Volume-11 Issue-8, July 2022 – International Journal of Innovative Technology and Exploring Engineering (IJITEE)

H91760711822

IJITEE Journal — Sat, 30 Jul 2022 11:51:54 +0000

The International Journal of Innovative Technology and Exploring Engineering (IJITEE) has ISSN: 2278-3075 (online), an open-access, peer-reviewed, periodical monthly international journal. This journal is published by Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) in January, February, March, April, May, June, July, August, September, October, November and December.The journal aims to publish high–quality peer–reviewed original articles in the area of Engineering and Technology that covers Computer Science and Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering and all interdisciplinary streams of Engineering and Technology. #Smart Computing and Information Processing #Signal and Speech Processing #Image Processing and Pattern Recognition #WSN#Artificial Intelligence and machine learning #Data mining and warehousing #Data Analytics #Deep learning #Bioinformatics #High Performance computing #Advanced Computer Networking #Cloud Computing #IoT #Parallel Computing on GPU #Human Computer Interactions #Recent Trends in Microelectronics and VLSI Design #Process & Device Technologies #Low-Power Design #Nanometer-Scale Integrated Circuits #Application specific ICs (ASICs) #FPGAs #Nanotechnology #Nano Electronics and Quantum Computing #3. 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Integration Tool using Internet of Things in Smart Architecture of Passenger Processing at Airport Terminal
Rupali Dahake¹, Pallavi Mirajkar²
¹Dr. Rupali Dahake, Assistant Professor, Department of MCA, Suryadatta Group of Institutes, Pune (Maharashtra), India.
²Dr. Pallavi Mirajkar, Assistant Professor, Department of Computer Science, M. D. College, Parel Mumbai, (Maharashtra), India.
Manuscript received on 30 June 2022 | Revised Manuscript received on 30 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 93-97 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91760711822 | DOI: 10.35940/ijitee.H9176.0711822
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Digital technology and Internet of things is acting as turning force on aviation industry. It is also noted that airport IoT solutions are leading in efficient airport operations and smooth passenger flow. The proposed architecture is to gear smart passenger processing through sensor, connected devices, artificial intelligence and analytical decision making. It also focuses on great potential of IoT integration in end to end passenger processing at airport terminal. This proposition helps in ‘always stays a connected passenger ‘concept. The proposed concept gives new dimension to check-in to boarding in smart way. The use of IoT will help to enhance security efficiency, shorter and better traveller experience with selecting capabilities in IoT. The Internet of Things (IoT), a network of connected smart devices through sensors which are used to communicate and collect the smart data which are analysed with augmented intelligence, such analysed data used to perform act across the applied area.
Keywords: Internet of Things (IoT), Passenger Processing, Integrated Architecture, Smart airport.
Scope of the Article: IoT

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J98820881019

IJITEE Journal — Thu, 28 Jul 2022 12:05:37 +0000

Application of Reverse Vertex Magic Labeling of a Graph
Masthan Raju. U¹, Sharief Basha.S²,
¹Sharief Basha.S, Department of Mathematics, School of Advanced Sciences,Vellore Institute of Technology, Vellore , Tamilnadu, India.
²Masthan Raju. U, Department of Mathematics, School of Advanced Sciences,Vellore Institute of Technology, Vellore , Tamilnadu, India.
Manuscript received on 29 August 2019. | Revised Manuscript received on 22 September 2019. | Manuscript published on 30 September 2019. | PP: 12-14 | Volume-8 Issue-11, September 2019. | Retrieval Number: J98820881019/2019©BEIESP | DOI: 10.35940/ijitee.J9882.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Graph labeling is a currently emerging area in the research of graph theory. A graph labeling is an assignment of integers to the vertices or edges or both subject to certain conditions. If the labels of edges are distinct positive integers and for each vertex the sum of the labels of all edges incident with is the same for every vertex in the given graph, then the labeling of the graph is called magic labeling. There are several types of magic labeling defined on graphs. In this paper we consider vertex magic labeling and group magic labeling of graphs as an application of magic labeling. We solve a problem of finding number of computers/workstations to be allocated to each department in a company under certain conditions.
Keywords: Vertex magic labeling, Group magic labeling.
Scope of the Article: Graph Algorithms and Graph Drawing

