**3. Methodology**

*LabVIEW - A Flexible Environment for Modeling and Daily Laboratory Use*

**theme**

Healthcare ●

Residential ●

Energy ●

*Summary of remote monitoring system using LABVIEW and interfacing hardware.*

●

**Platform for interfacing hardware**

Education ● ●

**Arduino Raspberry-Pi NI** 

● ●

Agriculture ●

Environment ● ●

● ●

**related-DAQ**

●

**PLC**

●

**Article title Application** 

Arduino and LabVIEW in educational remote monitoring applications

Remote monitoring and control of VFD fed three phase induction motor with PLC and LabVIEW software

Remote monitoring of BLDC motor using LabVIEW and

An efficient IoT based biomedical health monitoring and diagnosing system using myRIO

Development of a Medical Care Terminal for Efficient Monitoring of Bedridden

Smart multi-level tool for remote patient monitoring based on a wireless sensor

zigbee

Subjects

network and

mining

IoT application on establishing smart home

Intellisense and remote centralized security monitoring system for the ventilation system in deep

Design and Real Time Implementation of SmartWater Management using LabVIEW and IoT

An estimated method of visibility for a remote sensing system based on LabVIEW

and Arduino

Solar power remote monitoring and controlling using Arduino, LabVIEW and web browser

Remote air quality monitoring system by using MyRIO-LabVIEW

• Hardware configuration: The development the system, take into consideration the hardware that will be used, as this will impact the data flow process. Different setup configurations necessitate different initialization settings, necessitating the creation of a specific algorithm. To minimize errors, electronic components are chosen in such a way that they are configurable and easy to interface with.

●

**70**

**Table 2.**

To read, monitor, and control sensor data, LabVIEW employs a virtual instrument. MyRIO, DAQ, and NI-ELVIS are examples of known hardware interfaces. This hardware works on the same principle as the interfaces between the actual plant and the LABVIEW programming. Arduino and Raspberry-Pi are two of the most common data acquisition devices that support open-source programming by transforming functional interfaces into low-cost interface hardware. The use of LABVIEW with open-source hardware is gaining popularity due to increased practical implementation, especially in remote monitoring applications. The current study can be used as a pilot guide for developing a remote laboratory that is similar to an industrial-based temperature process. The proposed framework is intended to provide benefits in terms of practicality and cost-effectiveness. The built interface module in the proposed framework will provide access to the laboratory experimental setup, is illustrated in **Figure 4**.

Any experimental parameters or configuration input can be fed into the Arduino platform and transmitted to any user's mobile device connected to the laboratory network. The student can use this to remotely manipulate lab parameters and evaluate the outcomes without having to be physically present in the laboratory. This development's laboratory experiment involves data acquisition and PID control tuning of a modular-based LD-Didactic temperature equipment. A platform for reading and transmitting data and control parameters between the user and the remote laboratory setup is needed to design the module for this experiment (refer **Figures 5** and **6**). In addition, a user interface for displaying output that is accessible via mobile devices is required. Both temperature process modeling and PID controller tuning can be accomplished through algorithm development.

A mechanism for data collection necessitates an array sequence of data collection and transmission. When the thermocouple sensor reads the temperature of the oven, the input temperature transmits the data to the control unit of the processing computer, which is pre-installed with LABVIEW. Furthermore, prior initialization is required to establish LINX interconnectivity with a pre-programmed script of Arduino UNO using ATmega328P microcontroller operating at 16 MHz clock speed, a 32kB Flash memory, a 2kB SRAM, six analogue input, six I/O, one UARTs, one I2C, and one SPI. The gateway processes the received data and posts aggregated data with timestamp to the Blynk cloud. The temperature data are then stored in an 8-bit array and synchronized by sending it to the cloud. The current study can be used as a pilot template for establishing

*Block diagram for modular based LD didactic temperature monitoring system and control with IOT.*

**73**

*Cost-Effective Interfaces with Arduino-LabVIEW for an IOT-Based Remote Monitoring…*

a remote experiment between a temperature control plant and a mobile device to achieve remote laboratory application. The programming sequence is as follows: Step 1: Initialize pin and load ESP8266 libraries in Arduino IDE.

