All of the articles in this proceedings volume have been presented at the [ICDLAIR 2024] during [December 6-8, 2024] in [NIT kurukshetra]. These articles have been peer reviewed by the members of the [Technical and Scientific Committee] and approved by the Editor-in-Chief, who affirms that this document...

Natural-sounding speech synthesis systems with end-to-end models have been designed for Spanish, American English, and Chinese. However, little work has been done on the end-to-end text-to-speech synthesis development for the Indian languages. The lack of good training data has been a challenge of this...

Breast cancer is a commonly seen illness in women and is the primary reason for cancer-related deaths among women. The early detection of cancerous tissue will aid in recovery and treatment of it and can save more lives. The detection of breast cancer is challenging using mammography, as dense tissues...

As Low Earth Orbit satellites play a vital role in the 6G space network, the risk caused by space debris has become increasingly significant. This paper presents a comprehensive risk prediction model for LEO satellites to enhance the safety and reliability of satellite communication systems. We introduce...

Among the various threats converging on the world of cryptocurrencies, the phishing attacks presented are among the most threatening ones within Ethereum. This paper introduces an innovative ensemble-based framework that enhances the detection of phishing attacks within Ethereum and mitigates against...

Android’s popularity as an operating system stems from its extensive benefits; however, this has also made it a primary target for malware, which now exists in various categories. Numerous approaches leveraging static and dynamic analysis have been proposed for malware detection, though static analysis...

Sugarcane is a vital crop in global agriculture, yet it is highly susceptible to diseases that can drastically affect crop productivity and disrupt agricultural planning. Traditional methods for identifying and diagnosing diseases in sugarcane leaves rely heavily on manual inspections, which are labor-intensive,...

Adversarial attacks affect the performance of NIDS as attackers subtly modify inputs to bypass detection in traditional machine learning models. Ensuring adversarial robustness is essential for maintaining reliable detection under such conditions. Explainable AI (XAI) provides transparent insights into...

Medicinal plants play a crucial role in healthcare, but various diseases often threaten their cultivation. Early and accurate diagnosis of plant diseases is essential for maintaining plant health and ensuring sustainable production. Deep learning has emerged as a powerful tool for automated image-based...

Introducing ingestible sensors and smart pills to patients creates a kind of breakthrough in how doctors and caretakers can track patients’ compliance and gather health information. This paper aims at examining the effectiveness and application of these technologies in boosting the level of patients’...

Recognizing crop diseases at an early stage is essential for modern agriculture because it greatly enhances crop output and decreases economic losses. Manual examination and specialized expertise are the backbone of traditional disease detection approaches, but they can be exhausting and error-prone....

The collaboration of multiple Cloud Providers (CPs) with the intent to share resources with each other and enhance resource availability to customers is termed as Cloud Federation. The collaboration of participating CPs is based on mutual agreements among them with all the terms and conditions of association...

The accelerated advancement of deepfake technology presents considerable challenges to the security of digital media, leading to serious concerns due to the potential for misleading information, manipulation, and malicious use. As deepfakes become increasingly advanced and realistic, the need for effective...

In recent years, the tea industry has gained newfound importance, driven by advancements in technological innovation and automation. These developments have played a pivotal role in boosting productivity and ensuring the quality of tea production. Within the field of tea agriculture, a crucial challenge...

Extensive research has been conducted in the field of text summarization, leading to significant advancements in various domains. However, scientific summarization, which entails capturing nuanced details such as mathematical equations, complex terminologies, and intricate symbols, remains largely underexplored....

This review explores how modern technology is transforming navigation for blind and visually impaired individuals, with a focus on tools that detect objects and measure distances. By harnessing advancements in imaging and machine learning, it becomes possible to turn visual data into useful feedback...

The Internet of Medical Things (IoMT) has revolutionized healthcare by enabling real-time data collection, monitoring, and analysis. However, the adoption of IoMT systems also introduces challenges related to data security, privacy, and scalability. Blockchain technology, with its decentralized and immutable...

Multi-face recognition remains an active area in deep learning domain, excelled by the need for enhanced security and efficiency in various applications. The motivation for proposing this automatic multi-face recognition system originates from the increasing demand for non-intrusive and reliable identification...

In modern fitness environments, accurate tracking of user activity and identification poses significant challenges due to the dynamic nature of gym settings. This project introduces an innovative system that uses RFID for entry/exit tracking and OSNet-based deep learning for robust, real-time re-identification...

This paper investigates the important need for more robust IoT security policies. It looks at the prospect that using machine learning methods to improve the accuracy and efficiency of IDS might help them The spread of linked devices makes protecting IoT settings from cyberattacks a priority. Our approach...

This paper focuses on the translation of Indian Sign Language (ISL) into text, to expand the range of people with whom individuals with hearing impairments can communicate. The proposed method for this utilizes Mediapipe Holistic for capturing hand gestures and Long Short-Term Memory or LSTM networks...

Online disinformation efforts employ memes, a highly popular kind of content. They get the most success on social media platforms due to their ability to easily access a large audience. As part of a disinformation campaign, memes use different types of rhetorical and psychological techniques, like slander,...

Deep Learning models are gaining widespread adoption and popularity across various realworld applications, including image recognition, speech recognition, self-driving cars, and critical infrastructure Systems. However, these models are found to be vulnerable to imperceptible adversarial perturbations...

Paddy cultivation is a cornerstone of agricultural production worldwide in India and many other rice-growing regions. Efficient management of paddy fields is essential for maximizing yield and assuring food security. Paddy leaf health is a critical indicator of the overall condition of rice crops, as...

With the advent of fast paced industrialization and rapid growth and urbanization, the grave issue of air pollution in urban areas, especially in industrial sectors and in developing countries is at an all-time high. Air pollution can have adverse effects on the health and well-being of humans. It can...

This study compares classical Machine Learning (ML) models Logistic Regression, Random Forest, and Support Vector Machine with a Hybrid Voting Classifier and an enhanced Deep Neural Network (DNN) for breast cancer classification using the Breast Cancer Wisconsin dataset. In comparison to conventional...

Watershed images are essential for environmental resource management, providing critical insights into hydrological and ecological systems. However, these images are vulnerable to unauthorized access, misuse, and copyright violations during digital transmission and storage. This paper presents a robust...

Software-defined networking (SDN) transforms modern networks by enabling programmability for dynamic service provisioning. However, SDN faces significant challenges due to the limited capacity of flow tables in OpenFlow (OF) switches, which are typically stored in Ternary Content Addressable Memory (TCAM)....

The objective of the project is to create an advanced decentralized voting application, using blockchain technology to deliver a secure, transparent, and tamper-proof voting system. By exploiting the immutable and decentralized properties of blockchain, the application seeks to improve the trustworthiness...