Akhilesh A Waoo
Biographic Data
| ID | 10126943 |
|---|---|
| NAME | Akhilesh A Waoo |
| GIVEN NAMES | Akhilesh A |
| FAMILY NAME | Waoo |
| SIGNATURE | WAOO A A |
| AFFILIATIONS | Amicable Knowledge Solution University |
| ORCID | 0000-0001-6788-710X |
| VERIFIED | Yes |
| TOTAL WORKS | 23 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 23 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Heart Attack Detection by Heart Rate Monitoring Using Iot Techniques
IoT innovation captures and delivers information in the cloud, enabling faster and more accurate handling, storage, and auditing of information flows. Healthcare organization is one of the most encouraging applications of data innovation. The ECG signal reflects the action of the heart and assumes a fundamental role in the discovery of cardiovascular problems. This exploration work proposes an IoT execution of pulse identification, ECG signal pre…
A Systematic Analysis of Current Developments and Potential Challenges in Applied Deep Learning-Based Seed Yield Prediction
Seed yield prediction is crucial in modern agriculture, aiding farmers and stakeholders in making informed decisions regarding crop management, resource allocation, and harvest planning. Traditionally, seed yield prediction relied on empirical models and historical data, which often lacked accuracy and robustness, particularly in dynamic agricultural environments. However, with the advent of deep learning (DL) techniques, there has been a paradig…
Ai for Sustainable Development
Artificial intelligence (AI) has become universal across various sectors, permeating every aspect of our lives regardless of age or profession. In this era of AI, it's necessary to prioritize sustainable development and innovation in its application. While AI enables rapid completion of tasks alike human efficiency, it also raises concerns about increasing unemployment rates. However, AI serves as a powerful tool for decoding the universe, emphas…
A Machine Learning Approach for Predictive Analysis of Traffic Flow
Traffic congestion is a critical issue affecting urban areas globally, leading to significant economic and social costs. Predictive traffic flow analysis has emerged as a promising solution to mitigate congestion and enhance transportation efficiency. This paper proposes a machine learning approach for predictive analysis of traffic flow, leveraging the wealth of available data from various sources such as traffic sensors, GPS devices, and traffi…
Exploring the Interplay Between Communication Complexity and Network Density in PDNS
This research investigates the features of a PDN interconnection network for Parallel and Distributed architecture. PDN is a novel and evolving architecture for parallel and distributed systems. It is an extremely effective method of joining a group of nodes into a network with a diameter equal to 2. At a distance of one or two nodes are joined together. A Perfect Difference Set is a mathematical technique for estimating the improved number of no…
Secure Dicom Image Communication
The envisioned system addresses the multifaceted challenges in DICOM image communication by implementing sophisticated digital watermarking algorithms that are resilient against advanced deep learning attacks, ensuring data integrity and bolstering security in healthcare imaging systems. By harmonizing the balance between data protection and patient privacy within legal frameworks, and using privacy-preserving methods, the system adheres to compl…
Pram-Based Algorithm for Perfect Difference Network Analysis
Perfect Difference Networks (PDNs) are fundamental in various computational tasks, particularly in areas like signal processing, image processing, and cryptography. Analyzing PDNs efficiently is essential for optimizing their performance. In this paper, we present a Parallel Random-Access Machine (PRAM) algorithm specifically designed for PDN analysis. The proposed algorithm leverages parallel computing capabilities to expedite the analysis proce…
Door Security System for Home Monitoring Based on Iot
The smart door lock system Using IoT is an innovative solution that combines the power of Internet of Things (IoT) technology with traditional door locking mechanisms to enhance security, convenience, and control. This system employs smart devices, sensors, and a cloud-based platform to create an intelligent and responsive door access management system. The core components of the smart door lock system include a smart door lock device, IoT-enable…
Genetic Algorithm vs Ant Colony Optimization for Offloading in Mobile Augmented Reality
This study presents a comparative analysis of two prominent optimization techniques, Genetic Algorithm (GA) and Ant Colony Optimization (ACO), for offloading tasks in Mobile Augmented Reality (MAR) environments. MAR applications often require intensive computational resources, leading to performance bottlenecks on resource-constrained mobile devices. Offloading tasks to remote servers can alleviate these constraints, but the selection of appropri…
