INTERNATIONAL JOURNAL OF MANAGEMENT RESEARCH AND REVIEW
ACCIDENT DETECTION WITH CCTV USING CONVOLUTIONAL
Accidents have been a major cause of deaths in India. From past decade surveillance cameras have been installed for security purposes on several roads and are still being installed, but those surveillance cameras aren’t being used to their fullest. Also, there isn’t enough of man power to survey each and every road, each and every surveillance video. More than 80% of accident-related deaths occur not due to the accident itself but the lack of timely help reaching the accident victims. The intent is to create a system which would detect an accident based on the live feed of video from a CCTV camera installed on a road. The idea is to take each frame of a video and run it through a deep learning convolution neural network model which has been trained to classify frames of a video into accident or nonaccident. Convolutional Neural Networks has proven to be a fast and accurate approach to classify images.
Convolutional Neural Network; Accident Detection; Deep Learning; Video Classification; Recurrent Neural Network
KUKKUNOORI SHIVARAM1 , GOGULA GOPINATH KATURU VIVEK KUMAR REDDY3, MATHANGI SAMRAJ4
Women's Entrepreneurship Around the World, with a Focus on India
Entrepreneurship – An Economic Transformation. Entrepreneurs are Born and Entrepreneurs are Made. Entrepreneur is an individual who has a vision and generates an action plan to accomplish it. Empowering the Global economy with Women Entrepreneurs have blasting quickly. As of now, the number of women entrepreneurs has phenomenal level of growth. This article deals with the Evolution of Women entrepreneurs, their rapid growth, challenges they face and different platforms encouraging women entrepreneurs at global level with respect to India
Skill Development among Women: Empowering Through Education
Today, empowering women through education and skill development is vital for sustainable growth. Women’s empowerment is linked to their ability to acquire relevant skills and knowledge that enhance their employability, independence, and participation in society. This paper examines how skill development can change women’s lives by exploring the relationship between education, vocational training, and empowerment, especially in developing countries. Education is the foundation for skill development. It provides women with basic literacy and math skills, while also building the confidence and awareness needed for active involvement in economic and civic life. However, many regions, especially rural and marginalized communities, face obstacles in accessing quality education and skill development programs due to social barriers, poverty, gender bias, and a lack of institutional support. This paper argues that closing this gap requires a broad approach that combines formal education with vocational and technical training. The Government of India and various international organizations have launched numerous projects such as the Skill India Mission, Pradhan Mantri Kaushal Vikas Yojana (PMKVY), Mahila E-Haat, and Deen Dayal Upadhyaya Grameen Kaushalya Yojana (DDU-GKY) to address gender disparities and promote women’s economic participation. These programs aim to provide skills that meet industry demands, helping women find jobs or start their own businesses. Additionally, NGOs and community-based programs play a crucial role in reaching women in remote and underserved areas. This paper uses secondary data and case studies to assess the effectiveness of skill development programs for women. It highlights how skill development not only increases income but also positively influences health, children’s education, decision-making abilities, and overall gender equality. Special attention is given to the significance of digital literacy, soft skills, financial literacy, and life skills in achieving complete empowerment. The findings suggest that when skill development is supported by inclusive policies, mentorship, and infrastructure that considers gender issues, it can greatly empower women. However, the paper also points out ongoing challenges such as low awareness, inadequate funding, drop-out rates, and mismatches between training and job market needs. In conclusion, the paper stresses the need for strategies that transform gender roles, foster stronger partnerships between public and private sectors, and create better monitoring frameworks to ensure the reach and sustainability of women-focused skill development programs. Empowering women through education and skill training is not just an objective for development; it is necessary for inclusive growth and fair progress.
