀膄蒃袃腿膃薅蚆肅膂蚈袂羁膁莇蚄袇芁葿袀螃芀薂蚃肁艿芁袈羇芈蒄蚁羃芇薆羆衿 S. Lee et al.: A Pyroelectric Infrared Sensor-based Indoor Location-Aware System for the Smart HomeA Pyroelectric Infrared Sensor-based Indoor Location-Aware System for the Smart HomeSuk Lee, Member, IEEE, Kyoung Nam Ha, Kyung Chang Lee, Member, IEEEAbstract Smart home is expected to offer various 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. Currently, the research effort 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 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 experimentally on a test bed.Index Terms smart home, location-based service, pyroelectric infrared sensor (PIR sensor), location-recognition algorithmI. INTRODUCTIONThere is a growing interest in smart home as a way to offer 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 residents life such as housework, amusement, rest, and sleep. Hence, in order to enhance the residents convenience and safety, devices such as home appliances, multimedia appliances, and internet appliances should be connected via ahome network system, as shown in Fig. 1, and they should be controlled or monitored remotely using a television (TV) or personal digital assistant (PDA) 3, 4. Fig. 1. Architecture of the home network system for smart homeEspecially, attention has been focused on location-based services as a way to 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 residents pattern of living or health, then home appliances should be able to anticipate the residents needs and offer appropriate intelligent service more actively. For example, in a passive service environment, the resident controls the operation 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 residents condition. Various indoor location-aware systems have been developed to recognize the residents location in the smart home or smart office. In general, indoor location-aware systems have been classified into three types according to the measurement technology: 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, which use infrared sensors, ultrasonic sensors, and vision sensors, respectively. The scene analysis method examines a view from a particular vantage point. Representative examples of the scene analysis method are 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 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-based methods, such as Active Bats, do not recognize the residents location directly, but perceive the location of a device carried by the resident, such as an infrared transceiver or radio frequency identification (RFID) tag. Therefore, it is impossible to recognize the residents 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 residents location without such devices. However, Easy Living can be regarded to invade the residents privacy while the Smart Floor has difficulty with extendibility and maintenance.This paper presents a non-terminal based location-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 overlap. 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 whileavoiding privacy 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 conditions. 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 algorithm. 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 theconclusions are presented in Section IV.II. ARCHITECTURE OF THE PIR SENSOR-BASED INDOORLOCATION-AWARE SYSTEMA. Framework of the smart homeGiven the indoor environment of the smart home, an indoor location-aware system must satisfy the following requirements. First, the location-aware system should be implemented at arelatively low cost because many sensors have to be installed in rooms of different sizes to detect the resident in the smart home. Second, sensor installation must be flexible because the shape of each room is different and there are obstacles such as home appliances and furniture, which prevent the normal operation of sensors. The third requirement is that the sensors for the location-aware system have to be robust to noise, and should not be affected by their surroundings. This is because the smart home can make use of various wireless communication methods such as wireless LAN or radio-frequency (RF) systems, which produce electromagnetic noise, or there may be significant changes in light or temperature that can affect sensor performance. Finally, it is desirable that the systems accuracy is adjustable according to room types.Among many systems that satisfy the requirement, the PIR sensor-based system has not attracted much attention even though the system has several advantages. The PIR sensors,which have been used to turn on a light when it detects human movement, are less expensive than many other sensors. In addition, because PIR sensors detect the infrared wavelengthemitted from humans between 9.410.4 m, they are reasonably robust to their surroundings, in terms of temperature, humidity, and electromagnetic noise. Moreover, it ispossible to control the location accuracy of the system by adjusting the sensing radius of a PIR sensor, and PIR sensors are easily installed on the ceiling, where they are not affected by the structure of a room or any obstacles. Figure 2 shows the framework for the PILAS in a smart home that offers location-based intelligent services to a resident. Within this framework, various devices are connected via a home network system, including PIR sensors, room terminals, a smart home server, and home appliances. Here, each room is regarded as a cell, and the appropriate number of PIR sensors is installed on the ceiling of each cell to provide sufficient location accuracy for the location-based services. Each PIR sensor attempts to detect the resident at a constant period, and transmits its sensing information to a room terminal via the home network system. Fig. 2. Framework of smart home for the PILAS.Consequently, the room terminal recognizes the residents location by integrating the sensor information received from all of the sensors belonging to one cell, and transmits the residents location to the smart home server that controls the home appliances to offer location-based intelligent services to the resident.Within this framework, the smart home server has the following functions. 1) The virtual map generator makes a virtual map of the smart home (generating a virtual map), and writes the location information of the resident, which is received from a room terminal, on the virtual map (writing the residents location). Then, it makes a moving trajectory of the resident by connecting the successive locations of the resident (tracking the residents movement). 2) The home appliance controller transmits control commands to home appliances via the home network system to provide intelligent services to the resident. 