design of gesture technology implementing wireless sensor...

Design of Gesture Technology Implementing Wireless Sensor Network and Short Message Service

Sudarmawan1 and Ferry Wahyu Wibowo2 Department of Informatics Engineering, STMIK AMIKOM Yogyakarta

Jl. Ring Road Utara, Condong Catur, Depok, Sleman, Yogyakarta [email protected], [email protected]

ABSTRACT Technology used to improve quality of life. It is invading every area in human lives and continuously developed in many sectors. The ability of research and development is always done by scientists and engineers. Innovation emerges methods for creating and developing activities those are done by individual or group. In this paper presents an instrumentation design of gesture technology that is using two components to transmit data to other devices, e.g. personal computer (PC) and mobile devices. The two components are wireless sensor network (WSN) and short message service (SMS) modules. These components are needed to yield a functioning portable instrumentation. The device used as data controller to the wireless sensor network and short message service modules is Raspberry Pi. Raspberry Pi is an open-source hardware platform. Implementation of kinect is used to capture human body motion, i.e. head, hands, and feet. Each part is scalable as value of capturing human body motion. Keywords : Instrumentation, Raspberry Pi, SMS, Technology, WSN. 1 INTRODUCTION Some problems in the aspect of tracking human body motion have been observed with some rules. Approaching kinematic model from depth image that uses system of natural scales until multi-sensor models has been proposed. A multiple depth camera approach (MDCA) implements many cameras to detect object image using high quality. An image depth selection from camera has a lot of information

that is produced from sensors to estimate object motion and position. Human body motion detection has a high dimension that needs sampling and particle filter. After capturing object particle, the object will be computed based-on signed distance from every node until it forms a human parameter. A frequency value to obtain accurately approaches those are resulted by the human motion detection in the real-time condition is about 15 Hz at GPGPU1. Nowadays the field of computer vision has been made easy using SimpleCV. SimpleCV is an open-source framework that is often applied for establishing computer vision application. The implementation of SimpleCV can provide a high computer vision libraries, e.g. OpenCV. In this case, the programmer may not have a basic knowledge about bit depths, file format, image storage, etc. A low-cost and portable instrumentation is needed to pressure consumption in the production scale. This paper observed to design and build the instrumentation of gesture technology that is used to detect human body motion. This instrumentation design is completed with wireless sensor network (WSN) and short message service (SMS) modules. The function of WSN is implemented to transmit data to the personal computer (PC) through X-Bee module. So, when the data captured and processed by Raspberry Pi, the information will be sent to WSN and SMS modules. The aim of designing this instrumentation is to obtaining detection of human body motion that can be functioned for healing stroke patient. So, the other family can follow the progression of

ISBN: 978-1-941968-02-4 ©2014 SDIWC 104

Proceedings of the International Conference on Electrical, Electronics, Computer Engineering and their Applications, Kuala Lumpur, Malaysia, 2014

medical treatment of the patient without coming to the clinic. 2 RELATED WORKS Instrumentation system of wireless level alarming system is a device designed to monitor object motion as real-time data using data transmitting principles through wireless and short message service (SMS). Transmitting real-time data not only transmitted via wireless and SMS, but also the data will be stored on the secured data (SD) card which is attached on the Raspberry Pi. In this paper presented Microsoft Kinect for XBOX 360 that provides depth sensor to detect human body motion and position. The usage of this interfacing has been implemented in various researches likes virtual environment controlling interface, system detection specification performance test that implements noise, accuracy, resolution, and latency of human skeleton detection2. A 2D/3D anatomy based-on algorithm is an iterative that needs initial 3D data. The initialization has a limitation on the area setting that effects on the accuracy, so it can make not efficient to be used. The limitation of interactive performance can be reduced using input simulation approaches. A different gesture signs from two hands to body are a multi-function sensor technology enhancement. Hand gesture method uses six control levels to manipulate data in 3 dimensions area that yields good detection accuracy method3. 2.1 Raspberry Pi Raspberry pi has some features for inputs and outputs playing as interfacing hardware to communicate with other devices. For interfacing with others, it can be programmed using python script. Raspberry Pi is a standard mini personal computer (PC) that has the ability to run on Linux operating system and its applications like multimedia (audio, video, picture), web browser, programming (QT, Phyton, C++), database server, etc. Data

connection of Raspberry Pi provides RJ45 socket that is connected to cloud through connection cable. The Raspberry Pi can be connected to WiFi using WiFi dongle that is compatible with it. The Raspberry Pi has specification as bellow:

- Power supply that is used to power on Raspberry Pi is about 5 Vdc and 700 mA via micro USB cable

- Microcontroller/microprocessor-based that using ARM1176JZF-S core with frequency 700 MHz

- Input/output (I/O) ports of Raspberry Pi have 8-pins GPIO

- Interfacing ports have UART TTL, SPI, I2C, USB, Composite RCA, 3.5 mm jack, 10/100 ethernet (RJ45), liquid crystal display (LCD) panels via DSI, camera serial interface (CSI), HDMI.