Women Empowerment, Skill Development, Vocational Training, Gender Equality, Education
Cloud-Based Healthcare Risk Prediction And Cloud-Band Surgical Monitoring System Using Iot Devices
The combination of IoT devices and cloud technology has changed the healthcare ecosystem, especially in surgical environments, by providing real-time patient monitoring and risk prediction functionality. This research presents a Cloud-Based Healthcare Risk Prediction and Cloud-Band Surgical Monitoring System that combines advanced machine learning methods, cloud computing platforms, and IoT devices to monitor and predict risk levels for patients in real time. The system combines Decision Trees for classifying patient risk levels, and a Gradient Descent model-building process for optimizing model performance and accuracy levels. The paper highlights the system's contributions to surgical decision-making, patient safety, and resource allocation. Results demonstrate strong performance across the metrics of expected performance with an overall accuracy level of 93%. Challenges remain with data security and privacy; however, the proposed system provides a scalable and reliable intervention to predict patient risk and monitor surgical patients
cloud Computing, Health care, Decision Trees, Gradient Descent
उच्चतर माध्यममक छात्राओं का सशक्ततकरण: पटना, बिहार में एक अध्ययन
यह अध्ययन पटना , बिहार में उच्च माध्यममक छात्राओं के सशक्तिकरण को प्रभाविि करने िाले िहुआयामी कारकों की जांच करिा है। आठ स्कूलों की 320 महहला छात्रों (उम्र 16-18) के साथ ममश्रिि -पद्धति दृक्टटकोण का उपयोग करिे हुए , शोध सशक्तिकरण और चार पररकक्पपि तनधाारकों के िीच संिंधों की जांच करिा है: गुणित्तापूणा मशक्षा पहुंच , सामाक्जक आश्रथाक क्स्थति , सामाक्जक समथान नेटिका और पाठ्येिर भागीदारी। मात्रात्मक तनटकर्ा सशक्तिकरण और गुणित्तापूणा मशक्षा (आर =0.64, पी <0.001), सामाक्जक आश्रथाक क्स्थति (आर =0.48, पी <0.001), और सामाक्जक समथान नेटिका (आर =0.59, पी <0.001) के िीच महत्िपूणा सकारात्मक सहसंिंधों को प्रकट करिे हैं , क्जसमें पाररिाररक समथान विशेर् रूप से प्रभािशाली के रूप में उभर रहा है। जिकक समग्र पाठ्येिर भागीदारी ने ममश्रिि पररणाम हदखाए , नेिृत्ि -उन्मुख गतिविश्रधयों ने सशक्तिकरण के साथ मजिूि संिंध प्रदमशाि ककया (आर =0.57, पी <0.001)। मपटीपल ररग्रेशन विश्लेर्ण ने गुणित्तापूणा मशक्षा पहुंच , मािृ मशक्षा , पाररिाररक समथान और नेिृत्ि गतिविश्रध भागीदारी िाले एक मॉडल की पहचान की , क्जसने सशक्तिकरण स्कोर में 63% मभन्निा को समझाया। 40 साक्षात्कारों के गुणात्मक डेटा ने लड़ककयों की एजेंसी और आकांक्षाओं को विकमसि करने में मािृ मशक्षा , मशक्षक परामशा और महहला रोल मॉडल की महत्िपूणा भूममका पर प्रकाश डाला। तनटकर्ों से पिा चलिा है कक सशक्तिकरण पहल को शैक्षक्षक पहुंच के साथ -साथ पाररिाररक जुड़ाि , नेिृत्ि विकास और मलगं -उत्तरदायी मशक्षण प्रथाओं पर जोर देिे हुए िहुआयामी दृक्टटकोण अपनाना चाहहए। यह शोध ककशोर महहला सशक्तिकरण को प्रासंश्रगक रूप से समझने में योगदान देिा है, क्जसके मलए बिहार के सामाक्जक -सांस्कृतिक पररदृश्य में लड़ककयों के शैक्षक्षक और व्यक्तिगि विकास को प्रभािी ढंग से समथान देने के मलए क्षेत्रीय -उपयुति माप और हस्िक्षेप रणनीतियों की आिश्यकिा होिी है।
स्त्री अनुभव और आत्मसाक्षात्कार की दृष्टि से मैत्रेयी पुष्पा व ममता काष्टिया के कथा साष्टहत्य का अध्ययन
