DESIGN AND INTEGRATION OF MIDDLEWARE FOR IoT ......Here we are focused to build middleware for Solar...

DESIGN AND INTEGRATION OF MIDDLEWARE FOR IoT DEVICES

TOWARDS SOLAR PANEL MONITORING BASED ON RASPBERRY PI 1Mallegowda M, 2Dr Anithakanavalli,3Amrutha M P,

Department of computer science and Engineering College

Ramaiah Institute of Technology MSR Nagar, Bengaluru, Karnataka 560054

ABSTRACT

The use of technology has become an essential part of improving lifestyle, work

efficiency, and a catalyst for economic growth. The benefit of the Internet of Things

(IoT) and connected nodes has been on a steep incline in recent years. This work aims to

research, build, test and implement a low-cost solar energy monitoring and control

system using IoT devices. Photovoltaic energy can be controlled and monitored using IoT

technology from any place in the world. In order to accomplish this goal, a complete

front-end to back-end system that includes a smart device application (iOS platform), a

cloud-based database, an Application Programming Interface (API), and a hardware

development is proposed. A small programmable specialized computing device (e.g.,

Raspberry Pi) for preliminary testing. This smart node was chosen due to familiarity, and

its capabilities, such as general purpose pins and built-in Wi-Fi chip. The end goal is to

observe energy efficiency by monitoring and controlling photovoltaic energy units. This

research paper proposes an IOT based approach for solar power consumption and

monitoring that allow the users to monitor or control a solar plant. Majorly, solar plants

are built in the locations where people cannot reach on daily basis so this approach allows

the people to virtually control their systems from faraway places.

Key words: Internet of Things, iOS platform, Application Programming Interface,

Raspberry Pi, Solar

1. INTRODUCTION

With headway of wired and remote system advances, web associated cell phones,

for example, advanced mobile phones and tablets are currently in across the board utilize.

Journal of Seybold Report ISSN NO: 1533-9211

VOLUME 15 ISSUE 9 2020 Page: 4215

Therefore bringing about another idea, Internet of Things (IoT) [1-2], was presented and

has gotten consideration in the course of the last few a long time. When all is said in

done, IoT is really a data sharing condition where protests in consistently life are

associated to wired and remote systems. As of late, it is utilized not just for the field of

buyer gadgets and machines additionally in different fields, for example, a savvy city,

human services, keen home, savvy auto, vitality framework, and modern security. At

present, the sunlight based photovoltaic (PV) vitality is one of the urgent renewable

vitality sources. The sunlight based vitality is turning into a potential arrangement

towards practical vitality supply in future. As more Rooftop Solar Photovoltaic

frameworks are getting incorporated into the current matrix, there is a developing

requirement for checking [3] of constant era information got from sun oriented

photovoltaic plants so as to improve the general execution of the sun oriented power plant

and to keep up the matrix steadiness. As nearby observing is unrealistic for the installer in

this way checking remotely is basic for each sun oriented power plant At this juncture

harnessingthe power of IoT for monitoring solar power plants by using raspberry pi and

more advanced computational facilities is promising.

The Control era from Solar Photovoltaic plants is variable in nature because of

changes in sun powered irradiance, temperature and different elements. Along these lines

remote observing is basic. For creating remote observing framework for sun powered

photovoltaic control plant, IoT (Internet of Things) approach is taken in this work which

really imagines a not so distant future where regular articles will be furnished with

microcontrollers and handsets for computerized correspondence. The remote observing

take out the risks associated[4] with the customary wiring frameworks and make

information estimation and observing procedure considerably less demanding and

financially savvy and IoT based frameworks take a monster jump towards checking by

insightful basic leadership from web executed in the raspberry pi.

The decentralized design of the remote checking frameworks and its adaptability

of organization make it most appropriate for sun based mechanical purposes.When all is



said in done remote checking frameworks need to get, dissect, transmit, oversee and input

the remote data [5], by using the most developed science and innovation field of

correspondence innovation and other zones. It additionally combines far reaching

utilization of instrumentation, electronic innovation and PC programming. Pervasive

checking PV framework approaches show represents a few issues like low automaticity

and poor constant. These issues can be deflected with a proficient remote condition data

observing and controlling framework. This framework ought to incorporate programmed

determination systems the PV station.

Therefore in this work utilizing Python equal programming language and will be

placed on Raspberry Pi 3. To support individuals learning IoT for fundamental, we make

comfort applications to send and accepting order line information to get to S or A. This

mlw serves to decipher a line of orders used to run or access the different highlights in

the IoT section. MP / MT is used in Python towards the time-competency of program

work execution

2. PROPOSED IoT BASED SOLAR PANEL MONITORING

In this chapter discuss the complete details of the architecture and designs for

proposed solar panel monitoring system. The structure of the proposed Deployment

representation of middleware design is shown in figure 1.

Figure 1. Deployment representation of middleware.