3) The moving pattern predictor saves the current movement trajectory of the resident, the current action of home appliances, and parameters reflecting the current home environment such as the time, temperature, humidity, and illumination. After storing sufficient information, it may be possible to offer human-oriented intelligent services in which the home appliances spontaneously provide services to satisfy human needs. For example, if the smart home server “knows” that the resident normally wakes up at 7:00 A.M. and takes a shower, it may be possible to turn on the lamps and some music. In addition, the temperature of the shower water can be set automatically for the resident.B. Location-recognition algorithmIn 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 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 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 collecting 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 residents location is deter-mined in the 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 residents 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 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 accuracy 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 that 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 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 is 3 / 2 m 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. Since 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.Fig. 3. The location-recognition algorithm for PIR sensors.In order to determine the residents location precisely and increase the accuracy of the system, it is desirable to have more sensing areas with given number of sensors and to have sensing areas of similar size. Fig. 4 shows some examples of sensor arrangements and sensing areas. Fig. 4(a) and 4(b) show the arrangements with nine sensors that produce 40 and 21 sensing areas, respectively. The arrangement in Fig. 4(a) is better than Fig. 4(b) in terms if the number of sensing areas. However, the arrangement in Fig. 4(a) has some areas where a resident can not be detected and lower location accuracy than that in Fig. 4(b). Fig. 4(c) shows an arrangement with twelve sensors that five 28 sensing areas without any blind spots.Fig. 4. Location accuracy according to the sensor arrangement of PIRsensors. (a) 40 sensing areas. (b) 21 sensing areas. (c) 28 sensing areaswith twelve sensors.When PIR sensors are installed around the edge of a room, as shown in Fig. 4(c), it sometimes may give awkward results. One example is shown in Fig. 5. Fig. 5(a) shows the path of a resident. If we mark the estimated points by using the sensor location or the midpoint of adjacent sensors, it will be a zigzagging patterns as shown in Fig. 5(b). In order to alleviate this, we may regard the sensors on the edges to be located a little inwards, which give the result shown in Fig. 5(c).Fig. 5. The effect of compensating for the center point of the outer sensors.(a) Residents movement. (b) Before compensating for the outer sensors. (c)After compensating for the outer sensors.III. PERFORMANCE EVALUATION OF THE PILASA. Resident-detection method using PIR sensorsSince the PILAS recognizes the residents location by combining outputs from all the sensors belonging to one cell, determining whether a single sensor is ON or OFF directly influences location accuracy. In general, because the ON/OFF values can be determined by comparing a predefined threshold and the digitized sensor output acquired by sampling the analog signal from a PIR sensor, it is necessary to choose an appropriate signal level for the threshold. For example, Smart Floor, which is another non-terminal method, can recognize a residents location exactly by comparing the appropriate threshold and a sensor value, because a pressure sensor outputs a constant voltage based on the residents weight when he remains at a specific point. However, because a PIR sensor measures the variation in the infrared signal produced by a moving human body, its output is in analog form, as shown in Fig. 6. That is, as the variation in the infrared radiation from a resident increases when a resident enters a sensing area, the PIR sensor outputs an increasing voltage. Conversely, the voltage decreases as the resident leave the sensing area. If the resident does not move within the sensing area, the variation in the infrared radiation does not exist and the PIR sensor outputs zero voltage. Therefore, it is very difficult to deter-mine when a resident is staying resident within a specific sensing area using only the voltage or current threshold of a PIR sensor.Fig. 6. Signal output of PIR sensor.In order to guarantee the location accuracy of the system, the resident-detection method must meet several requirements. First, if no resident is present within a sensing area, the PIR sensor should not output ON signal. That is, the PIR sensor must not malfunction by other disturbances such as a moving pet, temperature change and sunlight. Second, it should be possible to precisely determine the point in time when a resident enters and leaves a sensing area. That is, in spite of variations in sensor characteristics, residents speed and height, it should be possible to determine the time point exactly. Finally, because the output voltage of a PIR sensor does not exceed the threshold voltage when the resident does not move within a sensing area, it is necessary to know if a resident stays within the sensing area. In order to satisfy these requirements, this paper introduces the following implementation method for the resident detection method for PIR sensors. First, in order to eliminate PIR sensor malfunctioning due to pets or temperature changes, a Fresnel lens, which allows human infrared waveforms to pass through it while rejecting other waveforms, is installed in front of the PIR sensors. Second, when the output of a PIR sensor exceeds the positive threshold voltage, and this state is maintained for several predefined sampling intervals, that the resident has entered a sensing area. Here, the threshold must be sufficient for the method to distinguish variation in the residents infrared from an environmental infrared signal caused by pets or temperature change. Moreover, when the sensors output falls below a negative threshold voltage and this status is maintained for several sampling intervals, it is assumed that the resident has left the sensing area. Finally, when the output voltage remains between the two threshold voltages, for example when the resident is not moving inside the sensing area, the output of the corresponding PIR sensor is changed from ON to OFF. At this time, if other sensors installed near this sensor do not output ON signal, the method regards the resident as remaining within the corresponding sensing area.B. Performance evaluation using an experimental test bedIn order to verify the feasibility of the PILAS, an experimental test bed was implemented. Since the intelligent location-based service in the smart home does not require very high location accuracy, we designed the system to have a location accuracy of 0.5 m. Figure 7 shows the experimental test bed in a room measuring 4 × 4 × 2.5 m (width × length × height). In the experiment, twelve PIR sensors were fixed on the ceiling, using the arrangement shown in Fig. 4(c). An Atmel AT89C51CC001 microcontroller 17 was used for signal processing and judging ON/OFF, and a Nippon Ceramic RE431B PIR sensor 18 and NL-11 Fresnel lens were used. Especially, a horn was installed on each PIR sensor to limit the sensing area to the circle with 2 m diameter. Fig. 8 shows the experimental results with the horn. In the figure, the RE431B sensor outputs the signal shown in (a) when a resident passes through the sensing circle, while it outputs the irregular signal shown in (b) when the resident moves within the circle. Finally, no signal is detected when the resident moves outside the circle, as shown in (c). From these experimental results, we verified that the PIR sensor detects residents within the sensing area only. In addition, in order to judge whether the signal is ON or OFF, it is necessary to choose a threshold for the RE431B sensor that considers external environmental disturbance. Initially, several experiments were performed to determine the threshold with respect to the internal temperature change caused by a air conditioner or heater and other disturbances, such as wind or sunshine. Based on these experimental results, when the threshold of the RE431B sensor was ±0.4 V, external environmental temperature change did not affect its performance at detecting the resident. In addition, we verified that pets did not affect the sensing performance with the sam
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