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AR and Online Purchase Intention Towards Eye Glasses
Augmented reality (AR) can be a potent tool for Indian online eyewear marketers by bridging the gap between online and offline purchasing experiences and meeting the needs of social validation and sensory engagement, which are preferences of Indian consumers. The present research explores how augmented reality (AR) technology affects Indian consumers' intentions to buy glasses online. A combination of descriptive and exploratory research design was used on the sample size of 236 consumers. Data was analyzed using frequency table and Structured Equation modelling (SEM) to identify the relationship amongst the variables. The findings indicate that accessibility to product information, telepresence, and perceived ease of use are important variables impacting purchase intention. AR can bridge the gap between online and offline experiences, meet consumer preferences, and create trust and confidence. Future research should explore AR's effectiveness and personalization possibilities for Indian online eyewear retailers. Future research should explore AR's effectiveness and personalization possibilities for Indian online eyewear retailers. 2024 IEEE. -
Arabica Coffee Bean Grading into Specialty and Commodity Type Based on Quality Using Visual Inspection
Expanding potential of coffee consumers to seek out the freshest and best flavors is a cause for the rise of specialty coffee inthe market. Specialty coffee is grown and harvestedmaintaining an emphasis on quality and clarity of flavor, whereas commodity coffee is harvested for caffeine content. Within those inclusive categories, arabica and robusta are the two types of main branches of coffee that weencounter in the coffee market. Specialty coffees differ significantly from conventional coffees in that they are cultivated at higher altitudes, can be traced, and are professionally processed after being harvested. The quality is constantly examined and understood at every stage, from growth to brewing. Green arabica quality is assessed by counting the defective beans present in the sample. These defects can be primary (Category I) or secondary (Category II). If the primary defects are null and less than five secondary defects, coffee is said to be a specialty.Prior research has been done on classifying the coffee species and differentiating good beans from bad beans. Our research involves the combination of machine learning like K-NN and deep learning convolutional neural networks for classifying specialty coffee from commodity type using computer vision. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
ArcGAN: Generative Adversarial Networks for 3D Architectural Image Generation
Due to advancements in infrastructural modulations, architectural design is one of the most peculiar and tedious processes. As the technology evolves to the next phase, using some latest techniques like generative adversarial networks, creating a hybrid architectural design from old and new models is possible with maximum accuracy. Training the model with appropriate samples makes it evident that the designing phase will be simple for even a layman by including proper parameters such as material description, structural engineering, etc. This research paper suggests a hybrid model for an architectural design using generative adversarial networks. For example, merging Romes architectural style with Italys will accurately and precisely recover the pixel-level structure of 3D forms without needing a 2D viewpoint or 3D annotations from a real 2D-generated image. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Are Women Employees in Engineering Institutions Suffer from the Stress: An Investigation Approach
Workplace stress could be detrimental to both the employer and its employees. The greatest ways to keep distress at bay in the workplace are via competent management and well-organized processes. Supervisors must recognize signs of staff distress and be prepared to provide assistance. Whenever an individual is confronted with job expectations and pressures exceeding their skillset and expertise, they experience stress connected to their employment. Workplace stress is common and could exacerbate stress when workers don't perceive they have the backing of management or coworkers in dealing with the challenges they face. The term 'stressed' is frequently used as a justification for ineffective management and inadequate supervision, even though it is typically caused by a misunderstanding of the difference between pressure and challenge. Stress and other forms of adversity are at an all-time high, both in the job and in personal life. Employee stress could be further exacerbated by things like job uncertainty, excessive hours, frequent changes, workload, and unattainable targets. The purpose of this article is to understand the variables that contribute to high-stress levels amongst female faculty members in engineering institutions strain in the job atmosphere. One's ability to manage stressful work situations, the amount of social help and assistance one receives, and the coping mechanisms one employs all play significant roles in how much stress one endures on the job. This research was done because it was necessary and important. In addition, women play a larger role in society than males do. This study suggests that women experience much high levels of stress than men do employment reasons, repercussions, roles and obligations of women faculty in engineering education, and possible remedies are all explored in this paper. 2023 IEEE. -