Here we are focused to build middleware for Solar Panel monitoring module

device which is application specific middleware. The developed middleware is designed

for the Solar Panel Monitoring IoT module based on embedded systems using the

Raspberry Pi command line sent via the firebase's real-time database. The middleware is

designed using multiprocessing or multi - threading with a combination of Python

parallel programming language for executable programs to operate a sensor or actuator

that is most effective in CPU use and memory use. The developed middleware is really

an interpreter to convert command protocols which is used to monitor the actuator or to

obtain data from sensors. Furthermore, this is always anticipated that Raspberry Pi also

used modularly in case of an IoT Solar Panel Monitoring Device.

2.1 Middleware layer located in Raspberry Pi

The middleware comprises of two sections, one is sent on sensor router side and

the other conveyed on entryway side. The middleware which is between application

framework and basic sensor arrange, passage side offering types of assistance dynamic

and advancement interface for the application. Through control and booking of passage,

sensor router side actualizes the assignment reallocation to help the utilization of fine-

grained usage

Figure 2. Middleware layer located in Raspberry Pi along Raspbian OS



The figure2 shows the architecture layer of the mlw system to be designed and

built with Raspberry Pi. The architecture mainly consists of two main principles that is

the hardware and the software phase. The key blocks on the middleware of the software

system architecture consisted of blocks for data exchange, blocks for translation and data

generation as work orders and blocks for sensors and actuators accessing the system. The

hardware architecture consists of the construction of a set of sensors and actuators which

could be used flexibly. Here, the middleware component is to configure the request

feature mostly on second portion of the system driver.

Figure 3: Sensor and Actuator which can be accessed through middleware

The instruction data is deciphered into an errand or task pack by the receiver class

which would be completed by the task assignment class of the undertaking that should be

finished by the Raspberry Pi-dependent IoT portion. The mechanism is then formed as a

job or task to be completed and instructions are given to the system driver containing

sensor class and actuator class. Sensor nodes could be accessed easily by sending a

command line with certain stated requirements for commands to control the sensor or

actuator. The S&A chart that can be used for Raspberry Pi 's built-in middleware is

shown figure 3



2.2 Implementation of proposed system

The proposed system is implemented using paython programing language. The

MP / MT used in Python is necessary to make mlw with circulated process for

enormously powerful processors and to allow heterogeneity access to S or A, all the more

fundamentally interfacing equipment and to upgrade organized effort between

applications and equipment. Lastly, we evaluate MP&MT for CPU bond and memory

use.

Figure 4 Solar panel monitoring system contained IoT sections and mlw

The figure 4 shows overall implementation of our work, were in the

middleware is built for the specific application that is for solar panel monitoring using

raspberry pi and measures temperature, humidity and lux by the sensor nodes

configured in different localities.



Figure 5: First module for Raspberry including S & A

The hardware module for Raspberry Pi to scale S & A. The figure 5 shows the

initial module for the extended GPIO, sensor and L293D DC engine driver.

Figure 6: module for Raspberry including sensor actuator

The developed hardware modules for Raspberry Pi for the scaling temperature

sensor, dust sensor, servo motor. We designed the hardware module for Raspberry Pi

to connect OLED LCD and the push button. The figure 6 shows second module that

must attached to first module:

Figure 7: Overall system workflow



Here are two primary elements in the use of mlw on IoT section,For example,

look at the notification of orders sent and the management of the devices which

should be utilized. Incoming information processing, interpretation and running

functions are done in the middleware to get to the S&A as a procedure. The figure 7

shows the system overflow and how the system interacts with other modules.

2.3 RSA (Rivest-Shamir-Adleman) Algorithm

In this work, we use RSA algorithm to encrypt and decrypt data sent between the

sensor nodes and master nodes that is for solar panel monitoring. The RSA algorithm

is a public key encryption method and is known to be the most secure form of

encryption. It has the following features:

a. RSA algorithm is a common exponentiation in a finite field over integers

including prime numbers.

b. The integers used for this approach are big enough to make it impossible to

solve.

c. There are two sets of keys in this algorithm: private key and public key.

The figure8 shows the general description of RSA algorithm:

Figure 8: RSA Algorithm



2.3.1 Algorithm

The steps of RSA are as follows:

Step1: Select two large prime numbers, x and y. The prime numbers need to be large

so that they will be difficult for someone to figure out.

Step2: Calculate n = x * y.

Step3: Calculate the quotient function; ϕ(n)=(x−1)(y−1)

Step4: Select an integer e, such that e is co-prime to ϕ(n) and 1<e<ϕ(n). The pair of

numbers (n,e)(n,e) makes up the public key.

Step5: Calculate d such that e.d=1 mod \ϕ(n). The pair (n,d)(n,d) makes up the

private key.