Effects of Stratified Cross-Validation and Hyperparameter Tuning on Sentiment Classification With the Chi2-Rfe Hybrid Feature Selection Technique in the Imdb Dataset
Data analysis from social networking sites provides government entities, businesses, and event planners with insights into public sentiments and perceptions. Sentiment analysis (SA) resolves this need by classifying the sentiment of social network users into multiple classes. Despite their usefulness, data from social networking platforms frequently exhibits challenges, including unstructured formats, high volume, and redundant or irrelevant info…
Enhancing Reliability and Efficiency of Detecting Malicious Data Injection in Wireless Sensor Networks
Wireless sensor networks (WSNs) have gained significant attention in recent years due to their versatile applications ranging from wildlife tracking to environmental monitoring. However, WSNs are susceptible to various challenges such as hardware failures, communication link faults, and malicious attacks, which can significantly affect their reliability and performance. In this paper, we focus on the issue of malicious data injection in WSNs and …
Advances in Computer Vision
Computer vision, a rapidly evolving field at the intersection of computer science and artificial intelligence, has witnessed unprecedented growth in recent years. This comprehensive review paper provides an overview of the advancements and challenges in computer vision, synthesizing the latest research findings, methodologies, and applications. We explore the historical evolution of computer vision and discuss recent advancements in algorithms an…
Examining the Influence of Iot on Wireless Sensor Networks
We are in the world of the Internet and the Internet makes tasks easier. It is observed that IoT exerts a major effect on wireless systems. Multiple sectors are using the IoT based on wireless systems. IoT and WSNs are working jointly and making the way easier than easy. Now we are not only communicating person to person via a device all over the world but drastic technology which comes and it has simply made life easier, which is IoT (Internet o…
Enhanced Ai Security With DWT Watermarking and Hybrid Anomaly Detection Framework (Hadf)
This paper presents a novel approach to enhancing security in artificial intelligence systems through the fusion of Discrete Wavelet Transform (DWT)--based watermarking with a Hybrid Anomaly Detection Framework (HADF). Traditional watermarking techniques often struggle to withstand various attacks in digital environments, especially in the context of AI systems where the stakes are high. In response, the proposed framework combines the robustness…
Impact of Machine Learning-Based Routing Protocols for Efficient Data Transmission in Wireless Sensor Networks (Wsns)
Wireless Sensor Networks (WSNs) play a pivotal role in collecting and disseminating data in various applications, ranging from environmental monitoring to healthcare. The efficiency of data transmission in WSNs greatly depends on the routing protocols employed. In recent years, machine learning techniques have emerged as promising tools to enhance the performance of routing protocols in WSNs.This review paper aims to provide a thorough examinatio…
The Role of Deep Learning in Exploring Traffic Prediction Techniques
This research paper delves into the pivotal role of deep learning in advancing traffic prediction techniques. With urban traffic management becoming increasingly intricate, accurate short-term traffic prediction remains a cornerstone for effective congestion mitigation and transportation planning. Leveraging the capabilities of deep learning methodologies, this study systematically explores various deep learning models and their applications in p…
Analyzing Machine Learning Methods to Enhance Grain Quality Assessment and Evolution
Assessing grain quality is a crucial component of agricultural production, with significant implications for global food security and economic prosperity. With the increasing demand for top-tier grains, there arises a pressing need for sophisticated methodologies to aid in the ongoing assessment and monitoring of grain quality throughout its development. This paper offers a comprehensive examination of machine learning (ML) techniques utilized in…
Optimizing Crop Yield and Fertility Management Using KNN and Ml
Agricultural productivity and sustainability are critical concerns in modern farming practices. This study explores the application of machine learning algorithms, specifically K-Nearest Neighbors (KNN) and boosting, for optimizing crop yield and fertilizer management. By leveraging historical data on crop characteristics, soil properties, weather conditions, and fertilizer application, predictive models are developed to recommend crop varieties …
Performance Analysis of Activation Functions in Neural Networks
