CHAPTER2  LITERATUREREVIEW  This chapter is discussed about theinformation that can be gathered to build up this project from the journal,findings, article, and books. This chapter also give an explanation about therelated study done by other researchers. During literature review, the studieswill highlight few topics that will support and contributes the idea to makethis research reliable for those who studying in the same area. The researchthat has been done by other researchers in fall detection system using wirelesssensors.

This chapter will discuss the general information related in writingto the project title which are fall detection system, wireless sensors, microcontroller,GPS and GSM technology. Through the brief explanation in these topics, it willhelp in better understanding of this project of what this project is all about. 2.1     HumanFall Detection System Overview Falls are a common issue, but they are difficult todefine rigorously. Falls among the elderly is increasingly becoming a concern issuein developing countries.

The aftereffects of falls in elderly may lead to physical,medical, psychological, social and economic consequences adversely. Inaddition, a person who falls often lays for hours unable to move or use the alertmechanisms. Sometimes, they are seriously injured or even dead by the time theyare found (Tang, Ong & Ahmad, 2015). Thus, researchers from all around theworld has invented various methods of fall detection in order to prevent theseincidents.  Humanfall detection system is an assistive device (Igual, Medrano, & Plaza, 2013)which can detect the fall incidences and prevent the fall victims from lyingdown for hours (Igual, et al., 2013) using motion-sensors devices. In earlyyears, a human fall detection system is intended to alert when a fall eventoccurs but not to diminish the incidence of fallen (Dang,Truong & Dang, 2016).This system can alert a concerned person and can also be easily build and usefor societies.

 2.1.1  Method of Fall Detection Differenttechnologies have been studied to detect falls, which can be separated in twomain approaches which are wearable devices andcontext-aware systems.

 Incontext-aware systems, the sensors are installed in a certain area orenvironment in order to detect falls event. There are various common type ofsensors which are floor sensors, pressure sensors, infrared sensors, cameras,and microphones (Igual, et al., 2013).An ambient device method is one of the subgroup in context-aware systems wheremultiple sensors, most commonly pressure sensors are deployed in indoorenvironment to detect the presence of user and when the user falls (Gannapathy, Tuani Ibrahim, Zakaria, Othman,Latiff, 2013).

According to Delahoz and Labrador (2014),since the pressure sensors are low-cost and inconspicuous. The major benefit ofthis system is the user need not to wear any device on their body (Arote & Bhosale, 2015).Though, the major weakness of these sensors have is the low accuracy of falldetection.

 Onthe other hand, wearable devices method often rely on small electronic devices whichmust be worn by the user to be able to detect changes in acceleration, motionor impact in order to detect falls event when it occurs and to immediately sendan alert to a concerned person. The user usually wear one or more wearable devices which are usually equipped with movement sensors such as accelerometers andgyroscopes. The benefits of this method are not restricted to only a certainarea, low cost of installation and small in sizewhich will ease the user to perform his/her daily activities. Moreover,according to a study by Wang,Zhang, Bin, Lee, and Sherratt (2014), the accuracy of the system is very highwhich 97.5% is while 96.8% of sensitivity and the specificity is 98.

1%. Inaddition, the user can be almost track universally if a wireless connection areprovided in the wearable devices (Casilari,Luque, & Morón, 2015). Most of the existing human fall detection systems requirea base station.

This proposed paper will develop a human fall detection systemwhich works as a wearable device, hence entirely not relying from a basecentral. 2.2     Microcontrollers Amicrocontroller is a micro, low-cost integrated computer, used for sensinginput from the real world and controlling devices based on that input. Thecircuit contains many items that a desktop computer has such as memory andControl Processor Unit (CPU) but does not have any interface such as monitorand keyboard (Brain, n.d.).Microcontroller iseasily to communicate with desktop computers and to use simple sensors andoutput devices (Jayant,n.d.

). In addition, it is also very useful because itdoes not need the full power of a desktop computer and does need to be smalleror cheaper for designing a simple interactive device. Microcontroller has twomain types namely Arduino microcontroller and Raspberry Pi microcontroller.

 2.2.1 Arduino Microcontroller ArduinoUno as shown in Figure 2.1 is a single-board microcontroller and an open-sourceplatform based on ATmega328 (Tang, et al., 2015).Arduino has an operating voltage of 5V while the input voltage range from 6V to20V. It also has 32KB of flash memory, 2KB of SRAM, 1KB of EEPROM, 23programmable I/O channels and up to 20MHz of clock.