Area and Energy Efficient Method Using AI for Noise Cancellation in Ear Phones
Adaptive filters are suitable for most of the Digital Signal Processing (DSP) applications such as channel equalization, noise cancellation, echo cancellation, channel estimation and system identification. Nowadays due to the advancement in semiconductor technology, the need for Active Noise Cancellation (ANC) headphones in compact devices is increased. The major idea behind this proposed work is to design an area and energy efficient novel adaptive filter suitable for in-ear headphones by combining Normalized Least Mean Square (NLMS) and Block LMS (BLMS). The proposed filter is designed and simulated using Xilinx ISE 13.2. The simulation results shows that the proposed design mitigates the unwanted noises in various frequency bands. 2023 IEEE. -
Arming Farmers with Smart Farming: The Future of Agriculture
Internet of Things (IoT) innovation is currently one of the growing fields across a diversity of industries, together with agriculture. IoT enhances our lives by making and promoting developments in a wide range of actions to encourage them to become more appropriate, practicality, and enhanced using suitable man-made recognition. Smart agricultural frameworks recognize a social trade toward more helpful, lower-cost agribusiness because of this innovation. The proposed work is to use IoT in the agriculture industry to collect real-time data (soil moisture, temperature, and so on) to help one look at a few climate scenarios from afar, efficiently, and greatly increase production. A global solution for monitoring and managing the agricultural field remotely has been proposed. Implementation of a local stand-alone field control unit that includes detection and activation capabilities. Developed a cloud solution for data storage, real-time monitoring, and historical data visualization based on the ThingSpeak cloud platform. Remote managing and control functions have been realized in both the local unit and the cloud using IoT infrastructure. 2022 IEEE. -
AROSTEV: A Unified Framework to Enhance Secure Routing in IoT Environment
The Internet of Things (IoT) is a global network which collects, process, and analyzes the data. IoT sensors and devices are limited to low memory, power, and processing capabilities. The RPL is a proactive routing protocol which is mainly intended for the IoT. There is a possibility of routing vulnerabilities, which masquerade the data in IoT environment. In order to overcome this problem, a framework called AROSTEV is proposed which comprises of three techniques such as RDAID, RIAIDRPL, and E2V. The primary objective of AROSTEV framework is to detect and mitigate the routing attacks such as rank decreased attack (RDA), rank increased attack (RIA), and rank inconsistency attack (RInA), respectively. Each technique takes the responsibility to progress its activity against the internal routing attacks. This framework can be used to implement the smart city environment. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Artificial Intelligence (AI) in CRM (Customer Relationship Management): A Sentiment Analysis Approach
The use of customer relationship management (CRM) in marketing is examined in this essay. It looks at how CRM makes it possible to use reviews, integrate AI, conduct marketing in real time, and conduct more regular marketing operations. CRM tactics are illustrated through case studies of businesses like Uber, T-Mobile, Amazon, Apple, and Apple. CRM offers centralized data, better marketing and sales, and better customer support. There is also a discussion of the ethical, private, security, adoption, and scalability challenges of AI in CRM. In general, CRM makes data-driven decisions and customer insights easier to achieve to increase growth, loyalty, and engagement. 2024 IEEE. -
Artificial Intelligence & Automation: Opportunities and Challenges
Artificial Intelligence (AI) and Automation innovation are growing at a steady rate that are changing organizations and bringing efficiency and adding to the economic development. The utilization of AI and robotization will likewise help improve different areas from wellbeing to horticulture. Furthermore, utilizing Automation and Artificial Intelligence would, follow the schedule, transform the idea of work and the working environment itself. For sure, machines will actually do large numbers of the undertakings typically done by people, just as supplement manual work and play out certain errands that an individual wouldn't have the option to do. Consequently, AI and mechanization have a great deal to bring to organizations and enterprises worldwide. This research paper comes up with a rundown through the blooming of Artificial Intelligence and Automation. We explored the existing potentiality of cognitive emerging technologies. This paper outlines the discussion about artificial intelligence and automation technologies and an overview of the applications. 2023 American Institute of Physics Inc.. All rights reserved. -