Activation functions are pivotal components in neural networks, serving as decision-making units that evaluate the output of network nodes, thus influencing overall performance. Selecting the appropriate activation function is crucial for neural network effectiveness. While various activation functions exist, not all are suitable for every scenario; some may be deprecated due to operational limitations. Characteristics like monotonicity, derivati…
Exploring the Transformative Impact of Artificial Intelligence on Higher Education
This paper presents a complete examination of the job of AI in advanced education, planning to give bits of knowledge into its applications, advantages, difficulties, and future bearings. Drawing upon hypothetical structures and exact proof, the paper investigates how AI is reforming academic practices through customized learning and draws near clever coaching frameworks and versatile guidance. It additionally examines the manners by which AI-dri…
Improving Security of Iot Device Communication Using Modified Hashing Solution
Advancements in technology have led to the invention of outfits, and the number of devices is increasing every day. Diligence is introducing new devices day by day and prognosticating that 50 billion devices will be connected by 2022. These devices are stationed through the Internet, called the Internet of Things (IoT). The operation of IoT devices is weather prediction, covering surgery in hospitals, identification of creatures using biochips, f…
Implementing Token-Based Authentication and Modified Hashing for Iot Security
“Internet of Things” mainly refers to the information exchange between objects or devices through the Internet. It is an innovative technology based on advanced network information technologies such as computer technology and Internet technology and is also one of the main directions for the development and application of network information technology. The emergence and operation of the Internet of Things technology will greatly promote the enha…
Enhancing Medical Image Security Through RGB and Yuv Color Based Advanced Triple Watermarking Techniques
This paper delves into the exploration and evaluation of diverse triple watermarking embedding techniques specifically tailored for medical imaging. In the healthcare sector, where the confidentiality and integrity of medical images are paramount, implementing robust security measures without compromising image quality is crucial. The study focuses on triple watermarking methods that incorporate three layers of security, aiming to enhance the pro…
No prominent works on this page.
Heart Attack Detection by Heart Rate Monitoring Using Iot Techniques
IoT innovation captures and delivers information in the cloud, enabling faster and more accurate handling, storage, and auditing of information flows. Healthcare organization is one of the most encouraging applications of data innovation. The ECG signal reflects the action of the heart and assumes a fundamental role in the discovery of cardiovascular problems. This exploration work proposes an IoT execution of pulse identification, ECG signal pre…
A Systematic Analysis of Current Developments and Potential Challenges in Applied Deep Learning-Based Seed Yield Prediction
Seed yield prediction is crucial in modern agriculture, aiding farmers and stakeholders in making informed decisions regarding crop management, resource allocation, and harvest planning. Traditionally, seed yield prediction relied on empirical models and historical data, which often lacked accuracy and robustness, particularly in dynamic agricultural environments. However, with the advent of deep learning (DL) techniques, there has been a paradig…
Ai for Sustainable Development
Artificial intelligence (AI) has become universal across various sectors, permeating every aspect of our lives regardless of age or profession. In this era of AI, it's necessary to prioritize sustainable development and innovation in its application. While AI enables rapid completion of tasks alike human efficiency, it also raises concerns about increasing unemployment rates. However, AI serves as a powerful tool for decoding the universe, emphas…
A Machine Learning Approach for Predictive Analysis of Traffic Flow
Traffic congestion is a critical issue affecting urban areas globally, leading to significant economic and social costs. Predictive traffic flow analysis has emerged as a promising solution to mitigate congestion and enhance transportation efficiency. This paper proposes a machine learning approach for predictive analysis of traffic flow, leveraging the wealth of available data from various sources such as traffic sensors, GPS devices, and traffi…
Exploring the Interplay Between Communication Complexity and Network Density in PDNS
This research investigates the features of a PDN interconnection network for Parallel and Distributed architecture. PDN is a novel and evolving architecture for parallel and distributed systems. It is an extremely effective method of joining a group of nodes into a network with a diameter equal to 2. At a distance of one or two nodes are joined together. A Perfect Difference Set is a mathematical technique for estimating the improved number of no…
