International Journal of Engineering and Management Research
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The Influence of Artificial Intelligence on Our Daily Lives
Full text linkArtificial Intelligence (AI) has rapidly transitioned from an abstract concept confined to academic and theoretical discussions into a pervasive and tangible force actively reshaping modern society. Once considered the domain of science fiction, AI technologies now penetrate nearly every facet of daily life, fundamentally altering how individuals communicate, learn, heal, travel, manage finances, and operate within their personal spaces. Innovations such as virtual assistants, automated healthcare diagnostics, intelligent transportation systems, personalized education platforms, and smart home devices exemplify AI\u27s profound and expanding role.
The influence of AI is not merely limited to enhancing existing processes; it actively redefines societal norms, expectations, and possibilities. Through sophisticated algorithms capable of learning from vast datasets, AI systems offer unprecedented levels of convenience, personalization, and operational efficiency. They automate routine tasks, provide predictive insights, and foster new forms of human-machine collaboration. For instance, AI-driven recommendation engines anticipate consumer preferences, while machine learning models in healthcare predict disease outbreaks and suggest personalized treatment plans.
However, alongside these benefits, AI integration introduces a range of complex ethical, social, and economic challenges. Issues such as data privacy violations, algorithmic bias, job displacement due to automation, and the erosion of human decision-making autonomy pose significant concerns that must be critically examined. As AI systems grow more autonomous and influential, the need for transparent, ethical governance structures becomes increasingly urgent to ensure that technological advancement aligns with broader human values and societal well-being.
This research aims to explore the breadth and depth of AI’s influence on daily human activities by examining both qualitative and quantitative dimensions. Real-world examples, case studies, and statistical data are used to illustrate the tangible impacts of AI across key sectors. Additionally, a visual model is presented to capture the interconnected nature of AI applications across communication, healthcare, education, transportation, finance, and domestic life. The study ultimately argues that while AI offers transformative potential, a balanced, ethically-informed approach to its development and deployment is crucial to harness its benefits responsibly
BMS For Self-Charging E-Vehicle
Full text linkThe growth of electric vehicles (EVs) has sparked creative methods for increasing battery life and improving energy efficiency. In this work, a Battery Management System (BMS) for self-charging electric vehicles (SCEVs) is presented. The suggested solution comprises of a BLDC or induction motor for propulsion attached to the back wheel while an alternator is attached to the front tire that produces power while the vehicle runs. A pole switch is used for smooth transitioning between the two battery packs A and B. This aims in providing continuous vehicle motion while the alternator\u27s activity charges the battery attached to the motor. The BMS is an essential part of this system since it not only stops overcharging but also uses active cell balancing technique during discharging and passive cell balancing technique during charging to maximize battery performance. This study demonstrates how well the suggested BMS works to extend the life SCEVs, providing a viable option for the development of EVs in the future
Students’ Perception of Digital Transformation in Higher Education: A Study on Learning, Employability and Adaptability
Full text linkThe digital transformation has advanced globally, reshaping how students learn, communicate and get ready for the workforce. This empirical study looks at students’ perception on digital transformation in higher education with special focus on learning, employability and adaptability. Employing a structured questionnaire, responses were collected from students of higher educational institutions. Descriptive statistics and correlation analysis are used to study the relationship between digital transformation and student development outcomes. Results show that digital transformation has a favourable impact on students’ educational experiences, increases their employability and improves their ability to adapt to changing surroundings. By emphasising the significance of digital education in creating a generation prepared for the future, the study advances the more general objectives of economic resilience, sustainable development and efficient educational governance
A Study on Innovation Strategies Adopted by Indian Startups and its Sustainability
Full text linkThe startup culture in the Nation is shaping up well and has a definite future. The prime success factor for startups is their Innovative practices. The innovation in businesses has the potential of guiding the organisations towards sustainability. Government initiatives such as Startup India, Atal Innovation Mission, Digital India, and FAME India have played a crucial role in nurturing innovation and sustainability among startups. Innovation strategies adopted by the startups often include digital transformation, data-driven decision-making, AI and automation integration, and the creation of customer-centric solutions. India now ranks among the world’s top startup ecosystems, with over 100 unicorns spanning diverse industries, many of which are driven by innovative and sustainable business practices.