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H91150711822

IJITEE Journal — Sat, 23 Jul 2022 12:05:09 +0000

Integrated Unified Crime Information Management System
Onu Fergus Uchenna¹, Ukabuiro Ikenna Kelechi², Douglas Allswell Kelechi³, Kingsley Maduabuchi Okorie⁴
¹Onu Fergus Uchenna, Department of Computer Science, Ebonyi State University, Abakaliki, Ebonyi State, Nigeria.
²Ukabuiro Ikenna kelechi, Department of Computer Science, Abia State University, Uturu, Abia State, Nigeria.
³Douglas Allswell Kelechi, Department of Computer Science, Federal University of Technology, Owerri, Imo State, Nigeria.
⁴Kingsley Maduabuchi Okorie, Director of Operations in Eagle Haulage, Lagos, Lagos State, Nigeria.
Manuscript received on 01 June 2022 | Revised Manuscript received on 22 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 87-92 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91150711822 | DOI: 10.35940/ijitee.H9115.0711822
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Crime detection, investigation and prosecution are usually carried out by the various law enforcement agencies saddled with such responsibilities. In this study, an integrated web based unified system was developed and implemented for the five (5) agencies (Nigerian Police Force, National Drug Law Enforcement Agency, Economic Financial Crime Commission, Independent Corrupt Practices Commission, Department of State Services) to enhance domiciliation of crime data into one system for effective information sharing among the five agencies. The methodology adopted for the system design is Object Oriented Analysis and Design Methodology (OOADM) and the tools used are HTML, CSS, JavaScript, MySQL. The result obtained shows that with the integration of the five agencies, accurate records of suspects and victims were timely shared by the various agencies. There is also an effective collaboration among the various agencies in crime detection, investigation and prosecution of suspects.
Keywords: Information – 1, Management – 2, System – 3, Crime – 4,Agencies and LEA – 5
Scope of the Article: Security, Privacy and Trust in IoT & IoE

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H91740711822

IJITEE Journal — Sat, 16 Jul 2022 09:46:13 +0000

Analytical Solution of Non-Linear DPL Bioheat Transfer Model for Temperature Dependent Metabolic Heat Source During Thermal Therapy
Neha Sharma¹, Surjan Singh², Dinesh Kumar³
¹Neha Sharma, Department of Mathematics, Eternal University, Baru Sahib, (H.P), India.
²Surjan Singh, Department of Mathematics, Eternal University, Baru Sahib, H.P., India.
³Dinesh Kumar, Department of Mathematics, Government Polytechnic College, Nawada (Bihar) India.
Manuscript received on 30 June 2022 | Revised Manuscript received on 11 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 78-86 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91740711822 | DOI: 10.35940/ijitee.H9174.0711822
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this research paper, the simulation based modelling of heat transfer in tissue under periodic boundary condition has been considered. The dual-phase-lag bioheat transfer (DPLBHT) model is implemented for computation of the temperature based thermal therapy treatment. The elements of volumetric heat source such as perfusion of blood, metabolism heat source and external heat source are considered in non-linear DPL model. In this paper we have taken three cases for metabolic heat source namely, constant, linear and exponential. The combined two numerical methods which are based on finite difference scheme and Runge – Kutta (4, 5) scheme are exerted to solve the non-linear problem. We compute the exact solution for particular case. Numerical conclusions which are computed by numerical hybrid method are equated with exact result. It has been found that non-linear DPL model with exponential metabolic heat source is closed to exact solution. We also expressed the effect of different parameters such as relaxation time, perfusion rate, metabolic heat source parameter, associated blood perfusion heat, heat source because of heat flux and temperature gradient etc.
Keywords: Bioheat, Hybrid Method, Metabolic Heat Source, Non-linear, Runge – Kutta Method, Thermal Therapy, Tissues.
Scope of the Article: Heat Transfer

