All of the articles in this proceedings volume have been presented at the SASI-ITE 2025 during September 26–27 in Sasi Institute of Technology & Engineering, Tadepalligudem. These articles have been peer reviewed by the members of the Technical Committee and approved by the Editor-in-Chief, who affirms...

All living things need water, a basic and accessible element. Humans benefit much from groundwater. In the preceding years, landfills, factories, and non-point sources including fertilizer and pesticides impacted groundwater levels. It's crucial to analyze the water's quality for current and...

Rising network complexity in next-generation systems underscores the shortcomings of traditional optimization methods in both modeling and algorithms. This paper introduces a digital twin for mobile network (DTMN) architecture tailored for 6G networks. To overcome the limitations of traditional optimization...

Multi - level inverters (MLIs) have emerged as a vital component in modern power electronics, offering superior performance in medium and high-power applications such as electric vehicles, renewable energy systems, and industrial drives. By synthesizing a staircase waveform from multiple voltage levels,...

Quantifying greenery from an individual’s perspective is important due to its role in enhancing emotional well-being and reducing stress. While Google Street View (GSV) imagery has been widely used for street-level greenery assessments, its limited availability in many regions constrains such analysis....

Distributed Systems play an essential role in enabling real-time decision-making in Internet of Things (IoT) applications. However, maintaining strong data privacy while achieving high performance remains a persistent challenge. Traditional approaches, such as Federated Learning (FL) and Differential...

Noise pollution during Diwali festivities in India has emerged as a serious concern, affecting public health and the environment. This study proposes an AI-driven framework that integrates deep learning, reinforcement learning, and geospatial analysis to forecast and optimize noise levels during Diwali....

The rising frequency and sophistication of cyber threats in India’s cyberspace demand a robust real-time threat intelligence system for early detection, analysis, and mitigation. Traditional cyber security measures fall short due to fragmented data sources and limited adaptive threat detection. This...

This research proposes the design of an AI-powered online chess system that combines classical search algorithms with modern machine learning techniques to create an adaptive and intelligent gameplay environment. The model integrates the Minimax algorithm with Alpha-Beta pruning, reinforcement learning,...

This report explores the dynamics of customer conversion by examining the relationship between visit behaviour and conversion outcomes across various marketing channels. By condensing customer visit data into a singular representation for each customer, we capture the time intervals from their first...

This study investigates Land Use Land Cover (LULC) dynamics in ecologically sensitive Akole tehsil of Ahmednagar district over the past two decades (2001–2021) and predicts future scenarios for 2031 and 2041. Multi-temporal Landsat imagery (Landsat-5 and Landsat-8) acquired in February was classified...

Brain tumors represent one of the most critical challenges in medical diagnosis due to their high mortality rate and complex structure, and early and accurate detection is essential to improve treatment outcomes and survival rates. However, brain tumor detection and classification from MRI images remain...

This paper introduces a new benchmarking framework, “DataBench360,” created to evaluate the abilities of Large Language Models (LLMs) in solving practical data science problems. Unlike earlier benchmarks that focus only on narrow or simplified measures, DataBench360 uses a structured process to build...

The rapid advancement of data analytics has revolutionized the tourism and hospitality sectors, transforming them from labor- intensive models into insight-driven industries. While existing research emphasizes the influence of large-scale data analysis on general tourism trends, its role in addressing...

The accumulation of environmental soiling, such as dust and grime, is a primary factor in the performance degradation of solar panels, leading to efficiency losses exceeding 25% and significantly curtailing energy output. Manual cleaning methods, while common, are labor-intensive, pose substantial safety...

The aspect of sustainability of the spiritual destinations cannot be over emphasized in an attempt to sustain cultural heritage as well as the long-term amenities leading to the sustained social economic benefits to the local communities. This study attempts to study and explain the key issues affecting...

Generative Adversarial Networks (GANs) are now very powerful technologies in the cloud computing domain to fight major anomalies in detection, resource scheduling, cybersecurity, and privacy-preserving data generation. Recent research indicates a growing trend from simple GAN architectures toward sophisticated...

Deep Learning is a tool and it is utilized for to detect and categorize the images. Discovering diseases and taking measures to assist with human health is very advantageous. Unpredictable diseases are common these days. Diseases detectable from visible facial features can also help to curb further advancement...

Electric vehicle (EV) power trains need to interface low-voltage, high-current energy sources like fuel cells or batteries with high-voltage, low-current motors in an efficient manner. Especially when boosting or bucking is high, conventional single-stage, single-arm DC/DC converters frequently suffer...

Hematopoietic Cell Transplantation (HCT) is a critical therapy for hematologic disorders, yet post-transplant survival prediction remains complex due to heterogeneous clinical and genetic factors. This study presents a machine learning–driven framework that integrates Kaplan–Meier survival estimation...

Synthetic azo dyes, such as Acid Violet 7 (AV7), are highly stable in industrial effluents and therefore pose significant environmental challenges for their removal. This study investigates a hybrid process that combines hydrodynamic cavitation (HC) with activated carbon (AC) adsorption to degrade AV7...