Arduino board has various functionalities including creatinginterface circuits to read sensors and switches, writing programs and controllights and motors with a slight effort. Moreover with using a USB cable, it canload new code onto the board without needing a separate hardware which is alsocalled programmer. Arduino can beprogrammed and controlled using Arduino Programming Language. It is also easier to learn to program itsince it uses a simplified version of C and C++ thus, do not need muchprogramming knowledge in order to do basic programming (Ramalingam, Dorairaj, & Ramamoorthy, n.d.).However, there are still downsides of Arduino compared to Raspberry Pimicrocontroller.

Firstly, it is not easy to connect to the internet. Inaddition, Arduino is not great selection in writing complex software, entiresoftware stack or protocols for projects. Moreover, Arduino is not verypowerful compared to the Raspberry Pi.  Figure2.

1 Arduino Uno Board(Source:Tang, et al., 2015) 2.2.2 RaspberryPi Microcontroller RaspberryPi is a fully functional credit card-sized computer invented in year 2012,originally designed especially for education because it is cheap andeducation-oriented computer board. The raspberry pi is low cost, powerful and itdoes not consume a lot of power (Kasundra & Shirsat, 2015).

Raspberry Pi is not only can be used as sensor node but also as a controllerwhere these can be used as processing node in WSN networks. In addition, theprocessing of data and decision making can be based on artificial intelligence (Kasundra & Shirsat, 2015).The technical specifications of Raspberry Pi 3 board will be simplified inTable 2.1. Table 2.1Raspberry Pi 3 Specifications RAM 1GB LPDDR2 (900 MHz) SOC Broadcom BCM2837 NETWORK 10/100 Ethernet, 2.

4GHz 802.11n wireless STORAGE MicroSD GPIO 40-pin header BLUETOOTH Bluetooth 4.1 Classic, Bluetooth Low Energy CPU 4xARM Cortex-A53, 1.2GHz Quad Core GPU Dual VideoCore IV OS operating system or Windows 10 IoT VIDEO OUTPUT HDMI (rev 1.

3 & 1.4), Composite RCA (PAL and NTSC) AUDIO OUTPUT Audio Output 3.5mm jack, HDMI, USB 4 x USB 2.0 Connector CAMERA 15-pin MIPI Camera Serial Interface (CSI-2) DISPLAY Display Serial Interface (DSI) 15 way flat flex cable connector with two data lanes and a clock lane PORT 4 USB Ports  ­TheGPU has been capable of access, fast 3D core. The Raspberry Pi however,does not have internal storage.

However, it can use the SD cards to replaceinternal storage thus, making the debug of the software updates or operatingsystem can be changed faster from different versions. Additionally, RaspberryPi runs entirely on open-source software and it is easy to install in mostLinux software since it runs a specially designed version of Linux OS. Theideal microcontroller for the proposed project is Raspberry Pi as shown in Figured2.2 because the price is affordable in encouraging younger people for programming,exploring, experimenting mastering, and inventing mainly for universitystudents. In addition, it was quickly adopted by inventers, makers, andelectronics enthusiasts for projects that require more than a basicmicrocontroller such as Arduino devices because of its small size andaccessible price. Furthermore, Raspberry Pi can be connected to the interneteasily.  Figure 2.

2 Raspberry Pi 3 Board (Source: Qifan, Yang, Wang & Xu,2015)2.3     MotionSensors Motionsensor defined as a device which responds or senses any parameter of physicalmotion such as distance, rate and acceleration. Motion sensors may measure the changesin pressure or magnetic field indirectly. The electronic sensor can beintegrated with or connected to other device where it measures motion whichcontains an electronic sensor to alert the user of the presence of a movingobject (“What is A Motion Sensor?”, n.

d.). These sensors includes gyroscopesensor, accelerometer sensor, magnetic (Mag) Sensor and pressure sensor.

Inthis proposed project, gyroscope sensor and accelerometer sensor will be usedand will be explained more in further details. 2.3.1 Accelerometer SensorAn accelerometer isa low-power and an electromechanicaldevice that measures the vibration, or acceleration of motion of a structure (“A beginner’sguide”, n.d.).

It is a compressed device intended to measurenon-gravitational acceleration.  The sensorwill respond to the vibrations related to movement such as from standstill toany velocity when the object is integrated (Goodrich, 2013).An accelerometer sense either static or dynamic forces ofacceleration. Static forces include gravity, while dynamic forces can includevibrations and movement (“Accelerometers Basics”, n.d.). Accelerometer sensoras shown in Figure 2.3 are important components to devices that track fitnessand other measurements in the quantified self-movement.