समकालीन ह िंदी साह त्य में स्त्री लेखन ने अपनी हिहशष्ट प चान स्थाहपत की ै। मैत्रेयी पुष्पा और ममता काहलया दोनोिं ी लेखखकाओिं ने अपने कर्था साह त्य के माध्यम से स्त्री जीिन के िास्तहिक अनुभिोिं को प्रामाहिकता के सार्थ प्रस्तुत हकया ै। प्रस्तुत शोध पत्र में इन दोनोिं रचनाकारोिं के कर्था साह त्य का स्त्री अनुभि और आत्मसाक्षात्कार की दृहष्ट से तुलनात्मक हिश्लेषि हकया गया ै। इस अध्ययन में य स्पष्ट ोता ै हक मैत्रेयी पुष्पा ग्रामीि और हनम्न िगीय खस्त्रयोिं के सिंघषय को रेखािंहकत करती ैं, जबहक ममता काहलया मध्यिगीय श री स्त्री की मानहसक द्विंद्व और आधुहनक जीिन की जहिलताओिं को उजागर करती ैं। दोनोिं ी लेखखकाएिं हपतृसत्तात्मक व्यिस्था के हिरुद्ध स्त्री स्वर को मुखर करती ैं और स्त्री अखिता की खोज को अपने साह त्य का केंद्र बनाती ैं। य शोध कायय गुिात्मक शोध पद्धहत पर आधाररत ै और पाठ हिश्लेषि, तुलनात्मक अध्ययन तर्था नारीिादी आलोचना की सैद्धािंहतकी का उपयोग करता ै।
स्त्री अनुभि, आत्मसाक्षात्कार, मैत्रेयी पुष्पा, ममता काहलया, कर्था साह त्य
मौलिक अधिकार के रूप में प्राथलमक लिक्षा के प्रति दृष्टिकोण को आकार देने में कानूनी और सामाष्िक कारकों की भूलमका
यह अध्ययि तीि सारणीबद्ध अभ्याव़ेदि क़े माध्यम स़े "प्रार्थशमक शशक्षा को मौशलक अधधकार क़े रूप में आकार द़ेि़े में कािूिी और सामाजिक कारकों की भूशमका" क़े वैचाररक ढांच़े और संचालि का गंभीर रूप स़े ववश्ल़ेषण करता है। ताशलका 1 शीषषक क़े मुख्य घटकों का ववश्ल़ेषण करती है, जिसस़े एक स्पष्ट संरचिा का पता चलता है ल़ेककि अंतसंबंधों की खोि का अभाव है। ताशलका 2 कािूिी और सामाजिक कारकों पर ववस्तार करती है, उदाहरण और संभाववत प्रभावों की प़ेशकश करती है; हालााँकक, यह अत्यधधक सरलीकरण का िोखखम उठाता है और प्रासंधगक बारीककयों की उप़ेक्षा करता है। ताशलका 3 दृजष्टकोण की िांच करती है, माप संक़े तक और संभाववत ववववधताएं प्रदाि करती है, किर भी यह मुख्य रूप स़े अंतनिषहहत तंि में िाि़े क़े त्रबिा मतभ़ेदों पर ध्याि कें हित करती है। इस ववश्ल़ेषण का तकष है कक यद्यवप ताशलकाएाँ एक उपयोगी प्रारंशभक त्रबदं ु प्रदाि करती हैं, उन्हें कािूिी, सामाजिक और व्यवहाररक आयामों की गनतशील परस्पर किया क़े सार्थ महत्वपूणष िुडाव की आवश्यकता होती है। अध्ययि ववभाजित अभ्याव़ेदि स़े आग़े बढ़ि़े और शैक्षक्षक दृजष्टकोण को आकार द़ेि़े वाली प्रासंधगक िहटलताओं पर ववचार करि़े की आवश्यकता पर प्रकाश डालता है। इसक़े अलावा, संभाववत प्रभावों और ववववधताओं पर ताशलकाओं की निभषरता क़े शलए दावों को प्रमाखणत करि़े क़े शलए अिुभविन्य सत्यापि की आवश्यकता होती है। महत्वपूणष ववश्ल़ेषण प्रार्थशमक शशक्षा को मौशलक अधधकार क़े रूप में आकार द़ेि़े में कािूिी, सामाजिक और व्यवहाररक कारकों की उभरती गनतशीलता को पकडि़े क़े शलए शमधित-पद्धनत दृजष्टकोण और अिुदैध्यष अध्ययि को नियोजित करि़े क़े महत्व को ऱेखांककत करता है।
The Impact of Liquefaction on the Behavior of Retaining Walls is Studied
Retaining walls constructed adjacent to underground water are the structures which may be influenced by liquefaction. The design of these structures under vibration involves determining their displacements and forces caused by earthquake and liquefaction phenomena. In this study, it is attempted to assess the effect of liquefaction on the behavior of retaining walls using finite element method (FEM). The OPENSEES software is used for this purpose, which can simulate the behavior of saturated porous media using the u-P correlation formulation. Moreover, the Dafalias-Manzari critical state two-surface plas- ticity behavioral model is applied to simulate the behavior of sand, which can model a variety of behaviors of saturated sand in various uniaxial and cyclic loadings under drained and undrained conditions for different relative densities. The results of this study suggest that the OPENSEES software and Dafalias-Manzar behavioral model possess essential capabilities for numerical modeling of behavior of retaining walls under liquefaction conditions. The presence of retaining walls also chang- es the pattern of development of excess pore water pressure, particularly at middle depths of the wall.
Retaining wall, Liquefaction, Saturated sand, Critical state.