The literature presented through this paper is descriptive study conducted by the help of secondary data. The authors primarily aim to study the innovation strategies adopted by Indian Startups. By examining real-world examples of Indian startups, this study intends to provide insights into how innovation and sustainability together act as dual engines of modern entrepreneurship in India. Ultimately, this research contributes to understanding how startups can balance the pursuit of innovation with sustainable growth, ensuring that technological advancement and social responsibility coexist harmoniously. The authors have presented a recommendation in the form of Seven key aspects that may enable organisations to be more sustainable in their business approach. The scope of the study revolves around domain of Innovation & Sustainability. The inferences gathered are indicative in Nature rather exhaustive
Production and Performance of Bio-Diesel from Pongamia Oil Methyl Ester
Full text linkDiesel engines are widely used for different applications in industrial power plant, transportation, agriculture etc. despite these advantages, environmental pollution, cost increment, depletion of crude oil becomes a major concern throughout the world. A methyl ester of pongamia was prepared and blended with diesel in four different compositions varying from 25% to 100%. Methyl esters of pongamia oils has several outstanding advantages among other new renewable and clean engine fuel alternatives and can be used in any diesel engine without modification. The engine performance and emission characteristics of pongamia bio-diesel (Pongamia Oil Methyl Ester) and its blends with petro-diesel are presented. The engine tests are conducted on a 4-Stroke Tangentially Vertical (TV1) single cylinder kirloskar engine, throughout the experiment under steady state conditions at full load condition. From the test results, it could be observed that the B25 blend gives optimum performance like higher brake thermal efficiency lower specific fuel consumption and lower emissions like lower in smoke density and oxides of nitrogen. The research findings show that B25 gives lowest emissions which make it a good alternative fuel to operate diesel locomotives without any modification in existing diesel engine
A Study on Change Management at Organisations
Full text linkChange management is a critical aspect of modern organizational strategy, aiming to facilitate smooth transitions and ensure sustained productivity and morale during periods of change. Change Management encompasses with the virtues of evaluating the current status, planning the transition of the momentum and leading to a coordinal future. Kurt Lewin through his Change Model Unfreeze – Change- Refreeze explains Change as a process & not an event. Change management is the process, tools and techniques to manage the people side of change to achieve the required business outcome. Change management incorporates the organizational tools that can be utilized to help individuals make successful personal transitions resulting in the adoption and realization of change. Change management is a structured approach to help organizations transition from their current state to a desired one.
This study explores the intricacies of change management within organizations, examining the strategies employed to manage change, the challenges encountered, and the outcomes achieved. A descriptive study, conducted by the help of the secondary data aims to study the strategies adopted towards Change Management by the Organizations. The study further aims to understand the significance of Change Management at Organizations. The authors also contribute a Model towards Change Management. Through a comprehensive review of literature, this paper identifies key factors that contribute to successful change management, including leadership, communication, employee involvement, and adaptability. The findings provide valuable insights for organizations seeking to navigate change effectively and underscore the importance of a structured approach to managing transitions. The inferences are indicative in nature
Fraudshield – Deepfake Detection Tools
Full text linkFraudShield is a web application designed to detect and mitigate the impact of deepfakes, ensuring content authenticity and integrity. With the rise of image manipulation and deepfake videos, detecting fraudulent activities has become increasingly critical. This project introduces a hybrid detection system that integrates Convolutional Neural Networks (CNNs) to identify morphed images and manipulated content. The framework leverages machine learning techniques to detect tampered facial features, artifacts, and inconsistencies in deepfake videos and images. The CNN component analyzes visual features such as texture inconsistencies and pixel anomalies to detect image morphing or tampering. FraudShield employs a multi-stage CNN pipeline that extracts spatial and temporal features from images and video frames, enhancing its ability to identify synthetic forgeries. The system is trained on large-scale datasets to improve robustness against adversarial deepfakes. By utilizing this approach, the model enhances detection accuracy while minimizing false positives and false negatives. The hybrid model strengthens online security by offering a comprehensive fraud detection solution. Its scalable architecture enables adaptation to emerging fraud patterns and new types of image manipulation. Ultimately, the dual-layered system provides a reliable and efficient tool for identifying image tampering, reinforcing digital security
