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Application of Machine Learning to the Process of Crop Selection Based on Land Dataset S. Suman Rajest; S. Silvia Priscila; R. Regin; Shynu T; Steffi. R
International Journal on Orange Technologies Vol. 5 No. 6 (2023): International Journal on Orange Technologies
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v5i6.4546

We are well recognised that the vast majority of Indians work in agriculture. Most farmers always grow the same thing, always use the same amount of fertilizer, and always plant what the people want. Recently, there have been many breakthroughs in the use of machine learning in many fields of study and business. Thus, we intend to establish a framework for the application of machine learning in agriculture for the benefit of farmers. India's economy relies heavily on the nation's agricultural output. Agriculture, then, has the potential to serve as the backbone of the Philippine economy. Choosing the right crop every time is crucial when making agricultural plans. Researchers have utilised machine learning to explore agricultural issues such as crop yield, weather prediction, soil categorization, and crop labelling. Our Indian economy really needs the agricultural sector to undergo significant reforms. Simple applications of machine learning systems in agriculture have the potential to significantly enhance this industry. In addition to the considerable role played by improvements in farming machinery and technology, functional information about many subjects also plays an important role. The main idea of this study is to use the crop selection approach in order to address numerous issues in farming. This increases the wealth of India by increasing crop yields to their maximum potential. In our study, we use the method Random Forest (RF) to estimate a crop and then evaluate its performance relative to that of competing techniques

Android Application for Remote Control of Personal Computers Shynu T; S. Suman Rajest; R. Regin; Steffi. R
International Journal on Orange Technologies Vol. 5 No. 12 (2023): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v5i12.5126

The development of mobile devices, particularly in these modern times, has brought about a significant transformation in the way business is conducted. The capability of a mobile phone device is frequently anticipated to be comparable to that of a computer. In this day and age, the majority of people who use mobile phones feel that performing some things on their computers is inconvenient. The majority of people find that switching postures when sitting or stretching not only makes them feel more comfortable, but also makes them feel more at ease when they are browsing through their laptops. Standing five or ten feet away from the computer while being restricted to using only the keyboard and mouse can be an impractical situation. Additionally, the system provides the features to access the files that are available on the computer; if the file appears to be a media file, this Android app can play, pause, stop, mute, and turn on/off full-screen mode of the respective media. As a result, the application that is being proposed is intended to transform the handphone into a wireless keyboard or mouse that also includes a touch pad. The wireless network is the medium through which the link is established (WiFi). It has been demonstrated that this prototype is capable of performing the majority of the functions that are often associated with a computer.

Using a Deep Convolutional Neural Network to Identify Vehicle Driver Activity Shynu T; S. Suman Rajest; R. Regin; Steffi. R
International Journal on Orange Technologies Vol. 6 No. 1 (2024): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v6i1.5185

Driver actions and judgments are the most critical aspects influencing passenger safety in a vehicle. Common things that drivers do include: driving safely, talking on the phone, texting, eating, reaching behind, altering hairstyle or makeup, operating the radio, and operating mobile phones. The first four are considered typical driving duties, whereas the latter seven are considered distractions. The strategy is to take in the live feed from the dashboard camera, process the frames with pre-trained convolutional neural network (CNN) models, and then refine it with the transfer learning method to identify the driver's activities. An activity recognition system for drivers is developed utilising deep Convolutional Neural Networks in order to monitor their actions (CNN). A warning is sent to the driver based on the identified driver's actions. In addition to activating the warning lights, the system gently slows down the vehicle or forces the driver to shift to the side lane and come to a complete stop in order to protect everyone in the vehicle and the surrounding area.

The Application of Machine Learning to the Prediction of Heart Attack R. Regin; S. Suman Rajest; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 5 No. 4 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i4.4259

Heart illnesses are among the most significant contributors to mortality in the world in the modern era. Heart attacks are responsible for the death of one person every 33 seconds. disease of the cardiovascular system by disclosing the proportion of mortality all over the world that are caused by heart attacks. In order to forecast instances of heart disease, a supervised machine learning method is utilised. Because the incidence of heart strokes in younger people is growing at an alarming rate, we need to establish a method that can identify the warning signs of a heart attack at an early stage and stop the stroke before it occurs. Because it is impractical for the average person to often undertake expensive tests like the electrocardiogram (ECG), there is a need for a system that is convenient and, at the same time, accurate in forecasting the likelihood of developing heart disease. Therefore, our plan is to create a programme that, given basic symptoms such as age, sex, pulse rate, etc., can determine whether or not a person is at risk for developing a cardiac condition. The machine learning algorithm neural networks that are used in the suggested system are the most accurate and dependable.

An Approach Based on Machine Learning for Conducting Sentiment Analysis on Twitter Data S. Suman Rajest; R. Regin; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 5 No. 12 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i12.5122

Using Twitter's primary goals as a guide, we built a real-time sentiment analysis system that labels tweets according to the emotions they convey. One more way Twitter facilitates social networking is through microblogging, which allows users to record brief status updates. The analysis of the emotions conveyed at intervals between tweets allows us to get a reflection of public attitude, which is made possible by this massive amount of usage. The goal is to find the most accurate way to examine the information by primarily applying approaches based on machine learning. Data validation, cleaning, and preparation for visual representation will be performed on the entire provided dataset after the controlled AI technique (SMLT) has been used to capture various pieces of information, such as variable ID, amount and factual strategy, missing worth medicines, and univariate examination. Through the discovery of the optimal exactness computation, our inquiry provides a comprehensive guide to sensitivity analysis of model parameters in relation to performance in sentiment analysis prediction. All of the algorithms' performance metrics, including exactness recall, f1score, sensitivity, and specificity, are also computed and compared.