Mr. L. Harish, 2Mr. B, Suresh, 3Mr. S. Kiran Kumar, 4Mrs. D, Anusha, 5Mr. SK. Imran Pasha
Examining Urban Growth and Its Social and Economic Effects in Malda, West Bengal
This study examines the evolving urbanization patterns in Malda District, West Bengal, and investigates their multifaceted socioeconomic impacts from 2010 to 2023. Using a mixedmethods approach combining demographic data analysis, satellite imagery interpretation, and household surveys, we identify significant urban growth concentrated in English Bazar and Old Malda municipalities, with peripheral rural areas experiencing varying degrees of transition. The urbanization rate increased from 7.32% in 2010 to 14.87% in 2023, driven primarily by agricultural diversification, trade expansion, and improved transportation infrastructure. Our findings reveal that while urbanization has generated substantial economic opportunities through employment diversification and increased per capita income (rising by 67.3% in urban centers), it has simultaneously produced concerning socioeconomic disparities. These include increased income inequality (Gini coefficient rising from 0.31 to 0.39), uneven access to public services, environmental degradation, and cultural transformation. The study concludes that Malda's urbanization trajectory offers valuable insights for regional development policy, underscoring the need for inclusive urban planning frameworks that carefully balance growth imperatives with equitable distribution of resources and opportunities.
Urbanization patterns, socioeconomic impact, spatial analysis, Malda District, urban-rural divide.
Optical communication systems that use wide-band optical semiconductor amplifiers and high-speed signal processing
This work clarifies the analysis of the theoret- ical study of noise and transmission gain characteristics of semiconductor optical amplifiers (SOAs), which are relevant in the novel local area optical communication systems. We investigated the effects of noise on AlGaAs/ GaAs SOA transmission performance through the mea- surement of output power, optical gain, the optical signal- to-noise ratio, and noise figure. It was observed that noise has a dramatic effect on SOAs’ operation transmission efficiency, and the performance of the amplifier structure may be limited. If the drive current and injection power at the SOA can be changed and its active region length modified, then the variation of gain, optical signal-to- noise ratio, and noise figure at the output of the structure can be obtained.
device dimensions; gain bandwidth; noise figure; SOAs
Blockchain-Powered Smart Contracts And Federated Ai For Secure Data Sharing And Automated Compliance In Transparent Supply Chains
The accelerated development of international supply chains has brought with it challenges like data silos, inefficiencies, and security risks. Legacy systems are challenged with regulatory compliance and operational latency. To address this, this research suggests a novel framework that combines blockchain-based smart contracts with federated AI to maximize data sharing, increase transparency, and provide security. Blockchain offers a decentralized, tamper-evident ledger that fosters trust and accountability. Smart contracts streamline core supply chain processes such as order confirmation, payment processing, and compliance checking minimize dependence on human intermediaries, and lower operation costs. While federated AI facilitates joint model training across nodes without sharing raw data, guaranteeing privacy but enabling real-time decision-making, anomaly detection, demand forecasting, and threat analysis. This synergistic strategy not only ensures compliance and monitors possible fraud but also greatly enhances efficiency 93% and transparency in contemporary supply chain management, representing a significant improvement over traditional practices. This pioneering research presents a promising future.
Predictive Analytics In S/4 Hana: A Framework For Ai-Driven Enterprise Resource Planning
This research focuses on predictive analytics integrations in S/4 HANA for AI-driven enterprise resource planning. Predictive analytics in SAP S/4HANA is a functionality that uses statistical and machine learning techniques to interpret data and anticipate trends and future events. Predictive analytics help companies make data-driven decisions and develop their outcomes. Within the eco-system of SAP S/4HANA, PA is an add-on feature and a primary element that transforms data into proactive insights. Thus, AI-powered systems automate regular tasks, improve decision- making and create contemporary forecasting and data analytics. This research utilised both secondary qualitative and quantitative methods, with journals-articles, case study examples statistical websites, and others. Case study examples include Coca-Cola, Siemens AG, and Adidas, with measures such as the accuracy of predictions, operational efficiency, ROI, and user adaptation rate. Moreover, this application allows companies to handle large enterprise information stores, integrating predictive frameworks directly into operational systems. Index Terms- SAP S/4HANA, AI, ML, Predictive Analytics, AI Integration, ERP
Aligning Corporate Strategy with ESG for Lasting Competitive Success
This study investigates the relationship between Environmental, Social, and Governance (ESG) practices and corporate competitive advantage through strategic alignment. The research aims to examine how organizations can integrate ESG principles into their core business strategies to achieve sustained competitive success. Using a quantitative methodology analyzing 2,847 publicly listed companies from 2018-2022, this study employs regression analysis and structural equation modeling to test the hypothesis that strategic ESG alignment enhances competitive advantage. The findings reveal that companies with high ESG scores demonstrate superior financial performance, with an average ROA improvement of 3.8% and reduced cost of capital by 1.2 percentage points. ESG-driven firms exhibit enhanced innovation capabilities, improved risk management, and stronger stakeholder relationships, contributing to sustainable competitive advantages. The study concludes that ESG integration is not merely a compliance requirement but a strategic imperative that drives long-term value creation and competitive positioning. Organizations that align their corporate strategy with ESG principles demonstrate superior performance across multiple dimensions, including financial metrics, operational efficiency, and market valuation, establishing ESG as a fundamental driver of competitive success in the contemporary business environment