Hybrid Deep Learning Approach for Classifying Anxiety and Stress in Adolescents through Speech and Text Data
Full text linkToday, adolescents are exposed to a multitude of challenges, caused both in part by academic competition, dismissal from peer pressure, social media divulgence, and the shifting picture of the family and the social surroundings that young people are familiar with. The stressors of these can turn them particularly vulnerable to psychological conditions such as anxiety and stress, and if not readily identified and treated in the long run could be severe mental long term health consequences. However, these traditional assessment methods are typically limited by subjectivity interpretation, social desirability bias, and scalability in real-life situations. To address these limitations, this study puts forward a novel hybrid deep learning framework which employs both Convolutional Neural Networks (CNN) and Bidirectional Long Short Term Memory (BiLSTM) networks for the purpose of detecting anxiety and stress levels in adolescents. Both emotional tone and linguistic patterns are captured by the system, processing multimodal inputs, from acoustic features extracted from speech and from semantic information, from transcribed text. To exploit spatial hierarchies saved in Mel-frequency cepstral coefficients (MFCCs) of speech signals, CNNs are employed. The dependencies in the textual data are modeled using BiLSTM layers. The model successfully combines these complementary representations to gain an overall view of the user’s mental state. Experimental evaluations on a labeled dataset of adolescent speech text pairs show better performance than baselines on using each modality separately. Results demonstrated that combined speech and text can be employed for reliable, automated mental health evaluation. Not only does this improve diagnostic accuracy but it also creates a real-time, scalable screening tool for early intervention and continuous mental well being monitoring in youth populations
Sustainable Construction: Optimization of Microbial Soil Stabilization for Enhanced Construction Materials
Full text linkMicrobially Induced Calcium Precipitation (MICP) has emerged as an effective and sustainable method for soil stabilization, utilizing microbial processes to enhance soil strength through calcium carbonate formation. This research explores the transformation of Mongu sand into a strong construction material using MICP, with a focus on optimizing urease activity, bacterial concentration, and cementation media. Given the scarcity of rock conglomerates in the region but the abundance of sand, this study provides innovative solutions to address this issue by improving and even transforming materials into more suitable forms for construction. MICP presents significant potential for infrastructure development in areas with limited access to conventional materials, with future efforts aimed at scaling the process for larger and more complex projects. The findings provide insights into the optimal parameters for material transformation, revealing that maintaining urease activity between 10-15 µmol urea hydrolyzed per minute per mg of protein and bacterial concentrations of 1.5 x 10⁸ CFU/mL results in a substantial improvement in compressive strength and durability—up to 475% higher than untreated sand. Additionally, the study underscores the effectiveness of Sporosarcina pasteurii in promoting calcium carbonate precipitation, further emphasizing MICP’s potential for soil stabilization and construction in resource-constrained regions
A Prediction of The Air Quality Index: An Analysis of Ghaziabad City
Full text linkPM10 is one of the main air pollutants that causes air pollution. This study used Artificial Neural Networks (ANN), a common learning technique, to estimate the impact of this contaminant on human health and the environment using data between 2019 and 2023. The Pollution Control Board of Uttar Pradesh (UPPCB)\u27S air observation center obtained information related to the center of industry of Ghaziabad and finished the simulation and optimization procedures required using SPSS programming. Before being compared with the real data, the obtained air quality estimation results underwent a multilayer perceptron analysis. Moreover, there have been instances where the Ghaziabad province\u27s Air Quality Index (AQI) values have exceeded the allowable limit, especially during times of great output