*Full LABVIEW's block diagram to perform interfacing with Arduino and PID control system.*

Step 3: Install NI VISA, VI Package manager

Step 6: Transfer local data to cloud.

setting and connect the board with LINX Firmware Wizard.

Step 7: Visualize measured data in Blynk application.

receive from this experiment conducted in laboratories.

Step 2: Setting up the network credentials: SSID and Passkey to establish IOT

Step 4: Establish connection between Arduino board and LABVIEW. Then search for LabVIEW Interface for Arduino -- Firmware -- LIFA\_Base. Conduct port

**4. Blynk integration of IOT module with open-source hardware**

Open-source platform for realizing the remote monitoring applications is increased nowadays. To achieve remote capabilities, there is a need to develop a low cost and user-friendly interfacing technique, which is suitable for communicating the physical experimental system and the student's mobile device in real time, realizable through IOT development. Among various options, Blynk application which is available with IOS and Android apps is capable to control the open-source hardware such as Arduino and Raspberry Pi. The interfaces in digital dashboard for IOT interfaces enable centralized data collection and analysis which is beneficial for laboratories applications. Even though there is existing IOT based data acquisition to perform remote monitoring function, however high cost of data acquisition device limits the actual implementation. Therefore, the proposed interfaces using Blynk application are the best economically available to display the temperature

Online display of data measurements is commonly dedicated for end user which accessible with phone or computer. In this case Blynk due to its simplicity of user interface programming by simply dragging-and-dropping widgets, network cloud can be configured conveniently, and access capability from both smartphone and laptop/computer. The best feature is to exploit the laboratory equipment while deploying the system away from the real experiment setup which can be monitored

Step 5: Read temperature measurement and transfer to LINX Firmware Wizard.

*DOI: http://dx.doi.org/10.5772/intechopen.97784*

communications.

**Figure 6.**

**Figure 5.** *LABVIEW's block diagram interfaces with Arduino module.*

*Cost-Effective Interfaces with Arduino-LabVIEW for an IOT-Based Remote Monitoring… DOI: http://dx.doi.org/10.5772/intechopen.97784*

#### **Figure 6.**

*LabVIEW - A Flexible Environment for Modeling and Daily Laboratory Use*

*Block diagram for modular based LD didactic temperature monitoring system and control with IOT.*

**72**

**Figure 5.**

**Figure 4.**

*LABVIEW's block diagram interfaces with Arduino module.*

*Full LABVIEW's block diagram to perform interfacing with Arduino and PID control system.*

a remote experiment between a temperature control plant and a mobile device to achieve remote laboratory application. The programming sequence is as follows:

Step 1: Initialize pin and load ESP8266 libraries in Arduino IDE.

Step 2: Setting up the network credentials: SSID and Passkey to establish IOT communications.

Step 3: Install NI VISA, VI Package manager

Step 4: Establish connection between Arduino board and LABVIEW. Then search for LabVIEW Interface for Arduino -- Firmware -- LIFA\_Base. Conduct port setting and connect the board with LINX Firmware Wizard.

Step 5: Read temperature measurement and transfer to LINX Firmware Wizard. Step 6: Transfer local data to cloud.

Step 7: Visualize measured data in Blynk application.

### **4. Blynk integration of IOT module with open-source hardware**

Open-source platform for realizing the remote monitoring applications is increased nowadays. To achieve remote capabilities, there is a need to develop a low cost and user-friendly interfacing technique, which is suitable for communicating the physical experimental system and the student's mobile device in real time, realizable through IOT development. Among various options, Blynk application which is available with IOS and Android apps is capable to control the open-source hardware such as Arduino and Raspberry Pi. The interfaces in digital dashboard for IOT interfaces enable centralized data collection and analysis which is beneficial for laboratories applications. Even though there is existing IOT based data acquisition to perform remote monitoring function, however high cost of data acquisition device limits the actual implementation. Therefore, the proposed interfaces using Blynk application are the best economically available to display the temperature receive from this experiment conducted in laboratories.