The encryption is given by the following equation:

Given a plaintext P, represented as a number, the ciphertext C is calculated as

C=Pe mod n … (1)

The decryption is given by the following equation:

Using the private key (n,d), he plaintext can be found using:

P=Cd mod n … (2)

The first step is to refresh the Firebase real-time databases with a child order

table. Information from Firebase real-time databases is therefore processed with

boundary either capacity code which have been already resolved. The data parsing

results is redirected to the assignment management layer which must be separated

into the application driver blocks. Every data information shall be submitted in the

context of a set of function codes and specifications. Every data information contains

similar framework as the function code and requirements but the number of notes

code program may have various figures.There are two versions of the Task Allocator

on this paper, namely the sensor recipient and the actuator recipient.

The multiprocessing method or feature is a typical parallel computing concept

on an operating system where each operation is performed like a procedure.

Basically, the method (mainly a huge task) has threads to execute its small task.

Threads are often on the similar memory address table, so that the data processing



utilizes shared memory on either of the logical processors. The middleware built for

solar panel monitoring utilizes multi-processing or multi-threading, where the phase

of magnitude is split into multiple sub-processes rather than just threads. This

enables sub process work to be performed using another logical processor found in a

CPU. Raspberry Pi has four logical processors. The utilization of multiprocessing is

supposed to be enabled to automatically breakdown the work composed in the

middleware into four cores.

3. RESULTS AND DISCUSSION

In this section discuss the results and discussion of proposedDesign and

Integration of Middleware for IoT Devices towards Solar Panel Monitoring Based On

Raspberry Pi. The propose system is implemented using python programming

language. The proposed system initially recognize a few plan standards for such a

middleware. These standards rouse a bunch based lightweight mlw structure that

isolates application semantics from the fundamental equipment, working framework,

and system foundation. The genuine utilization of sensor arrange mlw exhibit that our

proposed design is exceptionally measured and effective, offers great execution in

complex application situations of Internet of Things



Figure 9: Overall setup of the proposed system

The figure 9 shows the overall setup of the proposed solar monitoring system,

which includes the connection between the raspberry pi and sensor nodes.

Figure 10: Result of monitored sensor data



The figure 10 shows the result of monitor sensor data. In this proposed system

comprise five sensor, such as temperature, humidity, water level, irradiance and light

level.

Figure 11: Main Interface of the Application

The figure 11 shows Main Interface of the Application. In this main interface

displays the sensor values of temperature, moisture and rain level



Figure 12: Collecting Data from sensor nodes

The figure 11 shows Main Interface of the Application. In this main interface

displays the sensor values of temperature, moisture and rain level. These collection

data’s are continuously monitored through IoT and automatically stored on database.

Figure 13: Current Spikes Response

The figure 13 shows Current Spikeresponse in the proposed solar panel

monitoring system for the date of 30th July, 1st august and 3rd august. In this

waveform clearly states that the current have minimum spikes.

Figure 14: Temperature Response

The figure 14 shows temperature response in the proposed solar panel

monitoring system for the date of 30th July, 1st august and 3rd august. The temperature

value of 30th July, 1st august and 3rd august are 32oC ,28oc and 26oc respectively.



Figure15: Humidity Response

The figure 15 shows humidity response in the proposed solar panel monitoring

system for the date of 30th July, 1st august and 3rd august. The humidity value of 30th

July, 1st august and 3rd august are 65h, 71h and 76h respectively.

Figure 16: Fire value response

The figure 16 shows fire value response in the proposed solar panel monitoring

system for the date of 30th July, 1st august and 3rd august. The fire value of 30th July,

1st august and 3rd august are 0.2f, 0.5f and 1f respectively.



Figure 17: Comparison of CPU using Multiprocessing and Multithreading

The figure 17 shows Comparison of CPU using Multiprocessing and

Multithreading response in the proposed solar panel monitoring system for the date of

30th July, 1st august and 3rd august. The CPU usage of 30th July, 1st august and 3rd

august are 0.6plval, 0.5plval and 0.01plval respectively.

4. CONCLUSION

The proposed middleware will ease the consolidation of software and heterogeneous

hardware with respect to WSN. The Universal Gateway (Middleware Layer) can

make communication between hardware and software layers simpler and supports

most WSN-related specifications, operating systems and protocols. This work

describes development of middleware for IoT module that is for solar panel

monitoring operating on Raspberry Pi utilizing Python parallel programming. The

designed middleware is responsible for translating received commands to reach

existing GPIOs in the IoT module. The sensors and actuators mounted to the IoT

module are ultrasonic sensors, temperature sensors, DC motors, potentiometers,

LEDs, pushbuttons, buzzers, LCDs and servo motors. The designed middleware

framework for solar panel monitoring even uses multi-processing or multi-threading,

so that commands obtained to reach the IoT module can be reacted rapidly and render

CPU usage most effective. Here the middleware layer is built for specific application



that is for solar panel monitoring. Hence to suggest that future enhancement would be

to handle multiple application simultaneously with good performance.

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DESIGN AND INTEGRATION OF MIDDLEWARE FOR IoT ......Here we are focused to build middleware for Solar...

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