International Journal of Innovative Technology and Research (IJITR)
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Deep Learning-Based Cultivation Protection From Animals With Repellents
Get PDFThe main objective of this paper is to the expansion of cultivated land into previous wildlife habitat, crop raiding is becoming one of the most conflicts antagonizing human-wildlife relationships. Farmers in India face serious threats from pests, natural calamities and damage by animals resulting in lower yields. We concentrated on the crop protection from animal attacks. The conventional techniques have the same kind of security applied to all the types of animals detected based on a Passive IR sensor, and only single-stage protection is applied. The images were captured and identified with the help of machine learning and deep learning techniques. On each side of the farm entrance, the device was installed to capture the image for processing to identify the animals, based on the animal identification, different levels of security were applied, and that will produce different sounds with different Db levels and variety of dazzling light. This work provides a comprehensive description of the design, development, and assessment of an intelligent animal repelling system that allows for to detection and recognition of the animals. The enhancement is done by different levels of protection and different types of protection based on the classified animals. In initial level protection, making the noise and lightning from the opposite side send the animal out of the farm. If the animals are still on the farm, initiating the next stage that the image will send to the owner. The accuracy of all the methods discussed will be compared based on the complexity of the technique, implementation cost, reciprocating time, and accuracy of animal detection. Edge computing has become an essential technology for real-time application development by moving processing and storage capabilities close to ending devices, thereby reducing latency, improving response time, and ensuring secure data exchange
Stock Market Prediction and Performance for Price Forecast Using ML
Get PDFThe main objective of this paper is to find the best model to predict the value of the stock market. During the process of considering various techniques and variables that must be taken into account, it is found out that techniques like random forest, support vector machine were not exploited fully. In, this paper it is about to present and review a more feasible method to predict the stock movement with higher accuracy. The first thing that have been taken into account is the dataset of the stock market prices from previous year. The dataset was pre-processed and tuned up for real analysis. Hence, this paper will also focus on data preprocessing of the raw dataset. Secondly, after preprocessing the data will be reviewed to use the random forest, support vector machine on the dataset and the outcomes it generates. In addition, the proposed paper examines the use of the prediction system in real-world settings and issues associated with the accuracy of the overall values given. The paper also presents a machine-learning model to predict the longevity of stock in a competitive market. The successful prediction of the stock will be a great asset for the stock market institutions and will provide reallife solutions to the problems that stock investors face.
Identifying Unauthorized Transactions On Credit Cards By Using Machine Learning Methodologies
Get PDFIt is essential for organizations that issue credit cards to be able to recognize fraudulent credit card transactions. This will prevent consumers from being charged for products that they did not buy with their credit card. The purpose of this project is to demonstrate the modelling of a data set via use of machine learning for the detection of credit card fraud. The problem of detecting fraudulent use of credit cards requires modelling previously completed credit card transactions using the information from those that were determined to be fraudulent. After that, this model is put to use to determine whether or not a new transaction constitutes fraudulent activity. Our goal is to appropriately handle misclassified categories by reducing the number of false Negative cases. During this stage of the process, our primary focuses have been on the analysis and preprocessing of data sets, as well as the application of multiple anomaly detection algorithms these algorithms include the local outlier factor and the isolation forest algorithm. We have used IEEE_CIS Fraud dataset, provided by the kaggle .we applied feature extraction technique to reduce the dimensionality of large dataset by extracting only those principle components with highest variance. Given the class imbalance ratio, we measured the accuracy using the Area Under the Precision-Recall Curve (AUPRC) which gives better results than any other previously used models
Planning to Implement Deep Learning Techniques for Object Tracking
Get PDFDetecting objects is a fundamental challenge in computer vision. As the same item might appear significantly differently depending on factors such as orientation, illumination, backdrop, and occlusion, detection can be challenging. Because of recent developments in deep learning and neural networks, we no longer need to come up with new heuristics on the fly in order to solve this kind of issue. Using a convolutional neural network (CNN) method, the "Object Detection" project can quickly and accurately identify objects in images. The identification of objects in arbitrary positions and orientations is made possible by a number of techniques, including "You Only Look Once" and other convolutional neural networks. We begin by using a convolutional neural network that has already been trained
Predicting Flight Delays with Error Calculation