Artificial Intelligence & Data Warehouse Regional Human Resource Management Decision Support System
High-quality data is utilized to make informed decisions that effectively help to successfully safeguard our environment. When there is an abundance of information that is both heterogeneous in nature (coming from a wide variety of fields or sources) and of unknown quality, various problems may occur. Furthermore, the problem's dynamic nature also imposes some other complications. In order to deal with such complications, the central role played by supercomputers in the modern environment is to promote protection initiatives like monitoring, data analysis, communication, and information storage and retrieval. In current days, the higher dependency on the data management process forced the developers to integrate and enhance all these initiatives with Artificial Intelligence knowledge-based techniques so that smart systems can be utilized by a vast number of people. In this context, this study has illustrated how Artificial Intelligence methods have changed the nature of Environmental Decision Support Systems (EDSS) over the course of the last two decades. The strengths that an EDSS should exhibit have been emphasized in this review. In the final section, we look at some of the more innovative solutions used for various environmental issues. 2022 IEEE. -
Artificial Intelligence and Deep Learning Based Brain Tumor Detection Using Image Processing
In the field of medical science, applications that are particularly used for diagnostic purposes, are used in the detection of brain tumors since detecting an error in MRI scanning is becoming a major task for radiologists and requires a lot of their focus. Flaws that are prevalent during tumor detection must be taken care of to avoid further complications. MRI scanning is one of the most recently developing technologies. The radiologist is a key player in the identification of the brain tumor. Radiologists have to check every image perfectly to avoid the errors in identifying the brain tumor. There is a probability that sometimes cerebral fluid may also appear as mass tissue during the MRI scan. The model that is proposed in this research uses a machine learning algorithm which helps to improve the validity of the classification of the images that are taken in MRI scans. The study focuses on having an automated system that carries out an essential role in determining whether a lump is present in the brain or not. The study tries to resolve the primary flaws in detection necessary to evade further complications in MRI images in brain detection. The main aim of this study is to train the algorithm in a more extensive dataset and to check the patient-level validity with the help of various new datasets. 2023 IEEE. -
Artificial Intelligence and Machine Learning Combined Security Enhancement Using ENIGMA
Enigma is a relatively new and emerging field that has the potential to bring significant benefits to the way contracts are executed and managed. The integration of Artificial Intelligence (AI) into smart contract technology can automate repetitive tasks, reduce the need for human intervention, improve decision-making, and provide transparency and trust. It can also provide more flexibility, handle more complex tasks, learn from past experiences, have predictive capabilities, and have human oversight and intervention. All these features make Enigma contracts more advanced than traditional smart contracts. AI-powered smart contracts, or Enigma contracts, can also improve contract execution, increase efficiency, facilitate better negotiation, and facilitate automated dispute resolution. However, as the technology is still in its early stages, major challenges and risks can adopted but the need for robust security. The potential for AI is to make decisions that are not in the best interests of its parties. Despite these challenges, the potential benefits of AI-powered smart contracts make them an area of on-going research and development that is worth exploring further. Enigma can be used or applied in various fields, and can be used to secure the sensitive information by applying robust security system. Enigma contract is a AI powered smart contract which is used to automate decision-making processes and improve its efficiency, Enigma as the name suggest it is a complex security network which has the potential to revolutionize the security system by increasing efficiency. 2023 IEEE. -
Artificial Intelligence and Machine Learning-Based Systems for Controlling Medical Robot Beds for Preventing Bedsores
