developing a raspberry pi-based monitoring system for...

International Electronics Symposium (IES) 2014 ISBN : 978-602-0917-14-6 Politeknik Elektronika Negeri Surabaya

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Developing a Raspberry Pi-based Monitoring System for Detecting and Securing an Object

Tohari Ahmad1, Hudan Studiawan2, Tirta Taruna Ramadhan3 1,2,3Department of Informatics, Institut Teknologi Sepuluh Nopember (ITS)

Kampus ITS Surabaya [email protected]

Abstract Monitoring certain areas or territories is needed in order to maintain the security. This often requires the security officers to manually monitor them. This is, however, may not be efficient due to human limitation, such as time and coverage area factors. An electronic monitoring may be able to solve this problem. Nevertheless, the cost factor can be the a hindrance. In this paper, we propose a relatively cheap monitoring system which has capability of detecting an object (human), calculating its distance, determining its coordinate and taking its picture. These data are then sent to the user through email. This real time system has made it easier for the user to make a further decision. The experimental result shows that this proposed monitoring system works well and is appropriate to use, even though in the condition when the light is low. Keywords: monitoring system, raspberry pi, data communication,minimal system.

1. Introduction

A monitoring system has been widely implemented in the world.It is oftenly used for helping people in securing certain areas or territories. In general, a device continously takes a picture/video and sends it to other site where an officer receives and monitors it. Here, a monitoring system makes it easier for people to take a critical decision in time, according to the data he/she receives.

A monitoring system is constructed by a camera along with all related devices for tranferring the data. This can be either wireless or wired devices, depending on the nature and requirements of the system. In some cases, wired communication is implemented in order to maintain the quality of the data; and in other cases, wireless communication is more appropriate for the flexibility reason.

Despite its limitation, there some advantages of using this system. First, it can cover an area which is difficult for people to reach, for example, a small-sizeunder water area. Second, it is able to work anytime.This is different from human which is unable to work for certain times. Third, it has a capability of relatively precise in identifying an object, if it is

combined with an object recognition system. This can be developed to be a more complex system to have more capabilities.

Variousmonitoring systems have been developed, ranging from relatively expensive systems such as in [1] to those of cheapsuch as in [2][3]. Overall, many existing systemsrequire the officers to continously monitor the received data. This characteristic can be a weakness of the system which results in other disadvantages for example, wasting the energy. Moreover, some of them only provide video streaming which can be accessed through the internet without anynotification of certain events.

In this paper, we propose a system which is able to notify the user in case a suspected event occured, provide the coordinate of the event which is linked to an on-line map. In addition, this system employs infra red to detect the existance of objects.

The rest of the paper is organized as follows. Section 2 describes the literatur review. Sections 3 and 4 respectively present the design and experimental result of the proposed system. Finally, the conclusion is drawn in section 5.

2. Related Works and Devices

Embedded systems have been implemented in various fields, which are oftenly combined with raspberry [4]pi or arduino[5] as the main system. For example, automatic door bell with detection [6] and automatic railway gate controller[7]. In the field of monitoring system, [3] employs raspberry pi to manage the data which has been captured by a camera whose architecture is depicted in Fig. 1. Due to its simplicity, this system does not provide many advanced fitures.

2.1. Raspberry Pi

Raspberry pi is a single board computer whose size is much smaller than PC. It comprises four models [4]: Model A, Model B, Model B+ and Compute Module; which all use BCM2835 as the combination of GPU and CPU to be the System on Chip. In addition, the model A and model B have the same board which is similar to that of model B+ but totally different from that of the compute module.

Overall, raspberry pi present similar capability to PC; however, due to its simpler specification, it still


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has limitation. Many open source applications such as Libre Office and web browser, can be installed to it.

camera Monitor

Raspberry pi

input output

Figure 1. Architecture of Surveillance cam [3]

2.2. HC-SR501 Passive Infrared Sensor (PIR)

PIR is a sensor to detect the object movement. It is a passive sensor which means that it does not emit infrared rays, but it receives that of the external party. In more details, the sensor compares the intensity of the infrared rays from time to time. If there is an object movement, then the intensity changes. This results in detecting the object. For detecting the human body, the HC-SR501 Body Sensor Module Pyroelectric Infrared is used.

The sensor has high sensitivity which works on ultralow votage [8]. It has power consumption 65mA and is able to detect an object whose temperatur 20-27o whose range detection can up to 5-7 meters.