- Boot-loader that is used by Raspberry Pi can be implemented based-on LINUX operating system that is suitable running on Raspberry Pi

- Features of Raspberry Pi have 512 MB memory, 2 USB ports, graphics Broadcom video core IV, and SD card slot. SD Card is installed the operating system for Raspberry Pi

- Dimensions of Raspberry Pi are 85.60mm (L) x 56mm(W) x 21mm(H)

The configuration of Raspberry Pi GPIO shown on figure 1.

Figure 1. Configuration of Raspberry Pi GPIO An example of controlling Raspberry Pi GPIO using python script that is making pin 7 as input and pin 8 as output can be written as bellow.

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Import RPi.GPIO as GPIO #set mode for pin numbering GPIO.setmode(GPIO.BOARD) #set I/O GPIO.setup(7, GPIO.IN) GPIO.setup(8, GPIO.OUT) #Input for pin 7 & output for pin 8 inputval = GPIO.input(7) GPIO.output(8, GPIO.HIGH) 2.2 Kinect Sensor Kinect sensor consists of some devices, i.e. depth sensor, color camera, four arrays microphone that provides 3 dimensions body motion detection, face and sound recognition abilities. Depth sensor consists of infra-red (IR) projector that combined using IR camera made by monochrome complementary metal-oxide semiconductor (CMOS) sensor. The IR projector is an IR laser that passes through diffraction and turned into IR dot sets. The relative geometry between both IR projector and IR camera as good as IR dot patterns. This makes a suitable construction between object dot observed on image and projector pattern, so the 3 dimensions image pattern reconstruction formed by triangulation. A random relative dot pattern recognition, synchronizing between IR image and projector pattern can be done using fast and strike methods comparing narrow environment like normalization cross correlation. The figure of kinect shown on figure 2.

Figure 2. Kinect sensor used to detect object image

Principle of object mapping that has been done by kinect sensor implements infra-red image to be encoded using gray code. As dark pixel, so close camera in the area. The dark pixel

indicates that there is no value for that pixel. It will happen when the detected point is too far and the depth of image can be computed accurately. 2.3 Zig Bee Pro Module Radio frequency module of Zig Bee or it is known as Xbee Pro 2.4 GHz has provided antenna cable. This module uses Xbee protocol for data communication. The specification of Xbee Pro written as bellow4.

- Power supply using 2.7-3.6 VDC - Working frequency of 2.4 GHz - Interfacing UART serial - Data rate of 250 kbps - Modulation of DSSS - The range for indoor is about 90 meters

and outdoor is about 3.2 kms Benefit of the XBee Pro usage is ability addressing node at the network, the data will be checked the error and will transmit acknowledge signal, so the data can be transmitted or received. The XBee Pro module usually implemented as wireless sensor network (WSN)5. The XBee Pro module has many pins, but in the implementation there are 4 pins that will be used to, i.e. Vcc (pin 1), ground (pin 10), Dout (pin 2), and Din (pin 3). Other pins provided by XBee Pro module are sleep pin (sleep_RQ) for low-consumption of XBee, flow-control pin (RTS/CTS), analog-to-digital input pin (ADC), digital input output pin (DIO), etc. Interfacing pins of XBee Pro module functioned to transmit and receive wireless data between both Xbee and Raspberry Pi are Din and Dout signals. XBee module consumes electrical current is about 50 mA and the power output is about 1 mW with range upto 100 meters at the outside. XBee-Pro module will consume electrical current about 55 mA when it is in the idle state or receiving data and about 250 mA when transmitting data. The power output of XBee Pro can reach 100 mW for the range of line of sight that is about 1600 meters. The module of XBee Pro shown on figure 3.

ISBN: 978-1-941968-02-4 ©2014 SDIWC 106


Figure 3. Kinect sensor used to detect object image 2.3 SIM908 GSM Module SIM908 is used to send and receive data to/from provider through serial port. SIM908 is also triband GSM/GPRS 900/1800/1900 MHz module that has GPRS multi-slot class 10 supporting for short message service (SMS), calling, data, and fax applications. Specification of SIM908 GSM module written as bellow.

