ISSN: 2582 - 9734
Mr. Himanshu Kumar Sharma, Deepanshu Agarwal
CrossRef DOI URL : https://doi.org/10.31426/ijesti.2026.6.9.6711
Artificial Intelligence (AI) has emerged as an important technological force in modern asset and portfolio management. The growing availability of financial data, improvement in computational capabilities, and development of machine learning, deep learning, natural language processing, and reinforcement learning have created new opportunities for investment analysis and portfolio decision-making. AI-based systems can process large volumes of structured and unstructured information, identify complex relationships among financial variables, forecast market movements, evaluate investment risks, and dynamically adjust asset allocations. Recent research indicates that AI is influencing not only portfolio optimization but also market forecasting, risk assessment, robo-advisory services, investment research, compliance, and strategic decision-making. .
AI and IoT Enabled Smart Irrigation Using Arduino
Surbhi Kumari, Chhoti Kumari, Dr. Bibek Kumar Sonu
CrossRef DOI URL : https://doi.org/10.31426/ijesti.2026.6.9.6712
Efficient irrigation requires timely information about changing field conditions. This paper develops a low-cost smart-irrigation framework that combines an Arduino Uno, a digital temperature–humidity sensor, Internet of Things communication, simple artificial-intelligence methods, and protected relay control. The study follows a design-and-evaluate approach at Ratu Road, Ranchi. Its analytical structure contains 210 time-stamped records, comprising 30 observations per day for seven days. Data quality, overall and day-wise descriptive statistics, environmental demand classes, and functional tests are examined. The illustrative dataset was complete, with an overall mean temperature of 29.81 °C (SD = 1.83) and mean relative humidity of 64.29% (SD = 7.17). Day 4 was warmest (30.91 °C) and least humid (58.90%), while Day 1 was coolest (28.66 °C) and most humid (68.39%). The irrigation-support distribution contained 64 low-, 72 moderate-, and 74 high-demand records..
Prof. Manju Sharma, Ashish Mishra
CrossRef DOI URL : https://doi.org/10.31426/ijesti.2026.6.9.6713
This research investigates the role of organisational climate in shaping teacher effectiveness within educational institutions. Organisational climate, defined as the shared perceptions and attitudes of the workplace, was measured alongside teacher effectiveness indicators such as instructional planning, classroom management, and student engagement. Results demonstrated a strong positive correlation between supportive organisational climates and higher teacher performance. Regression analysis identified leadership support, communication openness, and recognition of contributions as the strongest predictors of teacher effectiveness. The study concludes that organisational climate is a central determinant of educational quality, emphasizing the need for participatory leadership..
Prof. Dr. Preeti Sharma, Vinita Motwani
CrossRef DOI URL : https://doi.org/10.31426/ijesti.2026.6.9.6714
The goal of this research is to investigate how sustainable fashion relates to women's socio-economic empowerment within an Indian context, emphasising the need for an integrated, inclusive approach to solving environmental and social problems. The fashion industry is considered a significant contributor to economic growth as well as providing much-needed employment, especially for women; however, the structures in which it operates often prevent equitable participation and empowerment from being achieved. The objectives of the research are to critically assess how sustainable fashion contributes to women's empowerment and to create an Integrated Empowerment-Driven Circular Fashion Model (IEDCFM) to link sustainability, education and economic participation through women-led initiatives..
2026
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