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H91800711822

IJITEE Journal — Sat, 09 Jul 2022 09:04:22 +0000

Ensemble Filter Technique for Detection and Classification of Attacks in Cloud Computing
Darshan Thakur¹, Tanuja Pattanshetti²
¹Darshan Thakur, Department of Computer Engineering, College of Engineering, Pune (Maharashtra), India.
²Dr. Tanuja Pattanshetti, Department of Computer Engineering, College of Engineering, Pune (Maharashtra), India.
Manuscript received on 29 June 2022 | Revised Manuscript received on 04 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 67-74 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91800711822 | DOI: 10.35940/ijitee.H9180.0711822
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In all technologies, including traditional computing and cloud computing, security has always been the primary concern. In recent years, cloud computing has become widely accepted on a global scale. Cyber attacks aimed at it have increased along with its widespread acceptance. Although ample research is done in the security domain and cloud computing is based on rigid security fundamentals, the advancing network security attacks create the need for an advanced security mechanism. Also, the multiclass classification strategy has received very little attention, and classification accuracy can yet be improved. Hence, this work proposes an Ensemble Filter-based Intrusion Detection System (EFIDS) to address the limitations of previous research work. It not only identifies malicious traffic but also categorizes the attempted attacks (multiclass classification). The famous intrusion detection benchmark dataset, NSL KDD, is used to evaluate the model. Using the model, it was possible to enhance the classification accuracy of both binary and multiclass approaches up to 99.85 percent and 99.63 percent, respectively. Additionally, both forms of classification have shown a 65–70% improvement in training time.
Keywords: Cloud Computing, Security, Feature Filter, Classification.
Scope of the Article: Cloud Computing

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H91790711822

IJITEE Journal — Sat, 09 Jul 2022 08:58:09 +0000

Deep Learning Technique to Identify the Malicious Traffic in Fog based IoT Networks
Akshata Deshmukh¹, Tanuja Pattanshetti²
¹Akshata Deshmukh, Department of Computer Engineering, College of Engineering, Pune (Maharashtra), India.
²Dr. Tanuja Pattanshetti, Department of Computer Engineering, College of Engineering, Pune (Maharashtra), India.
Manuscript received on 30 June 2022 | Revised Manuscript received on 08 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 59-66 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91790711822 | DOI: 10.35940/ijitee.H9179.0711822
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The network of devices known as the Internet of Things (IoT) consists of hardware with sensors and software. These devices communicate and exchange data through the internet. IoT device-based data exchanges are often processed at cloud servers. Since the number of edge devices and quantity of data exchanged is increasing, massive latency-related concerns are observed. The answer to these issues is fog computing technology. Fog computing layer is introduced between the edge devices and cloud servers. Edge devices can conveniently access data from the fog servers. Security of fog layer devices is a major concern. As it provides easy access to different resources, it is more vulnerable to different attacks. In this paper, a deep learning-based intrusion detection approach called Multi-LSTM Aggregate Classifier is proposed to identify malicious traffic for the fog-based IoT network. The MLAC approach contains a set of long short-term memory (LSTM) modules. The final outcomes of these modules are aggregated using a Random Forest to produce the final outcome. Network intrusion dataset UNSW-NB15 is used to evaluate performance of the MLAC technique. For binary classification accuracy of 89.40% has been achieved using the proposed deep learning-based MLAC model.
Keywords: Internet of Things, fog computing, security, deep learning.
Scope of the Article: Internet of Things

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H91650711822

IJITEE Journal — Sat, 09 Jul 2022 08:42:49 +0000

Stress Detection using Facial Image for Elderly
Anupriya¹, Ashika Gupta², Mayank Singhania³, Sakchi⁴, Sudha B⁵
¹Anupriya, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
²Ashika Gupta, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
³Mayank Singhania, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
⁴Sakchi, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
⁵Prof. Sudha B, Assistant Professor, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
Manuscript received on 26 June 2022 | Revised Manuscript received on 03 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 75-77 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91650711822 | DOI: 10.35940/ijitee.H9165.0711822
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Stress plays an important role in late-life depression. It is a natural reaction to various factors which can lead to physiological and behavioural changes in human behaviour and performance. Dependence, ill health, loss of social role and recognition, and a lack of opportunity for creative use of leisure are some of the most common medical and psychological difficulties among the elderly. Automatic stress monitoring reduces the likelihood of health problems and promotes society’s well-being. Our project’s major goal is to use machine learning and image processing techniques to detect stress in the elderly population. Our system is an improved version of previous stress detection systems that did not include live detection, personal counselling, or stress level notification via a mobile device application. Instead, this system includes live detection and periodic analysis of the person in question, as well as detecting mental stress levels and notifying the person’s emergency contact. Our system is primarily targeted at the elderly, but it may also be used by students and IT professionals to manage stress and create a healthy, spontaneous work environment for employees, allowing them to give their best during working hours.
Keywords: Facial Image, Emotions, Encryption, Stress, Image-Processing.
Scope of the Article: Image Processing and Pattern Recognition