- Supply voltage range 3.4 - 4.5 V - Compliant to GSM phase 2/2+ - Class 4 (2 W @ 850/900 MHz) - Class 1 (1 W @ 1800/1900MHz) - Control via AT commands - (GSM 07.07 ,07.05 and SIMCOM

enhanced AT Commands) - SIM application toolkit - Interfacing using UART serial - Low power consumption - Normal operation temperature: -20 oC up to

+55 oC - Module (include antenna, SIM card

connector, socket) 3 RESEARCH METHODOLOGY This paper observed the data communication using Raspberry Pi input/output features to interface with other devices. The code that is used to interface and communicate between both Raspberry Pi and SIM908 shown on bellow.

import serial import timeser = serial.Serial(‘/dev/ttyUSB0’,9600,timeout=1) ser.flush() ser.write(‘ATDXXXXXXXXXX;\r’) ser.read(3) time.sleep(5) secondsser.write(‘ATH\r’) ser.close()

The definition of the code above can be explained that the baudrate used to communicate with SIM908 is 9600 bps. After initialization, the buffer needs to be flushed. Writing a command to the SIM908 uses AT command. The code of ser.read(3) means that it will read 3 bytes of data from the serial port. The code of time.sleep(5) is used to wait or make a delay for 10 seconds. The code of ser.close is used to close the serial communication. Global design of this instrumentation shown on figure 4. The core of the instrumentation implements Raspberry Pi that is connected with 3 modules that are SIM 908 module, XBee Pro module, and Kinect sensor. The device of SIM 908 module is attached to the Raspberry Pi GPIO, while XBee Pro module and Kinect sensor devices is attached to the USB ports. The XBee Pro module needs XBee PRO explorer board to be connected to the USB port. The data from XBee Pro transmitter module will be sent wirelessly to the receiver.

Figure 4. Global design of gesture technology-based instrumentation

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The Kinect sensor is used to capture image data that will be implemented as gesture detection. For the tilt of the Kinect sensor needs Kinect sensor power supply because it consumes 12 Volts to operation, while voice and camera of the Kinect sensor consume 5 Volts. The 5 Volts provided on the USB port, while 12 Volts provided from the Kinect sensor power supply. The detecting kinect sensor attached to the Raspberry Pi shown on figure 5.

Figure 5. Detecting Kinect Sensor The figure 5 shows that Raspberry Pi can detect Xbox NUI for audio, motor, and camera. 4 EXPERIMENTAL RESULT The capturing image object of human motion that is detected by Kinect sensor to determine the value of motion from its initial position done by Raspberry Pi. The configuration of this instrumentation shown on figure 6.

Figure 6. Configuration of instrumentation

The value of movement in this case, it uses 5 signs of body those are head, 2 hands and 2 feet. The table 1 shows the values of each body. Table 1. The values of each body that is detected by Kinect Sensor

No. Body Value 1. Head 1 2. Right Hand 2 3. Left Hand 3 4. Right Foot 4 5. Left Foot 5

When the head is moved then it will have value of 1, and when the right foot is moved then it will have value of 4. The value will be transmitted as data to the SIM908 and Zig Bee Pro devices. Monitoring data communication for SIM908 using AT command detected by serial communication performed by serial watcher application6. It can also be detected using other serial monitor application, e.g. terminal, hyperterminal, etc. The SIM908 module transmits its data to the cellular phone via provider. So timing between transmitting and receiving data can’t be determined by devices. Meanwhile, the data from Zig Bee Pro transmitter module is received using X-CTU application that is installed on the personal computer (PC) via Zig Bee Pro receiver. 5 CONCLUSION The transmitting data from Raspberry Pi module to the SIM908 and XBee Pro modules has been successful implemented. The data that has been transmitted through SIM908 is a short message service (SMS) and XBee Pro module is used to pass data wirelessly. The data of capturing object image done by Kinect sensor and processed by Raspberry Pi.

6 ACKNOWLEDGEMENT This work was supported by Indonesian Directorate General of Higher Education (DIKTI) grant, research contract number SP

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DIPA-023.04.2.189971/2014 date December 5th, 2013 and under division of research, development and public service of STMIK AMIKOM Yogyakarta research contract number 2013.109. 7 REFERENCES [1] L. Zhang, J. Sturm, D. Cremers, D. Lee, “Real-Time

Human Motion Tracking Using Multiple Depth Cameras,” unpublished.

[2] M.A. Livingston, J. Sebastian, Zhuming Ai, J.W. Decker, “Performance Measurements for The Microsoft Kinect Skeleton,” Virtual Reality Short Paper and Poster (VRW), 2012, pp. 119-120.

[3] R.H. Gong, Ö. Güler, Z. Yaniv, “Interactive

Initialization for 2D/3D Intra-Operative Registration Using The Microsoft Kinect,” Proceedings of SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modelling, 2013, doi:10.1117/12.2008525.

[4] S. Ferdoush, X. Li, “Wireless Sensor Network

System Design using Raspberry Pi and Arduino for Environmental Monitoring Applications,” The 9th International Conference on Future Network and Communication (FNC-2014), Procedia Computer Science 34, 2014, pp. 103-110.

[5] F.W. Wibowo, P.P. Purwacandra, “Object Tracking

Using Initial Data To Count Object Image Based-on Wireless Sensor Network,” The 2nd Telecommunication, Broadcasting, and Satellite (TelSaTech 2014), 2014. (references)

[6] J. E. Istiyanto, F. W. Wibowo, “A DC Motor Control

Based-on Cellular Phone,” Proceedings of 2nd Jogja International Physics Conference, 2007.

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design of gesture technology implementing wireless sensor...

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