2.3. Raspberry Pi NoIR Camera Module

Raspberry Pi NoIR Camera Module [9] is an add-on module for use in the raspberry pi. It is appropriate to use in a condition whose light is low because of its NoIR filter. Furtermore, its size and weight are also small (20 x 25 x 9mm and 3g, respectively) which make it easy to use for mobility.

2.4. Ranging Detector Mod Distance Sensor HC-

SR04

The sensor is used for measuring the distance of the object[10]. It works by sending 40 kHz ultrasonic wave and detecting whether there is echo resulting from it. Even though its maximum distance is relatively small (5m), its accuration is quite hight (3mm) and stable. The distance itself is calculated according to the duration of the signal high level, where the distance is proportional to the duration.In addition, this sensor consists of ultrasonic transmitter, receiver and control circuit.

2.5. Raspbian OS

Raspbian is a Debian-based operating system developed for raspberry pi [11]. It has more than 35.000 packages which are ready to use and support raspberry pi. So, it does not only provide services like other operating system.

2.6. OpenCV

OpenCV [12] is a free library developed based on the BSD-license. It comprises hundreds of computer vision and API for used in the image processing to

optimalize a real time application. There are some features in OpenCV which support data processing, including: camera calibration, object detection, 3D reconstruction and interface to video processing.

Overall, these technologies have been explored in many applications, such as in [13][14] [15].

3. Designing the Monitoring System

In this research, we develop a system which is able to monitor an areas, such that, wherever an object (human) entering the coverage area, it can be detected. By using devices described in Section 2, the developed system is able to give real time data, notify the user (through email) and give the coordinate of the object which is linked to the online map.

The main devices used in this system are: PIR for detecting the object, ranging detector for determining the distance, NoIR camera for capturing the data even though in the dark, and raspberry pi for processing the data. In order to saving energy, video streaming feature is removed from the system. This is because, it is assumed that the system is implemented in the remote location where the electricity is limited. Here, we use a power bank for the experiment.

3.1. Architecture

In more details, the system can be described in Figs. 2 and 3 (in the form of flowchart). The system works as follows. a. The PIR sensor which has been integrated with

raspberry pi through socket GPIO, detects an object (human) according to the temperature of the object and the detection result by using the OpenCV library.

b. Once the PIR sensor detects an object, the camera captures a picture whose result is stored in the raspberry pi file storage. This is followed by the ranging detector to calculate the distance of the object.

c. All data obtained from PIR, camera module and ranging detector are stored in the memory of raspberry pi.

d. The data is processed and sent to the user (security officer) by email. This includes the picture, the coordinate of the location which is linked to the online map, and the distance of the object from the camera as the supporting data.

4. Implementation and Evaluation

The system is developed whose result is depicted in Fig. 4. As its purpose, the system is evaluated to detect a specific type of objects: a human. The system itself consists of: raspberry pi PIR sensor HC-SR501 ranging sensor HCSR04 camera modul raspberry pi NoIR breadboard 400 tie point


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wireless USB adapter power bank SDHC card Converter VGA to HDMI

The experimental result shows that the system works properly if the distance of the object is less than 5m. The PIR sensor itself is able to detect an object upto 7m successfully; however, the ranging sensor can only accurately calculate the object distance no more than 5m as shown in Tabel 1. It can be inferred that if the distance of the object is more than 5m, the calculated distance is invalid.

Moving objectPassive infrared

Sensor (PIR)

Camera moduleRanging Detector Mod

Distance Sensor

Raspberry piemail

Figure 2. Data flow

In any light condition, the system has been able to detect an object who captured by the sensor and send the respected data to the user through an email. The system is evaluated in various times. Those are: 10.33, 13.44 and 18.45. Examples of the detected and captured object in different light condition are shown in Figs. 5 and 6, respectively; while the coordinat of the object which can be viewed by the user in the online map is depicted in Fig. 7. In this case, we use the online Google map.

Start

PIR sensor detection

Object movement

Human

Taking a pictureCalculating the

distance

Combining distance and its coordinate

Notificaton (email)

End

Yes

Yes

No

No

Figure 3. One cycle of object capturing process

Figure 4. Hardware implementation

Table 1. The distance of the object

No Real distance (m)

Detected distance (m)

1 1 1.0564 2 2 2.1260 3 3 3.1511 4 4 4.0190 5 5 4.9920 6 6 4.9927 7 7 4.9998 8 8 4.9998


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Figure 5. An example of the captured object when the light is high

Figure 6. An example of the captured object when the light islow

Figure 7. An example of the coordinat and map of the capturedobject in the online map

5. Conclusion

Based on the experimental result, the system has been able to detect an object (human), take the picture, calculate its distance from the camera, calculate the coordinate of the object and automatically send those data to the user by using an email.