Artificial Intelligence is one of the most important technologies of the modern world which is continuously changing the dimensions of almost every sector. AI and IoT have together resulted in multiple outstanding technological innovations which have also impacted the healthcare sector massively. This study has critically focused on the role of AI and robotics in the treatment outcomes for patients. This study has done deep research regarding the role of automated beds in reducing pressure ulcers or bed sores among patients who are recovering from any chronic disease. This entire study has secondary qualitative data collection for analyzing the design and microcontroller systems in automated beds. This has provided a detailed data analysis with relevant equations and tables for reaching its proposed outcomes. 2022 IEEE. -
Artificial Intelligence Application in Human Resources Information Systems for Enhancing Output in Agricultural Companies
Artificial intelligence (simulated intelligence) apparatuses like master systems, normal language handling, discourse acknowledgment, and machine vision have changed how much work in agribusiness, yet in addition its nature. This is on the grounds that the total populace and interest for food are developing, and the climate and water supply are evolving. Specialists and researchers are presently moving towards involving new IoT advances in shrewd cultivating to assist ranchers with utilizing manmade intelligence innovation to improve seeds, crop security, and composts. This will get ranchers more cash-flow and help the pay of the country in general. In agribusiness, computer-based intelligence is making its mark in three primary regions: checking soil and harvests, prescient examination, and cultivating robots. Along these lines, ranchers are utilizing sensors and soil tests increasingly more to accumulate information that can be utilized by ranch the board apparatuses for additional exploration and examination. This book adds to the field by giving an outline of how computer-based intelligence is utilized in agribusiness. It begins with a prologue to simulated intelligence, including a survey of all the computer-based intelligence techniques utilized in horticulture, similar to AI, the Web of Things (IoT), master systems, picture handling, and PC vision. 2024 IEEE. -
Artificial Intelligence Based Enhanced Virtual Mouse Hand Gesture Tracking Using Yolo Algorithm
Virtual mouse technology has revolutionized human computer interaction, allowing users to interact with digital environments without physical peripherals. The concept traces back to the late 1970s, and over the years, it has evolved with significant advancements in computer vision, motion tracking, and gesture recognition technologies. In recent times, machine learning techniques, particularly YOLOv8, have been integrated into virtual mouse technology, enabling accurate and swift detection of virtual objects and surfaces. This advancement enhances seamless interaction, intuitive hand gestures, and personalized virtual reality experiences tailored to individual user preferences. The proposed model, EHT (Enhanced Hand Tracking), leverages the power of YOLOv8 to address the limitations of existing models, such as Mediapipe. EHT achieves higher accuracy in hand tracking, real-Time hand gesture recognition, and improved multi-user interactions. It adapts to users' unique gestures over time, delivering a more natural and immersive computing experience with accuracy rates exceeding those of Mediapipe. For instance, across multiple sample datasets, EHT consistently outperformed Mediapipe in hand tracking accuracy. In Sample Dataset 1, EHT demonstrated an accuracy of 98.3% compared to Mediapipe's 95.65%. Similarly, in Sample Dataset 2, EHT achieved an accuracy of 99.35%, surpassing Mediapipe's 94.63%. Even in Sample Dataset 3, EHT maintained its superiority with an accuracy of 98.54 %, whereas Mediapipe achieved 98.26%. The successful implementation of EHT requires a custom dataset and optimization techniques to ensure efficiency on virtual reality hardware. EHT model is anticipated redefining how users interact with digital environments, unlocking new possibilities for intuitive and immersive computing experiences. 2023 IEEE. -
Artificial Intelligence based Semantic Text Similarity for RAP Lyrics
Data mining is the primary method of gathering large volumes of knowledge. To make use of such data to implementation requires the use of effective machine learning strategies. Semantic Textual Similarity is one of the primary machine learning strategies. At its core, semantic textual similarity is the identification of words with similar context. Initial work in STS involved text reuse, word search among others. The proposed research work uses a specific method of determining textual similarity using Google's Word2Vec framework and the Continuous-bag-of-words algorithm for identifying word similarity in rap records. A large data set consisting of over 50,000 rap records is used. The key aspect of proposed methodology is to determine the words with similar context and cluster them into different word clusters also called bags. To achieve the desired result, the dataset is first processed to obtain the features. Once the features are selected, a model is generated by passing the data onto the Word2Vec framework. The research work on semantic textual similarity was repeated across three different runs, with the data set size changing in every run. At the end of each the accuracy of similarity obtained by the model was determined. The current research work has achieved average accuracy as 85%. 2020 IEEE. -
