This document presents a non-terminal based indoor location system called PILAS that uses pyroelectric infrared (PIR) sensors. The PILAS system architecture includes PIR sensors installed in each room, room terminals, and a smart home server that generates a virtual map and provides intelligent services. The PILAS system can locate residents within a room by analyzing the output patterns of overlapping PIR sensors without requiring residents to carry any devices. An experimental test bed demonstrated that the PILAS system can accurately track a resident's movements and locate them with a maximum error of less than 30 cm.

1. A Pyroelectric Infrared Sensor-based Indoor Location-Aware System for the Smart Home 指導老師 : 張耀仁 學生 : 莊育嘉

2. Reference S Lee, KN Ha, KC Lee - Consumer Electronics, IEEE Transactions on, 2006 - ieeexplore.ieee.org

3. Outline Abstract Introduction Architecture of the PILAS ( PIR Sensor-Based Indoor Location-Aware System) Performance evaluation of the PILAS Summary and conclusions

4. Abstract Key issue of smart home how to detect the locations of resident Two approaches of research effort Terminal-based Resident must carry a type of device Non-terminal-based Resident don’t carry such device This paper use non-terminal-based approach Pyroelectric infrared sensors( PIR sensors)

5. Introduction How to enhance a resident’s convenience and safety multimedia appliance Internet appliances were connected via a home network system Controlled or monitored remotely using a TV or PDA Location-based service Can anticipate the resident Offer appropriate intelligent service

6. Introduction (continued) According to the measurement technology, indoor location-aware system have been classified into three types Triangulation Scene analysis Proximity methods

7. Triangulation This method uses multiple distances from multiple known points. Example Active Badges Use infrared sensors Active Bats Use ultrasonic sensors Easy Living Use vision sensors

8. Scene analysis The Scene analysis method examines a view from a particular vantage point. Examples MotionStar Use a DC magnetic tracker RADAR Use IEEE 802.11 local area network (LAN)

9. Proximity methods The proximity methods measures nearness to a known set of points. Example Smart Floor Uses pressure sensors

10. Introduction (continued) According to the need for terminal should be carried by the resident, indoor location-aware system have been classified into two types. Terminal-based method Non-terminal method

11. Terminal-based methods Active Bats Use RFID tag Use infrared transceiver It is impossible to recognize the resident’s location when user didn’t carry such devices.

12. Non-terminal methods This method can find resident’s location without such devices Easy Living Be regarded to invade the resident’s privacy Smart Floor This method has difficulty with extendibility and maintenance

13. Introduction (continued) This paper presents a non-terminal based location-aware system Use pyroelectric infrared (PIR) sensors Detection areas of adjacent sensors overlap Locate a resident Combining the outputs of multiple PIR sensors,

14. Architecture of the PILAS Framework of the smart home Location-recognition algorithm

15. Framework of the smart home An indoor location-aware system must satisfy the following requirements Location-aware system should be implemented relatively low cost Sensor installation must be flexible Sensors have to be robust to noise Sensors should not be affected by their surroundings It is desirable that the system’s accuracy is adjustable according to room types

16. Advantage of PIR sensors Have been used to turn on a light when it detects human movements Less expensive Robust to surroundings Infrared detect wavelength between 9.4~10.4μm In terms of temperature, humidity, electromagnetic noise Possible to control the accuracy Easily installed on the ceiling

17. Framework of the smart home( continue) Device are connected via a home network PIR sensors Room terminals Smart home server Home appliances Each room is a cell Each PIR sensor detect the resident at a constant period

18. Functions in smart home server Generating a virtual map Writing the resident’s movement Provide intelligence services Via the home network Save the current information Movement trajectory of the resident Current action of home appliance Current home environment May offer human-oriented intelligent services

19. Location-recognition algorithm In Fig. 3, Resident in 1 a output ‘ON’, b and c outputs ‘OFF’ In Fig. 3, Resident in 2 a and b output ‘ON’, c outputs ‘OFF’ If three or more sensors signal ‘ON’, the resident is located at the centroid of the centers

20. Location-recognition algorithm( continue ) The accuracy of this system is adjustable. In Figure.3, the radius of the sensing area is1m, then the maximum error is 1m. When resident is at point 2, the maximum error is √3/2 m

21. More sensing areas will increase the accuracy of the system Fig. 4. Location accuracy according to the sensor arrangement of PIR sensors. (a) 40 sensing areas. (b) 21 sensing areas. (c) 28 sensing areas with twelve sensors.

22. Sensors on the edges must to be located a little inwards Fig. 5. The effect of compensating for the center point of the outer sensors. (a) Resident’s movement. (b) Before compensating for the outer sensors. (c) After compensating for the outer sensors.

23. Performance evaluation of the PILAS Resident-detection method using PIR sensors The requirements of resident-detection method Implementation method for the resident-detection method for PIR sensors Performance evaluation using an experimental test bed

24. Resident-detection method using PIR sensors Recognize the resident’s location by combining outputs from all the sensors belonging to one cell Every sensor’s state will influence location accuracy the ‘ON’/’OF’ 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’s important to find appropriate threshold

25. Signal output of PIR sensor Resident enters a sensing area The variation in the Infrared radiation increase PIR sensor outputs an Increasing voltage

26. The requirements of resident-detection method PIR sensors must not malfunction by other disturbance It should be possible to precisely determine the point in time, include resident’s speed and height. It is necessary to know if a resident stays within the sensing area

27. The resident -detection method for PIR sensors (continue) Use Fresnel lens Allows human waveforms to pass through it while reject other waveforms To eliminate malfunctioning due to pets or temperature changes Resident has entered a sensing area Output of a PIR sensor exceeds the positive threshold voltage This state maintained for several intervals

28. The resident -detection method for PIR sensors (continue) Threshold must be sufficient for the method The method can distinguish variation between the resident’s infrared and other’s infrared The resident has left Sensor’s output falls below a negative threshold voltage The status maintained for several sampling intervals A resident stays within the sensing area Output voltage remains between two threshold voltage

29. Performance evaluation using an experimental test bed Design the system have a location accuracy of 0.5 m Room 4×4×2.5 m (width× length× height) 12 PIR sensors fixed on the ceiling The method is shown in Fig. 4(c)

30. Performance evaluation using an experimental test bed (continue) Signal processing and judging ‘ON/OFF’ Atmel AT89C51CC001 microcontroller A Nippon Ceramic RE431B PIR sensor NL-11 Fresnel lens A horn was installed on each PIR sensor to limit the sensing area to the circle with 2 m diameter

31. Performance evaluation using an experimental test bed (continue) Fig. 8 shows the experimental results with the horn In a, walk straight line In b, moves within the circle In c, moves outside the circle

32. Choose threshold To judge the signal is ’ON’ or ‘OFF’ When the threshold of the RE431B was ‘ ‘ This value based on the the respect to the internal temperature change External environmental temperature change didn’t affect its performance at detecting the resident Pets didn’t affect the performance

33. Determine the resident’s location PC-based location recognition algorithm Collected data every 10msec Use an NI 6025E data acquisition (DAQ) board In Fig. 9 It was drawn using a mouse in left window On the right is the estimated movement trajectory of resident

34. Determine the resident’s location Fig. 9, moving along a T-shaped path Trajectory made by connecting the resident’s location recognized by the PILAS Maximum location error is about 30 cm

35. Summary and conclusions The location accuracy in this paper is lower than 0.5 m It is possible to enhance the location accuracy of the system This system should be extended to deal with a room occupied by more than one resident