Secure Dicom Image Communication
The envisioned system addresses the multifaceted challenges in DICOM image communication by implementing sophisticated digital watermarking algorithms that are resilient against advanced deep learning attacks, ensuring data integrity and bolstering security in healthcare imaging systems. By harmonizing the balance between data protection and patient privacy within legal frameworks, and using privacy-preserving methods, the system adheres to compl…
Pram-Based Algorithm for Perfect Difference Network Analysis
Perfect Difference Networks (PDNs) are fundamental in various computational tasks, particularly in areas like signal processing, image processing, and cryptography. Analyzing PDNs efficiently is essential for optimizing their performance. In this paper, we present a Parallel Random-Access Machine (PRAM) algorithm specifically designed for PDN analysis. The proposed algorithm leverages parallel computing capabilities to expedite the analysis proce…
Door Security System for Home Monitoring Based on Iot
The smart door lock system Using IoT is an innovative solution that combines the power of Internet of Things (IoT) technology with traditional door locking mechanisms to enhance security, convenience, and control. This system employs smart devices, sensors, and a cloud-based platform to create an intelligent and responsive door access management system. The core components of the smart door lock system include a smart door lock device, IoT-enable…
Genetic Algorithm vs Ant Colony Optimization for Offloading in Mobile Augmented Reality
This study presents a comparative analysis of two prominent optimization techniques, Genetic Algorithm (GA) and Ant Colony Optimization (ACO), for offloading tasks in Mobile Augmented Reality (MAR) environments. MAR applications often require intensive computational resources, leading to performance bottlenecks on resource-constrained mobile devices. Offloading tasks to remote servers can alleviate these constraints, but the selection of appropri…
Effects of Stratified Cross-Validation and Hyperparameter Tuning on Sentiment Classification With the Chi2-Rfe Hybrid Feature Selection Technique in the Imdb Dataset
Data analysis from social networking sites provides government entities, businesses, and event planners with insights into public sentiments and perceptions. Sentiment analysis (SA) resolves this need by classifying the sentiment of social network users into multiple classes. Despite their usefulness, data from social networking platforms frequently exhibits challenges, including unstructured formats, high volume, and redundant or irrelevant info…
Enhancing Reliability and Efficiency of Detecting Malicious Data Injection in Wireless Sensor Networks
Wireless sensor networks (WSNs) have gained significant attention in recent years due to their versatile applications ranging from wildlife tracking to environmental monitoring. However, WSNs are susceptible to various challenges such as hardware failures, communication link faults, and malicious attacks, which can significantly affect their reliability and performance. In this paper, we focus on the issue of malicious data injection in WSNs and …
Advances in Computer Vision
Computer vision, a rapidly evolving field at the intersection of computer science and artificial intelligence, has witnessed unprecedented growth in recent years. This comprehensive review paper provides an overview of the advancements and challenges in computer vision, synthesizing the latest research findings, methodologies, and applications. We explore the historical evolution of computer vision and discuss recent advancements in algorithms an…
Examining the Influence of Iot on Wireless Sensor Networks
We are in the world of the Internet and the Internet makes tasks easier. It is observed that IoT exerts a major effect on wireless systems. Multiple sectors are using the IoT based on wireless systems. IoT and WSNs are working jointly and making the way easier than easy. Now we are not only communicating person to person via a device all over the world but drastic technology which comes and it has simply made life easier, which is IoT (Internet o…
Enhanced Ai Security With DWT Watermarking and Hybrid Anomaly Detection Framework (Hadf)
This paper presents a novel approach to enhancing security in artificial intelligence systems through the fusion of Discrete Wavelet Transform (DWT)--based watermarking with a Hybrid Anomaly Detection Framework (HADF). Traditional watermarking techniques often struggle to withstand various attacks in digital environments, especially in the context of AI systems where the stakes are high. In response, the proposed framework combines the robustness…
Impact of Machine Learning-Based Routing Protocols for Efficient Data Transmission in Wireless Sensor Networks (Wsns)
