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Week 13 (21/10/2019 - 25/10/2019)

Task: Updating Chapter 3 at the report as chapter 2 has been completed. In Chapter 3, the components and methods will be describing in the project. This chapter covers about block diagram, flowchart of project, the software and list of components and cost estimation this project.
This chapter will detail more about each and every component’s function in this project. From the components, the explanation of coding will be explained too. This method shows on how to implement the coding with the component required to build up the project.



Block Diagram of the Project

The block diagram shows the flow of the project works, started from input, microprocessor and output. At the toggle switch, it has designed with the battery when blind persons only want the know the status of the heart rate via earphone. 
       Once the toggle switch has been turned on, Arduino Uno starts to process the information from the pulse sensor, and then with EasyMP3 Shield. EasyMP3 Shield was not an independent component so it should be stacked on the Arduino Uno. The connection of Arduino Uno and EasyMP3 Shield were the same. 
When run the Arduino Uno, EasyMP3 shield will be automatically operated too. In the Arduino coding, it has been classified with the reading of heart rate. The tracks in the EasyMP3 shield’s SD card would play according to the classification of heart rate. The respective track would be played through the earphone to deliver the heart rate status of the users.
To record and save data at Microsoft Excel, PLX-DAQ should be installed first. In Developer tab, Macro and Active X need to be enabled when operating PLX-DAQ. In this case, Arduino Uno need to be connected to the USB cable to transfer the heart rate data. Once the Arduino cable has been connected to the computer, PLX-DAQ would be activated after clicked on the application. 
Internet of Things platform is the most important thing in any project especially project designed for blind persons. ThingSpeak server has been used to show the heart rate data from the pulse sensor by using ESP8266. When the data has been exported to the IoT, doctors could monitor their heart rate from distance. 

Flowchart of the Project

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