Get PDFFlight delay is vexatious for passengers and incurs an agonizingly high financial loss to airlines and countries. A structured prediction system is an indispensable tool that can help aviation authorities effectively alleviate flight delays. This project aims to build a two stage machine learning engine to effectively predict the arrival delay of a flight after departure based on real-time flight and weather data
A Review Study On Sustainable Solutions In Special Domains Using AI And ML
Get PDF"Sustainability means meeting our own needs without compromising the ability of future generations to meet their own needs. In addition to natural resources, we also need social and economic resources. Sustainability is not just environmentalism. Embedded in most definitions of sustainability we also find concerns for social equity and economic development." In this paper we will see as applications of AI and ML , sustainable solutions in some special domain areas
Student Placement Prediction Using Face Recognition
Get PDFThe paper presents a computer based placement to replace manual procedures adapted by institutes. As is around the year activity involving thousands of candidates a need has been felt to automate the entire operations. The candidate would be able to attend a real time interview with the help of this system. Face expression recognition facility in the system will enrich the system with the capability of analyzing the gestures and ethics. The system will also provide feedbacks for the students to improve their performance. Instant feedbacks will in turn increase the diversity and inclusion
Digital Voting Process via Block Chain Technology
Get PDFElectronic voting is growing in popularity in today's culture. It has the ability to reduce administrative expenses and boost participation in the electoral process. Voters can cast their ballots from any location with an Internet connection, doing away with the necessity for paper ballots and polling places. Regardless of their merits, online voting solutions are seen with skepticism due to the fact that they present novel security risks. Vote rigging on a massive scale is possible due to a single vulnerability. When used for elections, electronic voting systems must be reliable and secure. However, problems with computerized voting systems may slow their widespread adoption. Electronic voting systems are being developed using blockchain technology due to the end-to-end verification benefits it provides. Electronic voting systems that lack the distributed, non-repudiation, and security features of this technology are missing out. A summary of blockchain-based electronic voting methods is provided here. The primary purpose of this analysis was to look at where things stand with blockchain-based voting research and online voting systems, as well as any problems with foreseeing their future that may exist. This serves as both a conceptual overview of the planned blockchain-based electronic voting application and an introduction to the blockchain's core structure and properties as they pertain to electronic voting. Several of the problems that currently afflict election systems may be solvable with the help of blockchain technologies, it has been found. Yet, concerns about privacy and transaction speed frequently come up when discussing the use of blockchain technology in practical contexts. Secure remote voting is essential for a scalable blockchain-based electronic voting system, and fast transactions are necessary for widespread adoption
Reference Based Study On Soundtrack (Music) Sustainable Solutions Using AI Techniques
Get PDFArtificial intelligence (AI) has been used in applications to alleviate certain problems throughout industry and academia. AI, like electricity or computers, is a general-purpose technology that has a multitude of applications. It has been used in fields of language translation, image recognition, credit scoring, e-commerce and other domains. Computer music is the application of computing technology in music composition, to help human composers create new music or to have computers independently create music, such as with algorithmic composition programs. It includes the theory and application of new and existing computer software technologies and basic aspects of music, such as sound synthesis, digital signal processing, sound design, sonic diffusion, acoustics, electrical engineering, and psychoacoustics. The field of computer music can trace its roots back to the origins of electronic music, and the first experiments and innovations with electronic instruments at the turn of the 20th century. In this paper we will study how AI is applied for sustainable music solutions
Secure Clouds Through Reputation-Based Cloud Service Trust Management
Get PDFInadequate mechanisms for managing user trust in cloud services are a major roadblock to the broad adoption of this technology. Difficulties with privacy, security, and availability are inevitable in the cloud because of the service's intrinsic malleability, dispersion, and lack of transparency. Due to the sensitive nature of the information shared between customers and the trust management service, confidentiality must be maintained at all times. It's difficult to prevent malicious individuals from disrupting cloud services (for example, by providing false or misleading feedback to make a cloud service seem bad). Due to the dynamic nature of cloud infrastructure, it may be challenging to guarantee the constant availability of the trust management service in a cloud environment. We discuss the design and implementation of Cloud Armor, a reputation-based trust management framework that offers a collection of functions to provide Trust as a Service, with the goals of protecting cloud services from malicious users and comparing the trustworthiness of various cloud services. A unique protocol to verify the credibility of trust feedbacks while protecting users' anonymity; and (ii) an adaptive and resilient credibility model for gauging the veracity of trust feedbacks. Our approach's benefits and viability have been demonstrated through prototype development and experimentation with real-world trust feedback on cloud services