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H91730711822

IJITEE Journal — Sat, 09 Jul 2022 08:35:52 +0000

Big Data Heterogeneity A Short Review
Bhavana Hotchandani¹, Vishal Dahiya²
¹Ms. Bhavana Hotchandani, Department of Computer Science, Indus University, Ahmedabad (Gujarat), India.
²Dr. Vishal Dahiya, Department of Computer Science, Indus University, Ahmedabad (Gujarat), India.
Manuscript received on 30 June 2022 | Revised Manuscript received on 05 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 54-58 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91730711822 | DOI: 10.35940/ijitee.H9173.0711822
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The use of electronic devices and the digital globalization has brought a lot of technical revolution in the world. People use many devices and several applications available on the cloud. This leads to generation of ample amounts of data which is termed as huge data, technically a big data. This big data is heterogeneous in nature which is a combination of structured and unstructured data. This review paper aims to show the general facts of big data and then narrowing it down we are showing types of heterogeneous big data. This paper will help the novel researchers to gain facts about big data and its heterogeneity.
Keywords: 7Vs of Big data, Big Data, variety, heterogeneous data, heterogeneity.
Scope of the Article: Big Data Analytics

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H91690711822

IJITEE Journal — Sat, 09 Jul 2022 07:42:36 +0000

An Awareness of Superfoods for Healthy Lifestyle using Digital Marketing
Varsha Pimprale¹, Anushka Pillewar², Arya Deshpande³, Shyamali Neje⁴
¹Varsha Pimprale, Assistant Professor, Department of Computer, MKSSS’s Cummins College of Engineering, Pune (Maharashtra), India.
²Anushka Pillewar, Department of Electronics and Telecommunication, MKSSS’s Cummins College of Engineering, Pune (Maharashtra), India
³Arya Deshpande, Department of Information Technology, MKSSS Cummins College of Engineering, Pune (Maharashtra), India
⁴Shyamali Neje, Department of Electronics and Telecommunication, MKSSS’s Cummins College of Engineering, Pune (Maharashtra), India
Manuscript received on 29 June 2022 | Revised Manuscript received on 04 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 50-53 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91690711822 | DOI: 10.35940/ijitee.H9169.0711822
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Nowadays food is one of the major concerns of people. During this COVID-19 a pandemic situation, everyone wants to take the right food with its nutritional values. “Superfoods” are the expanded availability of products which has been a major demand for marketing. “Superfoods” has tremendously and recently gained attention along with the digital marketing strategy to motivate the super health benefits for the human body and also to prevent diseases and to provide the health benefits. Fruits and vegetables are the main sources of it. In many situations these foods play a very important role in decreasing the risk of critical conditions and diseases. Superfood represents a natural source of vitamins, minerals, and other nutrients required for a healthy lifestyle. These superfoods provided focusses on hygiene and balanced nutrition with the objective for promoting the health of the people in a better way [9]. This article explores how “Superfoods” awareness and its requirements can be known to common people using the blog. Therefore, we have created a blog on superfood and made a survey of it to know about the people’s views.
Keywords: Digital Marketing, Health, Organic Products, Promotions, Superfoods.
Scope of the Article: Healthcare Informatics

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H91640711822

IJITEE Journal — Sat, 02 Jul 2022 12:00:50 +0000

Brain Segmentation using MATLAB
V.V Nitin¹, T. Rohan², E. Sathwik³, T Satya Jayanth⁴
¹Venkata Nitin Voona, Department of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
²Ennapureddy Sathwik, Department of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
³Tamire Satya Jayanth, Department of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
⁴Thatikonda Rohan, Department of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
Manuscript received on 26 June 2022 | Revised Manuscript received on 02 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 43-49 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91640711822 | DOI: 10.35940/ijitee.H9164.0711822
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: A surprising mass of tissue wherein some cells duplicates and develops wildly is calledcerebrum growth. It should be identified at a beginning phase utilizing X-ray or CT checked pictures when it is just about as little as conceivable in light of the fact that the growth might perhaps result to malignant growth. This paper, for the most part centers around identifying and limiting the growth locale existing in the cerebrum by proposed philosophy utilizing patient’s X-ray pictures. The proposed procedure comprises of different stages which assume an alternate parts to deliver the examination with at most precision. division is applied to obviously show the growth impacted locale in the X-ray pictures. There are two main objectives of our project: 1) To analyze brain tumor 2) If there is, specify the location of the tumor.
Keywords: Brain Tumor, Matlab Analysis, MRI Analaysis
Scope of the Article: Artificial Intelligence

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