Artificial Intelligence based System in Protein Folding using Alphafold
Artificial Intelligence has a high potential to solve many real-world problems. In the recent years researchers are dealing with one of the biggest complications in biology, which is protein folding. With the assistance of technology, we can foresee how proteins fold from a chain of amino acids into 3D shapes that do life's errands. There are mainly three big problems associatedwith folding of proteins. The first problem is there any particular folding code. The second one there is a folding system. Then the final problem is we able to determine the 3D structure of proteins. Proteins are the microscopic machines and structural building blocks of our cells. They carry out important functions like breaking down foods, storing oxygen and forming scaffolds to help cells keep their shape. Each one is built up of one amino acid chain that folds in on itself into a mostly defined structure. Each part of our body and in any other organism is made either from or by proteins and this is true for every living creature, even for viruses. The structure of very small proteins can be foreseen using the computer method. This article is all about the protein folding problem with more spotlights on the role of AI-based systems in protein structure forecasts. The motivation behind this article is to convey an overall understanding of AI-based answers for protein folding problems. 2022 IEEE -
Artificial Intelligence for Enhanced Anti-Money Laundering and Asset Recovery: A New Frontier in Financial Crime Prevention
The incorporation of artificial intelligence (AI) into asset recovery and anti-money laundering (AML) procedures signifies a revolutionary change in the handling of financial crime. This article investigates the use of AI techniques to improve AML compliance, detect suspicious activity, and improve transaction monitoring. Financial institutions can now analyze massive volumes of transaction data in real-time, find anomalies, and lower false positives thanks to AI-based solutions, which include machine learning algorithms and predictive modeling. The research also outlines the difficulties and advantages of implementing AI, such as enhancing the effectiveness and caliber of suspicious activity reports (SARs) while resolving security and privacy issues with data. The study makes the case that AI's capacity to offer collaborative analytics and dynamic risk assessments is essential for the development of AML frameworks and the overall effectiveness of financial crime prevention. 2024 IEEE. -
Artificial Intelligence in Data-Driven Analytics for the Personalized Healthcare
Among the various developments in progress over the last decade, we have seen the generous growth of information investigation to take care of, plan, and use a lot of information beneficially. Be that as it may, because the analysis of evidence will only operate for authentic information and have findings as predefined by individuals, explicit principle-based calculations have been developed to broaden the investigation of information, 'Which is usually referred to as 'AI'. AI didn't expect PCs to be personalized unambiguously, which is a definite bit of leeway. In order to break down information and construct complicated equations to foresee models, which was called prescient analysis, AI was then joined with information inquiry. A set of laws characterized by persons, known as prescient equations, drive the prescient inquiry, and are used to break down genuine knowledge in order to predict potential outcomes. 2021 IEEE. -
Artificial Intelligence in Disaster Management: A Survey
This paper provides a literature review of cutting-edge artificial intelligence-based methods for disaster management. Most governments are worried about disasters, which, in general, are unbelievable events. Researchers tried to deploy numerous artificial intelligence (AI)-based approaches to eliminate disaster management at different stages. Machine learning (ML) and deep learning (DL) algorithms can manage large and complex datasets emerging intrinsically in disaster management circumstances and are incredibly well suited for crucial tasks such as identifying essential features and classification. The study of existing literature in this paper is related to disaster management, and further, it collects recent development in nature-inspired algorithms (NIA) and their applications in disaster management. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.