ESG, Corporate Strategy, Competitive Advantage, Strategic Alignment, Sustainability
AI-Driven Healthcare Data Management and Predictive Analytics using Cloud Computing and Secure Authentication
This study presents the improvements in health service delivery and revenue management of health-related data, mainly relying on real-time predictive analysis, anomaly detection, and personalized care management. A system for data collection organized through structured methodology involves a variety of sources of health care data such as electronic health records (EHR), wearable sensors, and medical devices. It has the intricate processes through pre-processing, handling missing values, normalizing, and extracting features through the Fast Fourier Transform (FFT) technique. The pre-processed data have been secured while still permitting organization for further processing and analysis. Multi-factor authentication (MFA) was set up to safeguard patient information for confidentiality. Different performance metrics were involved in evaluating the models with the total accuracy of 96.44%, precision 95.80%, recall 94.95%, and F1 score 95.37% and validated the strength of predicting health outcomes. The current integrated frame thus provides an increasingly strong justification for predictive health-care initiatives and the study of artificial intelligence, cloud computing, RNNs, and security and protection measures in data storage systems.
Artificial Intelligence, Cloud Computing, Recurrent Neural Networks, Data Preprocessing, Feature Extraction, Multi-factor Authentication, Healthcare Prediction
A STUDY ON CUSTOMER'S PERCEPTIONS OF RELIANCE RETAIL IN HYDERABAD, TELANGANA STATE
The Customers perception towards Reliance retail – A study on Reliance retail stores Hyderabad I have found that customers have preferred reliance retail stores than the other retail stores available in Hyderabad. I have concluded to this statement after sending a questionnaire to the customers in Reliance retail. I have done a data analysis on this questionnaire and found out that most of them preferred Reliance retail stores than other stores present. For this we have limited the study only to Hyderabad. I have done a comparison of pre and post pandemic performance of Reliance retail by taking the key components i.e. sales, profits and share capital of Reliance retail. From the study we have found that COVID – 19 has impacted the performance of Reliance retail stores. The sales of reliance retail have not been much affected during the COVID pandemic but the gross profits and net profits of Reliance retail has been adversely impacted due to this pandemic. But the pandemic has not at all impacted the share capital of the Reliance retail stores. In the data analysis we can see that during COVID there has been an increase in the share capital. In the conclusion we have come to know that Reliance retail received positive comments from the customer’s point of view and we can see that they are satisfied with the Research.
Reliance retail stores, Customers perspective, Sales, Profits, Share capital, COVID
A COMPREHENSIVE ANALYSIS ON THE SIGNIFICANCE OF FINANCIAL LITERACY IN PORTFOLIO OPTIMIZATION
This paper examines the pivotal role of financial literacy in the process of portfolio optimization. In an era marked by complex financial markets and an abundance of investment options, the ability to effectively manage investment portfolios has become increasingly crucial for individuals and institutions alike. Portfolio optimization, the strategic allocation of assets to maximize returns while minimizing risk, stands as a cornerstone of prudent financial management. However, achieving optimal portfolio outcomes requires more than just financial acumen—it demands a deep understanding of financial literacy principles.
This paper examines the pivotal role of financial literacy in the process of portfolio optimization. In an era marked by complex financial markets and an abundance of investment options, the ability to effectively manage investment portfolios has become increasingly crucial for individuals and institutions alike. Portfolio optimization, the strategic allocation of assets to maximize returns while minimizing risk, stands as a cornerstone of prudent financial management. However, achieving optimal portfolio outcomes requires more than just financial acumen—it demands a deep understanding of financial literacy principles. This study delves into the various dimensions of financial literacy that contribute to successful portfolio optimization. It explores how individuals with a strong grasp of financial concepts such as risk diversification, asset allocation, and investment strategies are better equipped to construct portfolios that align with their financial goals and risk tolerance levels. Moreover, the paper investigates the impact of financial education programs and initiatives on enhancing investors' ability to make informed decisions regarding portfolio management. Through a comprehensive review of literature and empirical evidence, this paper highlights the symbiotic relationship between financial literacy and portfolio optimization. It underscores the importance of ongoing education and awareness initiatives aimed at improving individuals' financial knowledge and decision-making skills. Additionally, it offers insights into practical strategies for enhancing financial literacy among investors, including personalized financial coaching, online tutorials, and interactive learning platforms. In conclusion, this study underscores that financial literacy is not merely a desirable trait but a fundamental prerequisite for effective portfolio optimization. By equipping investors with the knowledge and skills needed to navigate the complexities of financial markets, enhance risk management practices,and seize investment opportunities, financial literacy serves as a catalyst for achieving optimal portfolio outcomes and long-term financial well-being.