Accelerometersalso allow the user to understand the surroundings of an item better (Goodrich,2013).  Figure 2.3 Accelerometer Sensor(Source: https://www.parallax.com/product/28526) 2.3.2 Gyroscope Sensor Gyroscopesensor, also known as angular velocity sensor is used for sensing and measuringthe angular velocity motion and changes in orientation of an object (Trusov, 2011; “Gyro sensors – How They Work and What’s Ahead,” n.

d.).A gyroscope manipulate gravity of the Earth and uses the key principles ofangular momentum in order to determine orientation (Goodrich, 2013).The gyroscopes can measure velocityof rotational in either one, two, or three axes. 3-axis gyroscopes as shown inFigure 2.

4 consists of a wheel where a rotor is mounted onto smaller spinningaxis which placed in the center of a more stable wheel (Goodrich, 2013).There are various type of gyroscopes such as Rotary Gyroscope, VibratoryGyroscope and Optical Gyroscope.    Figure 2.4 3-axis Gyroscope Sensor(Source: https://www.parallax.com/product/27911) 2.

4     GPSModule GlobalPositioning System (GPS) is as a satellite-based navigation system which usesradio signals to determine the position precisely. It was originally formilitary purposes only, however was made available for public use eventuallyand it was developed by the US Department of Defense in 1973 but not fullyfunctional until 1994 (“How GPS Works”, 2014).In short, it is mainly a navigation system for real-time positioning and beingused all over the world to determine coordinates and to navigate in air, onland and sea accurately by GPS receiver.

The GPS receiver as shown in Figure 2.5analyzes the transmitted radio signals from the GPS satellites and measure thetime duration of the signals travelling from satellite to the receiver in orderto tracking the location of minimum of four GPS satellites and measure thedistance between each of GPS satellites and the receiver (“GPS in Schools – HowGPS Works”, 2015).  Figure 2.

5 GPS Module(Source: Borle & Kulkarni, 2016) 2.5     GSMModule Global System forMobile communication(GSM) Modem is a wirelessmodem that works with a GSM wireless network to transfer data. GSM modemrequires a SIM card from a wireless operator to enable it transfer data throughthe operators’ network. GSM modem as shown in Figure 2.

6 is controlled by a specialset of commands known as AT commands (“Introduction to AT Commands”, n.d.). SIM800GSM has 68 Surface Mount Technology (SMT) pads and provides interfaces betweenthe module and all user’s hardware. It has GPRS multi-slot class 12/class 10,One PWM, Bluetooth function, Audio channels, one SIM card interface andoperates on Quad-band 850/900/1800/1900 MHZ and transmit the SMS and Voice datawith low power consumption.  Figure 2.6 GSM Module(Source: Goel& Kumar, 2015) 2.

6     RelatedWorks The studies on human fall detection system hasboost up in recent years due to the advance of technologies in medical fieldresulting in demand of life expectancy rises. In “Fall Detection System Using Accelerometer and Gyroscope Based on Smartphone” by Rakhman, Nugroho, Widyawan, andKurnianingsih (2014) proposeda fall detection system using motion-based sensorsbased on smartphone. In the research, the proposed system used the embedded ofaccelerometer and gyroscope sensors in a smartphone with android operatingsystem to send alert which is an automatic call to family members through anapplication. However, the system not used a position determination using GPS totrack location and the project also did not implemented GSM technology in orderto send the alert. Meanwhilein “Human Fall Detection UsingThree-Axis Accelerometer and ZigBee Technology”, Aquino, Magno, and Tuason (2012) developed a human fall detection and monitoring system usingthree-axis accelerometer and ZigBee technology. The proposed system is anautomatic device monitoring system where after the fall is detected, it willtransmit data into a remote monitoring system automatically without anyintervention from the user.

Nevertheless, the system cannot locate thewhereabouts of the fall victims since this project did not implemented GPStechnology. In addition, Aquino et al. (2012) stated in the study that the developed device’s durability isdepending on the impact of falls. Onthe other hand, the paper titled “A Real-time Fall Detection System forMaintenance Activities in Indoor Environments” proposed by Triantafyllou et al.

(2016) focused on areal-time, multi-space and multi-camera fall detectionin indoor environments. The processof fall demonstrated by using Hidden Markov Models (HMM) which based on thefalling trajectory of a person, like the person’s velocity and area variance. Accordingto the experimental results, there were only two false alarms out of 5 similarfalls occurred. However, this project did not used aGPS technology to track location when fall events occurred. In addition, thisproject cannot be used in wider area range since it was only for indoorenvironment. Theproposed project by Jeon et al.