Planning the Most Effective Itinerary for Tourists through the use of Data Analysis R. Regin; S. Suman Rajest; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 5 No. 12 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i12.5124

In order to provide the most effective scheduling alternatives, data analysis of the information that the customer has provided is performed. The mobile application provides further recommendations, such as a list of all the appropriate sites or areas to visit inside the destination that has been picked, once the intended destination has been specified. In addition, the other significant recommendations concerning the method of transportation, the most efficient routes, the most desirable times, and the expenses associated with them will be automatically offered. Additionally, the Android Studio toolkit and the Google Maps interface are utilised in the process of application creation. Hadoop is used for the analysis of weather data. Hadoop is a Java programming platform and open-source Apache software that is utilised in the distributed world for the purpose of managing the management of enormous data volumes. One of the most significant benefits is the utilisation of the machine learning approach to cost estimation in the budget planning process. Travel plans that are efficient are provided by the intelligent local route as well as the form of transportation. The online application offers a platform that functions as a digital assistant that is intelligent and tailored to the tourists' areas of interest.

A QR Code-Based Real-Time Auditing System for Safe Online Data Storage S. Suman Rajest; R. Regin; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 6 No. 1 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i1.5186

Up until now, auditing systems have only had a web module; these modules are complicated and not user-friendly. Protecting sensitive data stored in the cloud requires the time-consuming and laborious procedure of encrypting all of the files. To verify a user's identification in the current system, the client must input biometric data. Next, in order to safeguard the user's identity and privacy, a signature key will be validated. One major problem with biometric data is that there are a lot of circumstances that might cause it to vary, so it can't always be matched precisely. An auditing and data storage app built for the cloud is the focus of this paper. The reference ID that the client creates is used to remotely store the financial audit data in the cloud. Using a QR code scanner, this reference ID that was generated for the client is immediately transformed into a QR code. You can access the required documents by downloading them and then opening them in a dedicated app. In the event that the client's internal storage becomes corrupted or lost, this file can be restored from the cloud.

SwiftTrip: Your Smart Travel Companion for Effortless Planning and Memorable Journeys R. Regin; Rajest , S. Suman
International Journal on Human-Computing Studies Vol. 6 No. 3 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i3.5316

This paper presents "SwiftTrip," an innovative tool designed to enhance travel planning by integrating location, activity, weather, and packing considerations. As travel becomes increasingly spontaneous, there is a need for comprehensive solutions that cater to dynamic travel environments. "SwiftTrip" addresses this gap by offering detailed vacation itineraries, weather forecasts, and customized packing lists. The system utilizes climate patterns to suggest optimal travel routes and weather-sensitive recommendations for attractions and activities. Advanced algorithms analyze meteorological data to generate personalized packing lists, ensuring travelers are prepared for varying weather conditions. By providing current and forecasted weather data, including temperature, precipitation, and wind speed, "SwiftTrip" aims to make travel planning more informed and enjoyable, ultimately enhancing the travel experience in a rapidly changing environment.

Adoption Restraints in Mobile Banking with Reference to India Deepa Damodaran; R. Regin; S. Suman Rajest
International Journal on Economics, Finance and Sustainable Development (IJEFSD) Vol. 6 No. 1 (2024): International Journal on Economics, Finance and Sustainable Development (IJEFSD
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijefsd.v6i1.5172

The number of people using mobile banking has been steadily growing over the past few years. Most of the time, this is the case in countries that are still developing or underdeveloped. It is proposed to investigate the comparative significance and distinctive influence of communication channels on customers' theories and attitudes regarding the adoption of mobile banking in India. This is despite the fact that the technology that provides services to the satisfaction of the user has not yet been investigated. "Perceived usefulness, perceived credibility, impact of communication channels, interpersonal networks, mass media, and social media" are the five primary variables that are incorporated into the study from a variety of perspectives. In the findings, it was discovered that the most important factors that influence the consumer's intention are the convenience of use and the cost. Banks ought to raise greater awareness and make it easier for customers to utilise themselves.

A New Natural Language Processing-Based Essay Grading Algorithm S. Suman Rajest; R. Regin; Shynu T; Steffi. R
International Journal on Integrated Education Vol. 6 No. 3 (2023): International Journal on Integrated Education (IJIE)
Publisher : Researchparks Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijie.v6i3.4079

The evaluation of an English essay is one of the most significant and difficult activities that is manually carried out by knowledgeable and capable instructors and faculty members. The advancement of science and technology has made it possible to automatically evaluate an English essay by employing techniques pertaining to natural language processing. For any given English essay, the intelligent system provides a generic evaluation as well as the topic/question correlation. This evaluation is based on the NLP multiple neural network model, which was used to build the system. The evaluation of essays according to worldwide standards is the primary contribution of this innovation. Any worldwide grading system, such as the Graduate Record Examination, the International English Language Testing System, etc., is qualified to make use of the grading standard. The algorithm gives users the opportunity to test their knowledge on a range of criteria, from the most basic to the most complicated, that are included in the scoring of an English essay.

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