Online display of data measurements is commonly dedicated for end user which accessible with phone or computer. In this case Blynk due to its simplicity of user interface programming by simply dragging-and-dropping widgets, network cloud can be configured conveniently, and access capability from both smartphone and laptop/computer. The best feature is to exploit the laboratory equipment while deploying the system away from the real experiment setup which can be monitored


#### **Figure 7.**

*VIs for Arduino-LABVIEW serial read and write.*


#### **Figure 8.**

*VIs from the front panel of the PID control and monitoring system (1) Arduino-LABVIEW serial read and write (2) waveform chart (3) PID setting parameters.*

**75**

**Figure 9.**

*Blynk interface with widgets configured for remote monitoring.*

*Cost-Effective Interfaces with Arduino-LabVIEW for an IOT-Based Remote Monitoring…*

**5. Real time PID tuning control for LD didactic temperature plant**

In addition to the existing control engineering laboratories, integrating an industryrelevant process with a remote lab has increased the understanding of temperature process modeling and tuning scheme. Obtaining accurate temperature control is crucial when simulate the PID tuning parameters namely K (proportional gain), Ti (integral time) and Td (derivative time). **Figure 10** demonstrates the experimental setup of the temperature measurement system. The plant contains several modular types of thermocouple unit, signal conditioning unit, meter, and processing unit to preinstall with LABVIEW. Real-time tests are shown in **Figure 11**, have revealed that the acquired measurement of plant temperature with several PID setting can be observed from the

and controlled from Blynk dashboard. The developed dashboard helps to provide better monitoring system with continuous monitoring and advanced data analysis which will be conducted later. Data acquisition process using Arduino-LabVIEW and IOT system need to be programmed in Arduino Integrated Development

Environment (IDE) in terms of how to manage data sequence and arranging for data transferring process. While data retrieval from either the processing computer or plant to serve as data logging functions is controlled by Blynk, it involves the Blynk interfaces to be remotely monitored away from the experimental setup with internet connectivity. The collected data are made available to remote users in graphical form. In order to build the data acquisition system with IOT interfaces, Blynk Arduino Library is required to install for establishing the firmware in the Arduino. To start with, BLYNK application requires to be configured and registered using an email. An authentication code with the SSID and the password of the network station is created uniquely for each of developed, and thus need to write these details as part of programming code. As shown in **Figure 7**, the design created for remote monitoring application to apply in temperature experiment study contains four slider widgets to represent the variables used for tuning process and a SuperChart widget

*DOI: http://dx.doi.org/10.5772/intechopen.97784*

to display real-time graph (see **Figure 8**).

### *Cost-Effective Interfaces with Arduino-LabVIEW for an IOT-Based Remote Monitoring… DOI: http://dx.doi.org/10.5772/intechopen.97784*

and controlled from Blynk dashboard. The developed dashboard helps to provide better monitoring system with continuous monitoring and advanced data analysis which will be conducted later. Data acquisition process using Arduino-LabVIEW and IOT system need to be programmed in Arduino Integrated Development Environment (IDE) in terms of how to manage data sequence and arranging for data transferring process. While data retrieval from either the processing computer or plant to serve as data logging functions is controlled by Blynk, it involves the Blynk interfaces to be remotely monitored away from the experimental setup with internet connectivity. The collected data are made available to remote users in graphical form.

In order to build the data acquisition system with IOT interfaces, Blynk Arduino Library is required to install for establishing the firmware in the Arduino. To start with, BLYNK application requires to be configured and registered using an email. An authentication code with the SSID and the password of the network station is created uniquely for each of developed, and thus need to write these details as part of programming code. As shown in **Figure 7**, the design created for remote monitoring application to apply in temperature experiment study contains four slider widgets to represent the variables used for tuning process and a SuperChart widget to display real-time graph (see **Figure 8**).
