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In the world of today, receiving complaints or feedback has become fundamental for an organization aiming to improve the quality of its products or services. Similarly, public complaints must be addressed to improve government service. There is no direct or effective channel for citizens in India to address issues with the government. Later, the government launched applications for registering complaints to make the public's job easier. However, there are some issues related to those applications' equity, i.e., the difficulty faced by the rural community and uncivilized people in using those applications. This paper proposes a smart microphonic grievance system that will allow people to register complaints orally, automatically classify them, and forward them to the appropriate sector. The test results demonstrate that this system can reduce the time and process for filing complaints and that it can be used by a diverse group of individuals in society. Overall, this system is a valuable solution for improving complaint management and addressing the unique needs of rural residents. [ABSTRACT FROM AUTHOR]

A growing field in India that can assist farmers in many ways is the identification of plant diseases. Plant disease reduces the mass production in agriculture. Every time due to heavy loss in agriculture, farmers face many challenges to raise up their needs. This study analyzes various diseases that affect various plants due to the following criteria like environmental condition, types of plant formed from Monocot and Dicot family, crop rotation and Ph value of the soil. The existing system analyzed the diseases based on one of the criteria. Although the strategy is to be followed to identify plant diseases at the early stage with various aspects so that the production in agriculture could be increased. The majority of machine learning algorithms already exist and may be improved upon to yield more accuracy. Xanthomonas wilt, Black and Yellow Sigatoka, Bunchy Top Virus, Black Sigatoka, Fusarium wilt, Cassava Bacterial Blight (CBB), Cassava Brown Steak Disease (CBSD), Cassava Green Mite (CGM), and Cassava Mosaic Disease (CMD), Yellow vein mosaic virus, and Powdery Mildew are a few of the diseases of the plants grown on crop rotation which are the subject of study of this paper. Plant illnesses are classified according to disease in the many open-source datasets that are accessible. For deeper understanding, we have provided a list of references. Here, we've examined the approaches that are now in use for automatically detecting various diseases of plant leaves. We present an approach for accurately identifying early signs of plant diseases from a variety of perspectives. [ABSTRACT FROM AUTHOR]

Heart disease is one of the fatal human diseases that cause sudden death, and the ratio of deaths has been rapidly increasing globally in both developed and developing countries in recent days. As per the record of World Health Organization (WHO), approximately 18 million people face death every year as a result of heart disease. Coronary Artery Disease (CAD) is a type of illness in which the heart fails to supply adequate blood to all parts of the body for normal function. Heart disease and CADs have emerged as the most life-threatening problem which occurs not only in India but also worldwide, and this is the cause of the large number of deaths. Early detection and diagnosis of heart problems is critical for preventing death and saving patients' lives. The traditional method of predicting heart problems is ineffective. As a result, it is critical to accurately identify the problem at an early stage. In recent days Machine learning plays a vital role in identifying patients with heart disease. This paper discusses about the various techniques involved in interpreting ECG signal and its issues. Also, the various machine learning methods which are applied so for from the various paper for the classification of Heart problem is clearly narrated. [ABSTRACT FROM AUTHOR]

Traffic accidents are among the sad events that cause great loss. In India, it has become a big problem because it has claimed the lives of innocent people. Road accident control has become an important task. One of the reasons behind the project is to prevent the increasing number of road accidents caused by speeding in prone areas. This study examines how we detect speeding vehicles and their license plate number. Vehicle speed detection and tracking contribute significantly to citizen safety by preventing many accidents. This module is essential in traffic monitoring, where traffic efficiency and citizen safety are the main concerns. In this study, we discuss possible ways to find a car, track its speed, and detect license plates. Various studies and research papers on speed detection were done before and can be found on the internet. The proposed approach broadly includes the steps such as plate contouring, finding date and time stamp, location detection, speed calculation, and reporting to the authorities. This paper aims to monitor the speed of vehicles to prevent accidents and reduce the impact in the event of an accident. This project proposes a modern and effective method for detecting and reporting illegal speeds. [ABSTRACT FROM AUTHOR]

