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A Pyroelectric Infrared Sensor-based Indoor Location-Aware System for the Smart Home 指指指指 : 指指指 指指 : 指指指

A Pyroelectric Infrared Sensor

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Page 1: A Pyroelectric Infrared Sensor

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

Page 2: A Pyroelectric Infrared Sensor

Reference

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

Page 3: A Pyroelectric Infrared Sensor

Outline

Abstract Introduction Architecture of the PILAS ( PIR Sensor-

Based Indoor Location-Aware System) Performance evaluation of the PILAS Summary and conclusions

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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)

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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

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Introduction (continued)

According to the measurement technology, indoor location-aware system have been classified into three types Triangulation Scene analysis Proximity methods

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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

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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)

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Proximity methods

The proximity methods measures nearness to a known set of points.

Example Smart Floor

Uses pressure sensors

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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

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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.

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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

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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,

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Architecture of the PILAS

Framework of the smart home Location-recognition algorithm

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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

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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

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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

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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

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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

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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

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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.

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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.

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Performance evaluation of the PILAS

Resident-detection method using PIR sensors The requirements of resident-detection method Implementation method for the resident-detection met

hod for PIR sensors Performance evaluation using an experimental te

st bed

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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

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Signal output of PIR sensor

Resident enters a sensing area

The variation in the

Infrared radiation increase

PIR sensor outputs an Increasing voltage

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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

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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

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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

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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)

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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 sen

sing area to the circle with 2 m diameter

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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

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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

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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

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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

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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