A Comparative Study of Tata Motors and Maruti Suzuki in the Automobile Industry: A Financial Analysis
Over the last several years, the automotive sector has continued to expand. The Indian car industry plays a key part in the global car market. With growing need for income backward, the growing middle-class and youthful populations, a huge pool of qualified workers and developing technology, are among the five leading auto-producers in the world by 2022. Profit is the motor that propels the company. Each company or organization should have sufficient earnings to survive and develop in the long term. Profitability is the capacity to take advantage of the whole commercial activity of an organization, corporation, company or business. It demonstrates how effectively management can benefit from all available market resources. I have chosen 2 car firms in India for this project. The main aim of this research is to analyze over the past five years the financial efficiency, liquidity, and profitability of the chosen car businesses (2017-2021). My research is based on secondary information. By utilizing various ratios, the financial situation is analyzed. The position of Maruti Suzuki & Tata Motors is determined by the research.
Arduino Based Vehicle Accident Alert System using GPS, GSM and Accelerometer. Accelerometer detects the sudden change in the axes of vehicle and GSM module send the alert message on your Mobile Phone with the location of the accident. The advancing technology has made our day to day lives easier. Since every coin has two sides similarly technology has its benefits as well as its disadvantages. The rise in technology has increased the rate of road accidents which causes huge loss of life. The poor emergency facilities available in our country just add to this problem. Our project is going to provide a solution to this problem. If we reduce the time between when an accident happens and when a medical ambulance is dispatched to the area, we can save human lives by reducing mortality rates. GPS has become an integral part of a vehicle system nowadays. The accelerometer senses a sudden shift in the vehicle's axles. It will be tested by Arduino. The Arduino sends the warning message via the GSM module to the police control room or a rescue team, including the location. So, after receiving the information, the police can automatically track the location via the GPS module. Then, the appropriate action will be taken after verifying the venue.
Vehicle Pollution Monitoring System Using IoT
Humankind, moving to a period cantered upon improvement has overlooked the significance of supportability and has been the real guilty party behind the rising Pollution levels in the world's air among all other living life forms. The Pollution levels at certain spots have come to such high degrees that they have begun hurting our very own It will being. An IoT based Air Pollution observing framework incorporates a MQ Series sensor interfaced to a ARDUINO UNO outfitted with an ESP8266 WLAN connector to send the sensor perusing to a Thing Speak cloud. Further extent of this work incorporates an appropriate AI model to foresee the air Pollution level and an anticipating model, which is fundamentally a subset of prescient displaying. As age of poisonous gases from ventures, vehicles and different sources is immensely expanding step by step, it winds up hard controlling the dangerous gases from dirtying the unadulterated air. In this paper a practical air Pollution observing framework is proposed. This framework can be utilized for observing Pollutions in demeanor of specific territory and to discover the air peculiarity or property examination. The obligated framework will concentrate on the checking of air poisons concentrate with the assistance of mix of Internet of things with wireless sensor systems.
Kavali Rohit2, T. Venkanna Yadav2, Shaik Shafi2, K. Surya Teja2
Ultra Violet Sterilization System with UV Lamp Failure Detection and Monitoring Over IOT
The project has been aimed at achieving a solution for huge energy wastage by introducing a method to control and monitor the ON and OFF timings of street lights by both automatically and manually from a remote location using Internet of Things (IoT). Conventional street lights in most of the areas are turned ON and OFF manually in the evening before the sun sets and the next day morning after there is sufficient sunlight and do not have a controlling system. The complete setup incorporates the use of Light Dependent Resistors (LDR) for sensing the light intensity in the environment and the sunlight falling on them to control the street lights. The lights will automatically glow once the sun goes down or at times when the intensity of light falling on the sensors diminishes due to stormy weather. A major leap has been taken in the project by using ESP 8266 Wi-Fi module for integrating the sensor with the street light and also for monitoring and controlling the whole network in real time from any remote location through the internet.