Wireless Sensor Networks (WSNs) play a pivotal role in collecting and disseminating data in various applications, ranging from environmental monitoring to healthcare. The efficiency of data transmission in WSNs greatly depends on the routing protocols employed. In recent years, machine learning techniques have emerged as promising tools to enhance the performance of routing protocols in WSNs.This review paper aims to provide a thorough examinatio…
The Role of Deep Learning in Exploring Traffic Prediction Techniques
This research paper delves into the pivotal role of deep learning in advancing traffic prediction techniques. With urban traffic management becoming increasingly intricate, accurate short-term traffic prediction remains a cornerstone for effective congestion mitigation and transportation planning. Leveraging the capabilities of deep learning methodologies, this study systematically explores various deep learning models and their applications in p…
Analyzing Machine Learning Methods to Enhance Grain Quality Assessment and Evolution
Assessing grain quality is a crucial component of agricultural production, with significant implications for global food security and economic prosperity. With the increasing demand for top-tier grains, there arises a pressing need for sophisticated methodologies to aid in the ongoing assessment and monitoring of grain quality throughout its development. This paper offers a comprehensive examination of machine learning (ML) techniques utilized in…
Optimizing Crop Yield and Fertility Management Using KNN and Ml
Agricultural productivity and sustainability are critical concerns in modern farming practices. This study explores the application of machine learning algorithms, specifically K-Nearest Neighbors (KNN) and boosting, for optimizing crop yield and fertilizer management. By leveraging historical data on crop characteristics, soil properties, weather conditions, and fertilizer application, predictive models are developed to recommend crop varieties …
Performance Analysis of Activation Functions in Neural Networks
Activation functions are pivotal components in neural networks, serving as decision-making units that evaluate the output of network nodes, thus influencing overall performance. Selecting the appropriate activation function is crucial for neural network effectiveness. While various activation functions exist, not all are suitable for every scenario; some may be deprecated due to operational limitations. Characteristics like monotonicity, derivati…
Exploring the Transformative Impact of Artificial Intelligence on Higher Education
This paper presents a complete examination of the job of AI in advanced education, planning to give bits of knowledge into its applications, advantages, difficulties, and future bearings. Drawing upon hypothetical structures and exact proof, the paper investigates how AI is reforming academic practices through customized learning and draws near clever coaching frameworks and versatile guidance. It additionally examines the manners by which AI-dri…
Improving Security of Iot Device Communication Using Modified Hashing Solution
Advancements in technology have led to the invention of outfits, and the number of devices is increasing every day. Diligence is introducing new devices day by day and prognosticating that 50 billion devices will be connected by 2022. These devices are stationed through the Internet, called the Internet of Things (IoT). The operation of IoT devices is weather prediction, covering surgery in hospitals, identification of creatures using biochips, f…
Implementing Token-Based Authentication and Modified Hashing for Iot Security
“Internet of Things” mainly refers to the information exchange between objects or devices through the Internet. It is an innovative technology based on advanced network information technologies such as computer technology and Internet technology and is also one of the main directions for the development and application of network information technology. The emergence and operation of the Internet of Things technology will greatly promote the enha…
Enhancing Medical Image Security Through RGB and Yuv Color Based Advanced Triple Watermarking Techniques
This paper delves into the exploration and evaluation of diverse triple watermarking embedding techniques specifically tailored for medical imaging. In the healthcare sector, where the confidentiality and integrity of medical images are paramount, implementing robust security measures without compromising image quality is crucial. The study focuses on triple watermarking methods that incorporate three layers of security, aiming to enhance the pro…
Computer Science (22 works) · Artificial Intelligence (11 works) · Computer security (8 works) · Engineering (6 works) · Machine learning (6 works) · Internet of Things (5 works) · Advanced Steganography and Watermarking Techniques (4 works) · Computer network (4 works) · Energy Efficient Wireless Sensor Networks (4 works) · Telecommunications (4 works)