Goods and Service Tax (GST) is the growing field of research which is not fully explored due to its recent implementation. Many researchers have explored on different areas of GST. However, as it a new topic in the area of indirect taxation it lacks systematization. Many earlier studies have no consensus on perception of taxpayers about GST and influencing factors of perception on GST implementation. Therefore this paper conducts systematic literature review to map relevant studies on Perception of Tax Payers towards GST and consolidate the reviewed studies and thus combine the findings to get answers to the research question. 126 research papers were identified, screened and ultimately refined for final review study. Thus, a total of 38 research papers were included in the SLR (systematic literature review). Researchers analyzed 38 relevant papers and frequency analysis is done to identify factors, theories, methodology, sample size periodicity of study and suggestions for improving perception. The findings show that awareness and tax knowledge are most important factors to get positive perception on GST. Theory of Planned Behavior (TPB) and conceptual models have been constructed for making studies on GST perception. Mostly Quantitative studies are conducted in this research area. The studies suggested correct policy framing and programs to educate the public are likely to increase positive perception about GST implementation. Thus this paper is useful to the government to make policy changes and thus making the GST implementation successful. [ABSTRACT FROM AUTHOR]

This Paper deals with sufferings of lower-caste people. It brings out the logical consequence of an oppression and domination of a man. It finds the presentment of 'India's Darkness and India's Light'. It presents how a chauffeur breakdown the Rooster Coop. It shows the anticipation of Balram about his master. It presents how a poor man emerges as a successful entrepreneur. It describes the title's symbolization. This paper represents India as an emerging entrepreneurial power in the modern days. This paper employs that the class conflict and how the deprived one's struggle for achieving a right position in the world. It also explains that the oppressors change from place to place but the sufferings of the oppressed class never change. [ABSTRACT FROM AUTHOR]

This paper is a brief summary of some linguistic characteristics of Lambada language. Lambada is a nomadic tribal language spoken by many speakers in India. Most of the linguistic features of Lambada are similar to those of various Indo-Aryan Languages like Hindi, Marathi, Gujarati, and Rajasthani etc. In spite of the massive borrowing of lexical items, Lambada has retained several linguistic features that are not found in other Indo-Aryan Languages. This paper attempts to look at various basic linguistic features of Lambada language such as speech sounds of Lambada, phonological processes and grammatical features in a brief note. [ABSTRACT FROM AUTHOR]

It is very common part of discussion that normal structures lag behind in terms of energy saving and its corresponding impacts on environment. This drives research to show implementation of common solutions and concepts that can be easily applied by majority of individuals to fulfill sustainable and self-sufficient goals to lead to a better habitat to live in. The aim of paper is to explore proper application of most common and most essential cost-effective design solutions to make structure following a step towards self-sufficient in itself. The paper has emphasized on quantitative and mathematical approach of study generating owns secondary data, from various research papers that are based upon similar background aspects. The value analyzed for solar panel tilt should range from 20o-30o for maximum efficiency, similarly distance between panels should be 1m-1.6m and horizontal shading device and vertical shading device should have at least depth of 450mm and 700mm respectively. The study is limited to a particular climate and region. i.e., Northeast region of India and focuses only upon most critical parameters. This paper will provide new directions for self-sufficiency in structures, which will further add values to the domain of architecture and civil engineering. Further, new areas of research can be application of new design alternatives for self-sufficiency, with respect to several other climatic conditions and regions. [ABSTRACT FROM AUTHOR]

The increase in data from modern sources, the heterogeneous nature of data, ambiguous and unstructured data, and the so-called Big Data with all of its five v's characteristics, indicate a growing need to use approaches that provide assistance in modeling and processing these data, provide additional automated data processing, and so on. The majority of all these studies involve one or more big data sets that may be used in various applications. Most of these selected papers use one or more distributed frameworks (such as MapReduce, Spark, or HDFS Hadoop distributed file systems). Furthermore, more than one strategy of Web mining is dealt with (such as Naive Bayes, Logistic Regression, and Random Forest, as examples) more than recommender system types (collaborative filtering, or/and content-based filtering). Various data sets were used (such as Movie Lens data set, LDOSCoMoDa data set, real bank loans dataset, using Facebook and Twitter for collecting data, data was taken across different companies, thousands of movies were used as exemplary data sets, or data sets used a sample data from different schools of Central Board of Secondary Education (CBSE) across India). Testing accuracy on the dataset obtained is required in the accuracy used (precision and recall). The best precision was 0.9886 and the best recall was 0.9835 in these studies. We have displayed some studies that have high precision and low recall and some other studies that have low precision and high recall. This paper introduces a literature survey about recommender systems that deal with big data through web mining techniques. [ABSTRACT FROM AUTHOR]