SOCIOECONOMIC-DEMOGRAPHIC STATUS AND LEVEL OF JOB SATISFACTION OF BANKER WOMEN EMPLOYEES: A CASE STUDY OF UBI IN PATNA DISTRICT
Banking is a typical example of the modern service industry, which has been overgrowing in India. The implications of the above-said transformations have affected the bank employees' social, economic and psychological domains and their relations. The job satisfaction of work life has become one of the essential issues in banking sector specially among women. Thus, the employee's job satisfaction became more critical to all organizations and at every workplace. The employees are not only expecting monetary benefits but also non-monetary benefits like better working conditions, interpersonal conflicts, role conflicts, job pressure, lack of freedom of work, absence of challenging work, etc. In this paper, an attempt has been made to identify the factors determining job satisfaction among women working in the banking sector in the Patna District of Bihar. The study based on primary data of 148 sample respondents that have been chosen randomly. Bivariate analysis and Chi-Square test were used for analysis. As a woman, she has to face several challenges in her family life, and it is double if she is working other than household work that gains some economic value. In her daily life routine, she has to face several unhealthy situations and circumstances not only outside of the workplace but with her office too that badly affect her performance, productivity, quality of work and the cop with the ties between family life and professional life. The banking industry needs to improve its policies and strategies to develop the quality of work life for its women employees.
Banking, Education, Employees, Job Satisfaction, Marital Status, Women
The water resource for farming is very much important. In Olden days people used to supply water for irrigation through rivers, reservoirs, tanks, and wells for irrigation farming. Day by day some of such resources vanish and over the century, the population of India has become three times. Demand for food as growing population and the need for water for agricultural productivity is crucial. As a result of a severe shortage of water exists across parts of India. Though we have different solutions with which water and fertilizer utilization can be optimized still there are few gaps which need to be addressed to make the current systems more robust and backed by technology to get better yields. In this work, IoT based water conservation for farming using auomated drip irrigation system by considering scalability. Here for storing statics or parameters could storage is used. Based on these parameters dripping decisions (soil, moisture, and climate conditions) has been taken. The proposed solution is implemented and shown results with necessary parameter.
Soil moisture sensor, Temperature sensor, IOT.
Mood Abhinav, Sabhavath Akhila, S Teja Sri, Boini Shiva Krishna
PERFORMANCE ANALYSIS OF DEBT MUTUAL FUNDS ATN.J INDIA INVEST PVT. LTD
Inventory management emerged as a specialized branch of management about a decade after the end of world war- II. It was realized that an integrated approach towards various inventory management function and use of effective tools and techniques were necessary for any progressive business organization. The material usually forms a major part of the total cost and constitutes one of the most important assets in the majority of the manufacturing companies. The success of business also depends on large extent upon the efficient inventory management.
FARMING MADE EASY USING MACHINE LEARNING
Agriculture is the primary mainstay of the economy in our country. In recent years because of uncertain trends in climate and other fluctuations in the price trends, the price of the crop has varied to a larger level. Farmers remain oblivious of these uncertainties, which spoils the crops and causes massive loss. They are unaware of the crop type which would benefit them most. Due to their limited knowledge of different crop diseases and their specific remedies, crops get damaged. This system is handy, easy-to-use. It provides accurate results in predicting the price of the crop. This framework utilizes Machine Learning’s Decision Tree Regression Algorithm to predict crop price. The attributes considered for prediction are rainfall, wholesale price index, month, and year. Consequently, the system gives an advance forecast to the farmers' which grows the speed of profit to them and consequently the country's economy. This system also incorporates other modules like weather forecast, crop recommendation, fertilizer recommendation, and shop, chat portal, and guide are also implemented.
K. Sravani2, K. Sangeetha3, G.Jhansi4, G. Ratna Priya
CLOUD BASED MULTIMEDIA CONTENT PROTECTION SYSTEM
We propose a new design for large-scale multimedia content protection systems. Our design leveragescloud infrastructures to provide cost efficiency, rapid deployment, scalability, and elasticity to accommodate varying workloads. The proposed system can be used to protect different multimedia content types, including 2D videos, 3D videos, images, audio clips, songs, and music clips. The system can be deployed on private and/or public clouds. Our system has two novel components: (i) method to create signatures of 3D videos, and (ii) distributed matching engine for multimedia objects. The signature method creates robust and representative signatures of 3D videos that capture the depth signals in these videos and it is computationally efficient to compute and compare as well as it requires small storage. The distributed matching engine achieves high scalability and it is designed to support different multimedia objects. We implemented the proposed system and deployed it on two clouds: Amazon cloud and our private cloud. Our experiments with more than 11,000 3D videos and 1 million images show the high accuracy and scalability of the proposed system. In addition, we compared our system to the protection system used by YouTube and our results show that the YouTube protection system fails to detect most copies of 3D videos, while our system detects more than 98% of them. This comparison shows the need for the proposed 3D signature method, since the state-of-the-art commercial system was not able to handle 3D videos.