(2017) titled “Self-Powered Fall Detection System Using Pressure SensingTriboelectric Nanogenerators” is an ambient-based fall detection system using aself-powered pressure sensing triboelectric nanogenerators (TENG) array. Withoutany external power source, each of the pressure sensing TENG array cell generatedanalog signals when the two surfaces of cell are brought into contact when thencell is pressed. These analog signals can make the processor classify a fallsor not falls events and can be carried out in a computer or a smartphoneplatform.

This project also not only can distinguish between falls and dailyphysical activities but can read the output signal waveforms from differentactions. The results showed 95.75% classification of accuracy in identifyingactual falls. But, this project can only be applied in certain area, thus thisproject also did not applied GPS technology which can track the location of fallsvictims.  Meanwhile,the project proposed by Huynh, Nguyen, Tran, Nabili, and Tran(2013)titled “Fall Detection System Using Combination of Accelerometer and Gyroscope”used a wireless sensor system (WSS) based a combination of accelerometer sensorand gyroscope sensor simultaneously to identify falls from normal Activities ofDaily Living (ADLs).

This project compromised a tri-axis digital accelerometersensor, 3-axis digital gyroscope sensor, ARM microcontroller and a Wi-Fi module.This project achieved an accuracy of 99.382% to distinguish between falling andADLs. However, this project did not implemented GPS technology to trackpatient’s location and at the same time did not used GSM technology to receivealert. Table2.1 simplified the significance projects that relates with this proposed humanfall detection system project. Table 2.

2 Related Works JOURNAL DESCRIPTIONS GAPS Fall Detection System Using Accelerometer and Gyroscope Based on Smartphone (2014) Arkham Zahri Rakhmani, Lukito Edi Nugrohoi, Widyawani, Kurnianingsih The proposed system utilized a tri-axis accelerometer and gyroscope contained on the smartphones. This study uses a smartphone with android operating system. While the sensors used are accelerometer and gyroscope sensor.

Did not implement GSM for sending short messages (SMS) and did not used position determination using GPS Human Fall Detection Using Three-Axis Accelerometer and ZigBee Technology (2012)   Kimberli Anne M. Aquino, John Lester S. Magno, Gizelle Ann C. Tuason The proposed fall detection device is a threshold-based tri-axial accelerometer using MEMS accelerometer technology. This device was embedded with a ZigBee wireless transmitter to forward data to a remote system which manages the monitoring of the patient. •       Did not have GPS •       Did not have GSM •       Cannot be used in wider area A Real-time Fall Detection System for Maintenance Activities in Indoor Environments (2016)   (D. Triantafyllou, S.

Krinidis, D. Ioannidis, I.N.

Metaxa, C. Ziazios, D. Tzovaras) The paper focuses on the detection of fall incidents while it highlights the leverage that such a system can provide to the human.

•       Did not used a GPS technology to track location •       Cannot be used in wider area   Self-Powered Fall Detection System Using Pressure Sensing Triboelectric Nanogenerators. (2017)   (Seung-Bae Jeon, Young-Hoon Nho, Sang-Jae Park, Weon-Guk Kim, Il-Woong Tcho, Daewon Kim, Dong-Soo Kwon, Yang-Kyu Choi) This paper proposed an economical, ambient-based fall detection system based on a pressure sensing triboelectric nanogenerator (TENG) array. •       Did not use a portable and wearable device thus can only be used in a room •       Did not used a GPS technology to track location Fall Detection System Using Combination of Accelerometer and Gyroscope (2013)   (Quoc T. Huynh, Uyen D. Nguyen, Su V. Tran, Afshin Nabili, Binh Q. Tran) This paper studied on a wireless sensor system (WSS) based on accelerometer and gyroscope fall detection system to collect data. The collection data program is written in Matlab (Mathworks, Inc, Natick, MA).

The program receives and display real-time data from the WSS. The WSS contains a set of ADXL345 (3-axis digital accelerometer sensor), ITG3200 (3-axis digital gyroscope sensor), MCU LPC17680 (ARM 32-bit cortex M3), and Wi-Fi module RN13 •       Did not implemented GPS technology to track patient’s location   •       Did not used GSM technology to receive alert Development of Human Fall Detection System Using Raspberry Pi with GPS and GSM Technology   This paper focuses on a portable and wearable human fall detection system which is inexpensive and easier to build. Once the falls event occurred, the device will detect the falls and immediately sends an alert message along with the victim’s location in a form of coordinates and link to Google Maps Application on a smartphone. •       Uses GPS Technology   •       Uses GSM Technology   •       Can be wear anywhere and anytime     References Aquino, K. A. M., Magno, J.

L. S., & Tuason, G. A. C.(2012).

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https://doi.org/10.1109/TCE.2014.6780921https://www.parallax.com/product/27911https://www.parallax.com/product/28526  

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