Agriculture is the backbone of success of rural countries like India. In this way, the proposed procedure is to utilize mechanization and web of thing (IoT) innovation to form agribusiness smart. There are currently several commercial IoT frameworks for water system planning that create differentiators for water monitoring and storage. However, this framework focuses on exploiting newly available water resources without controlling the selected water resources. Think about it, an inexpensive Arduino-based IoT framework was developed to design a computerized water system, and it will provide estimation of water requirements by using low-cost available sensors. This paper is around IOT based keen cultivating and water structure framework. The extreme motivation of this paper is to computerize the method of watering to plants. This work makes a difference us to notice the values of different parameters like moisture, temperature, humidity of plants and water them appropriately. This can be done utilizing Arduino board, voltage controller and transfer which commands the engine. In this paper, we have created an brilliantly water system framework that will control the water apportioning to the trim intelligently without any administrator and endeavors low-cost Arduino-based water system gadgets, sensors, particularly advanced procedures actualized in water system frameworks and farming, such as shrewdly water system frameworks. The main vision of this research is to detect minimum amount of water needed to nourish plants. Mass of the ranchers waste time instead of focusing on providing water to the crops at the time of need. The proposed framework find out the desired quantity of water on the basis of information received through the sensors - The main advantage of the system is the use of precision agribusiness and cloud platforms, which can expand the water use compost, which also helps in decision making. to increase crop yields. the weather conditions of the field. This article moreover points to create the water system framework for domestic gardening and this framework can be kept up without any human checking. It consequently checks the dampness of the soil beneath the tree and plants within the domestic cultivate and in case the dampness is moo it demonstrates the message and pours water naturally to the plants from the water capacity to which it is associated. The exact utilization of water system strategy is needed as there may be a requirement of precipitation or there may be dried regions. For this cause, a mechanized water system framework is utilized in which it is appropriate in all weather conditions. The soil dampness detector will sense the water substance and demonstrate either to pump the water or not. This will offer assistance to diminish the wastage of water additionally makes a difference to grow the plants indeed in the event that the human isn't physically present. The developed IoT framework has been tested in several field tests to calculate sensor accuracy, independent monitoring and operation, and usability monitoring, and to evaluate its capabilities and functionality. This framework appears to have been used effectively for the management and control of various water resources: water, groundwater, seawater and wastewater. By extension, it has been shown that the frame can be used for long periods without a source of control, which will make it a ideal device for using in annual crops. [ABSTRACT FROM AUTHOR]

Farmers grind away in the fields to take home just an exiguous income. Now, the agriculture industry is already a burdened industry with uncertainties from all directions. One of the major issues the industry is facing is crop loss. In India, every year around 30-40 per cent crops are lost. This has adverse effects on food security of the highly populated nation. For that matter, India is the 16th hungriest country in the world. Thus, there is a need to identify, understand and overcome agronomic losses. Extreme climate events and crop diseases are the two major reasons for crop losses. While climate events are less controllable, plant disease prevention becomes an important area of interest. Detecting plant diseases at early stages using images serves as key to preclusion of severity. In this paper, we have surveyed some of the significant papers on plant disease detection using image processing. [ABSTRACT FROM AUTHOR]

Two-wheeler vehicles are a major form of personal transport in the world and specially India, a substantial number of 2 wheelers on roads have made it difficult to monitor them correctly. This has led to carelessness from the drivers and increase in the number of accidents that can be prevented and minimized. One of the protective gears-helmet is not always worn by riders and it is tough for the traffic police to catch these violators, due to sheer size. Our project involves using the YOLO (You Only Look Once) algorithm to detect whether the riders as well as pillions are wearing the helmets so that they can be caught, and their vehicle details be sent for further processing to the traffic police. Along with the 2 wheelers, helmets are also required at construction sites, and we plan to apply the same. This paper proposes a framework for identification of motorcyclists without helmets. The application, with the help of YOLOv5 (You Only Look Once) and rigorous training gives us an accuracy of 87% true positives detection. [ABSTRACT FROM AUTHOR]

Text classification using K Nearest Neighbor, which locates the K closest matches in training data and uses the label of closest matches to forecast the class of the text. Euclidean distance is used to find the closet matchwhich is predict the class level. The technique Bag of Words is used to find numerical values from the document in terms of text representation. An annotated corpus in Odiabased on agriculture domain collected from ILCI, Govt. of India treated as training data and the representation of that text data for finding sentiment using the concept of the feature vector made from the entire document which we have collected. The calculation of the results using KNN with tf-idf is challenging for Odia text as it low resource language. This paper presents details of result analysis with thoroughly done by experiment. Evaluation of the model is focusedon speed of the transferring text data to the proposed model and getting high accuracy rate. The result of the testing data depends on good and bad features of the algorithm and suggests for how to improve feature iteration of the same model in future. [ABSTRACT FROM AUTHOR]