D.A.E.M.O.N (Dynamic Assistant for Efficient Multiple and Oral Navigation) is a modular, Python-based, voice-driven assistant designed for efficient, context-aware interaction with digital systems. The framework integrates speech recognition, natural language understanding, system-level automation, and...

The use of artificial intelligence in military surveillance has become essential in the rapidly changing field of modern warfare in order to improve real-time object detection in challenging aerial situations. The hybrid architecture presented in this study combines the global contextual awareness of...

This paper discusses the ways in which Environmental, and Social, Governance (ESG) practices can be effectively incorporated to produce both long-term competitive advantage and sustainable development. The study is based on the dynamic capabilities theory and focuses on the impact of absorptive and adaptive...

The demand for faster and energy- efficient arithmetic circuits continues to grow with the rise of modern VLSI applications. This paper explores a 4- bit Ladner-Fischer Parallel Prefix Adder (LF-PPA) implemented using non- conventional logic techniques such as Pass Transistor Logic (PTL), Double Pass...

Diabetic Retinopathy (DR) is one of the leading causes of preventable blindness worldwide, and early detection with precise severity classification is critical to reduce vision loss. Retinal fundus imaging is the most widely used modality for DR screening, but manual diagnosis is time-consuming, subjective,...

With the emergence of AI models like GPT, Deep Fake technologies, differentiating AI and human written text is increasingly complex. These models can produce highly realistic and consistent content that is difficult to detect, creating a growing demand for effective AI versus Human Text Authenticity...

Reinforcement Learning (RL) has emerged as a promising paradigm for process automation, yet its experimental validation with human operators in real-time control scenarios remains limited. This work presents a human-in-the-loop case study that evaluates the performance and usability of an RL based controller...

Geographically, the Ethiopian climate is quite diverse, due to its equatorial positioning and varied topography. The country’s climate traditionally classified into five zones from high cold area to highly hot climate zones based on the altitude and temperature variation. Hot desert regions, like Fentale...

The peer-to-peer (P2P) lending model has emerged as a transformative alternative to traditional financial institutions, enabling direct interactions between lenders and borrowers. However, P2P lending platforms face significant challenges, including trust deficits, fraud, high administrative costs, and...

Mobile Edge Computing (MEC) brings cloud-like capabilities closer to end users, enabling low-latency and high-efficiency processing for applications like autonomous vehicles, virtual reality, and smart healthcare. A core challenge in MEC is adaptive computation offloading, deciding whether tasks should...

Wi-Fi sensing for Human Activity Detection (HAD) provides a non-intrusive, privacy-preserving approach for monitoring human activity in indoor environments. This paper presents a real-time human activity detection framework based on Channel State Information (CSI) acquired from an ESP-32 embedded development...

BCC is among the most prevalent skin cancers, making timely diagnosis essential for effective treatment and tissue preservation. This study introduces a deep learning method for automatically classifying dermoscopic images as either BCC or healthy, utilizing a modified RepVGG-A0 network combined with...

This study conducts a scientometric analysis of global research on Robotics and Automation for Sustainable Manufacturing covering the period 2000–2024. Data were extracted from the Scopus database and analyzed using RStudio with Biblioshiny and VOSviewer to identify publication trends, citation patterns,...

The intersection of sustainable finance and artificial intelligence (AI) offers revolutionary opportunities for redesigning green financial systems. Conventional financial models have a tendency to miss the dynamic, systemic, and climate-related risks involved in sustainable investments, and uneven ESG...

In the current agricultural environment, the prompt and accurate identification of crop diseases is essential for safeguarding food security and sustaining lucrative farming methods. Conventional approaches that depend solely on observation or a singular data source frequently inadequately encompass...

In order to improve water quality and encourage sustainable water usage, this study provides the design, development, and performance assessment of a unique water filtration system. In order to provide safe and clean water for household and communal uses, the designed device has an effective filtration...

Land Surface Temperature (LST) is a key parameter for studying relationship between land and atmosphere, urban heat island and biophysical processes. This study analyses the spatial variability of LST in Odisha, India, employing remote sensing indices and modern spatial regression models. Five different...

This study addresses sustainable hemp fiber/epoxy composites with and without fillers—carbon powder (Cp) and groundnut shell powder (GNSP)—as eco-friendly alternatives to synthetic materials for high-temperature applications. According to the experimental results, hemp + GNSP + epoxy had the maximum...

The groundwater quality in coastal regions is significantly threatened by changing climate conditions. The purpose of this investigation is to quantify the pollution level of groundwater quality by analysing physicochemical characteristics of twenty water samples along the coastal tract of Odisha. Considering...

Unseasonal rains in India often damage harvested grains, causing substantial losses for farmers. Grains awaiting transport to rice mills for dehusking and bagging are especially vulnerable when exposed to heavy rains after harvest. To mitigate this problem, a mechanical system was developed to reduce...