G. Greeshimka2 ,K.Rohitha3 ,K. Madhimita4 ,K. Gnana Shreeya5, K.Namratha
ELECTRICITY THEFT DETECTION IN POWER GRIDS WITH DEEP LEARNING AND RANDOM FORESTS
As one of the major factors of the nontechnical losses (NTLs) in distribution networks, the electricity theft causes significant harm to power grids, which influences power supply quality and reduces operating profits. In order to help utility companies solve the problems of inefficient electricity inspection and irregular power consumption, a novel hybrid convolutional neural network-random forest (CNN-RF) model for automatic electricity theft detection is presented in this paper. In this model, a convolutional neural network (CNN) firstly is designed to learn the features between different hours of the day and different days from massive and varying smart meter data by the operations of convolution and down sampling. In addition, a dropout layer is added to retard the risk of over fitting, and the back propagation algorithm is applied to update network parameters in the training phase. And then, the random forest (RF) is trained based on the obtained features to detect whether the consumer steals electricity. To build the RF in the hybrid model, the grid search algorithm is adopted to determine optimal parameters. Finally, experiments are conducted based on real energy consumption data, and the results show that the proposed detection model outperforms other methods in terms of accuracy and efficiency.
G. Deepthi, G. Akshaya Reddy, G. Vijaya Laxmi, G. Rajasree
A MACHINE LEARNING BASED CLASSIFICATION AND PREDICTION TECHNIQUE FOR DDOS ATTACKS
The recent proliferation of Internet of Things (IoT) is paving the way for the emergence of smart cities, where billions of IoT devices are interconnected to provide novel pervasive services and automate our daily life tasks (e.g., smart healthcare, smart home). However, as the number of insecure IoT devices continues to grow at a rapid rate, the impact of Distributed Denial-of- Service (DDoS) attacks is growing rapidly. With the advent of IoT botnets such as Mirai, the view towards IoT has changed from enabler of smart cities into a powerful amplifying tool for cyberattacks. This motivates the development of new techniques to provide flexibility and efficiency of decision making on the attack collaboration in a software defined networks (SDN) context. The new emerging technologies, such as SDN and blockchain, give rise to new opportunities for secure, low-cost, flexible and efficient DDoS attacks collaboration for the IoT environment. In this paper, we propose Co-IoT, a blockchain-based framework for collaborative DDoS attack mitigation; it uses smart contracts (i.e., Ethereum’s smart contracts) in order to facilitate the attack collaboration among SDN- based domains and transfer attack information’s in a secure, efficient and decentralized manner. Co- IoT’s implementation is deployed on the Ethereum official test network Ropsten [1]. The experimental results confirm that Co-IoT achieves flexibility, efficiency, security, cost effectiveness making it a promising scheme to mitigate DDoS attacks in large scale
IoT Garbage Separator and Bin Level Indicator
The uncollected waste material when the waste bin is full is a common problem nowadays. Thus, an efficient waste management for the waste material is essential in ensuring a clean and green surrounding environment. This paper presents an Internet of Things (IoT) based Smart Waste Collection Monitoring and Alert System to monitor the waste material at the selected site of garbage collection area. The system is implemented using an ultrasonic sensor which is connected to Arduino UNO as to monitor waste bin garbage level. In this system, waste bin depth level will be sent via Arduino Ethernet Shield with an Internet connection to the Ubidots IoT Cloud. The Ubidots store the collected waste bin level data into IoT database and display the waste bin depth level on online dashboard for real-time visualization. The Ubidots Event manager invokes a notification alert to garbage collector mobile phone via a SMS when the waste bin is nearly filled for immediate waste collection. Therefore, the waste collection became more effective and systematic.
IoT Based Temperature Scanning Entry System
We propose a low-cost internet of things (IoT)-enabled COVID-19 standard operating procedure (SOP) compliance system that counts the number of people entering and leaving a vicinity, ensures physical distancing, monitors body temperature and warns attendees and managers of violations. The system comprises of multiple sensor nodes communicating with a centralized server. The data stored on the server can be used for compliance auditing, realtime monitoring, and planning purposes. The system does not record the personal information of attendees nor provide contact tracing information.