In future, this monitoring system can be enhanced by replacing the sensors to the more advanced ones, such that it is able to detect an object whose distance is more than 7 meters. Furthermore, the resolution of the captured image should also be increased to make it easier to manually recognize the object in the image. However, this can affect the file size sent to the user.

In addition, the reliability of the notification can be also be increased. For example, not only by email, but also by other means, such as SMS. The information of the object (name, registration number, etc) sent to the user may also be included. This feature, however, requires the object to be registered whose data is stored in the database. This works in certain environment, such school where the object is students.

References

[1] "FLIR Portable Thermal Handheld Surveillance Camera," Costco Wholesale, [Online]. Available: http://www.costco.com/.product.100095497.html? cm_sp=RichRelevance-_-categorypageHorizontal Top-_-CategoryTopProducts&cm_vc=category pageHorizontalTop|CategoryTopProducts. [Accessed 30 August 2014]

[2] S. Profis, "iCam is the cheap, easy way to get remote video surveillance," 9 April 2012. [Online]. Available: http://www.cnet.com/how-to/icam-is-the-cheap-easy-way-to-get-remote-


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video-surveillance/. [Accessed 30 August 2014]

[3] L. Upton, "Turn your Pi into a low-cost HD surveillance cam," Raspberry Pi Foundation, 2013. [Online]. Available: http://www.raspberrypi .org/turn-your-pi-into-a-low-cost-hd-surveillance-cam/. [Accessed 30 August 2014]

[4] "What is a Raspberry Pi?," Raspberry Pi Foundation, [Online]. Available: http://www.raspberrypi.org/. [Accessed 31 August 2014]

[5] "what is arduino?," Arduino, [Online]. Available: http://arduino.cc/. [Accessed 31 August 2014]

[6] "Automatic Door Bell With Object Detection," Electronichub, 19 May` 2013. [Online]. Available: http://www.electronicshub.org/ automatic-doorbell-with-object-detection/. [Accessed 31 August 2014]

[7] "Automatic Railway Gate Controller with High Speed Alerting System," Electronicshub, 15 May 2013. [Online]. Available: http://www.electronicshub.org/automatic-railway-gate-controller. [Accessed 31 August 2014]

[8] Adafruit, "PIR Motion sensor," Adafruit, 30 August 2014. [Online]. Available: https://learn.adafruit.com/pir-passive-infrared-proximity-motion-sensor/overview. [Accessed 31 August 2014]

[9] "Raspberry Pi "NoIR" Infrared Camera Board (5MP, 1080p, v1.3)," modmypi, [Online]. Available: https://www.modmypi.com/ raspberry-pi-noir-camera-board. [Accessed 31 August 2014]

[10] "Ultrasonic Ranging Detector Mod HC-SR04 Distance Sensor," Sainsmart, [Online]. Available: http://www.sainsmart.com/ ultrasonic-ranging-detector-mod-hc-sr04 -distance-sensor.html. [Accessed 31 August 2014]

[11] "Raspbian," Raspbian, [Online]. Available: http://raspbian.org/. [Accessed 31 August 2014]

[12] OpenCV, "Open Source Computer Vision Library," opencv dev team, 21 April 2014. [Online]. Available: http://docs.opencv.org/ modules/core/doc/intro.html. [Accessed 31 August 2014]

[13] Haro, L.F.D.; Cordoba, R.; Rojo Rivero, J.I.; Diez de la Fuente, J.; Avendano Peces, D.; Bermudo Mera, J.M., "Low-Cost Speaker and Language Recognition Systems Running on a Raspberry Pi," Latin America Transactions, IEEE (Revista IEEE America Latina) , vol.12, no.4, pp.755,763, June 2014

[14] Wibisono, W.; Arifin, D.N.; Pratomo, B.A.; Ahmad, T.; Ijtihadie, R.M., "Falls Detection and Notification System Using Tri-axial Accelerometer and

Gyroscope Sensors of a Smartphone," Technologies and Applications of Artificial Intelligence (TAAI), 2013 Conference on , vol., no., pp.382,385, 6-8 Dec. 2013

[15] Sugano, H.; Miyamoto, R., "Opencv implementation optimized for a cell broadband engine processor," Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009. DSP/SPE 2009. IEEE 13th , vol., no., pp.182,187, 4-7 Jan. 2009

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