India ranks second in production of cement. In order to produce one ton of cement about one ton of Co2 is released into atmosphere. As per Global Cement and Concrete Association, Cement is the third highest contributor of Green house gases in the atmosphere. In order to decrease the negative impacts of cement in the atmosphere a new type of concrete is evolved by conducting countless researches that is Geopolymer Concrete. The Amount of Cement Content in Geopolymer Concrete is null and void. Artificial Neural Networks is bough of Artificial Intelligence. It is one of the sophisticated Computed technique to prognosticate the properties of Geoploymer Concrete with minimum Percentage of error. In this paper more than 170 hunks of data gathered from the literature to train and test the data. In this study evaluated by various statistical indicators like mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE). After performing ANN the statistical parameters found be 0.92, 0.934 and 0.905. which resembles that ANN outcomes are satisfactory and can be used in evaluating the properties of the Geopolymer concrete. [ABSTRACT FROM AUTHOR]

Agriculture is the backbone of India which is diversified. Mushroom cultivation is one such farming method that not only gives promising profit to the cultivators but also provides nutritional mushrooms to the consumers. Nowadays, as the demand for the mushroom cultivation is increasing day by day, advanced technologies pave way for the farmers to improve quantity and quality along with its nutritional value of mushrooms. In this paper, pilot study has been conducted in order to extract knowledge-based inference by remotely monitoring the environmental conditions such as temperature and humidity using DHT11 sensor, CO2 using MG811 sensor, rat movement using PIR sensor and light intensity using LDR sensors are monitored through ThingSpeak cloud server to govern the appropriate actuators such as Sprinkler, LED, Humidifier, Exhaust Fan and Buzzer at the given threshold values, along with this Biological Efficiency%(BE%) has been conducted in both manually controlled mushroom and also in IoT enabled mushroom in two types of species i.e., P. florida and P.eous APK1. From the pilot study the results proves that the monitoring and automation of parameters plays a predominate role in producing the nutritious mushroom with increased Biological Efficiency % (BE%) in P.florida as 99.51% in IoT enabled cultivation whereas in manual controlled hut it is 90.99%. The proposed DCE highlights the importance of machine learning algorithm and its collaborative aspects of supervising and governing the environmental conditions in each stage of growth with appropriate actuators and Biological Efficiency %(BE%) which will play a major role in producing the most nutritious mushroom. Therefore, the proposed DCE framework will be greatly helpful for reaping highly nutrient mushrooms and it will help to increase social economic growth of self-help women and agriculturist. [ABSTRACT FROM AUTHOR]

Cotton is one of the important cash crops in India grown on more than 9 million hectors. Like other crops this also suffers from diseases but the effect on the yield affects many livelihoods. Thus, it is necessary to detect the disease in early phase so that cure can be taken. This paper proposes a Convolutional Neural Network (CNN) model for detecting diseases in cotton plants. The model implements in proposed work utilize transfer learning technique, leveraging pre-trained model that have been trained on extensive datasets. Specifically, the Resnet152v2 model serves as foundational architecture for the model, enabling accurate classification of distinct objects. In addition to Resnet152V2 base, the proposed work incorporates two supplementary dense neural network layers. These additional layers enhance the model capacity to learn complex pattern and improve its classification capabilities. With integration of transfer learning and inclusion of supplementary dense network layer, the model demonstrates its ability to effectively classify objects. In addition to Resnet152a 98.36% accuracy in distinguishing between healthy and diseased cotton plants. [ABSTRACT FROM AUTHOR]

The most frequent cause of natural disasters in India is tropical cyclones. Early warning, real-time monitoring, impact and damage assessment, and relief operations all depend on remote sensing and GIS. The Bay of Bengal is frequently the source of cyclones of various intensities. In this paper, the actual goal is to predicate the tropical cyclone in the tropical region of the Bay of Bengal, for that the main satellite data set is collected from the NASA data repository. The overall work is being done by using the tool MATLAB, where all machine learning classifications are applied to the data set and trained. As a result, which classifier has the highest accuracy will be considered as the best result. The primary goal of this research is to forecast cyclones using day-by-day satellite data of coastal regions and a variety of weather factors. The objective of this work is threefold. First to design a model to reduce the dependency on a single classification technique, secondly to avoid the over-fitting of data, as well as to improve the accuracy of the prediction. Two number of steps in collective learning: Multiple machine learning models created using the same or different machine learning algorithm. [ABSTRACT FROM AUTHOR]

Project Management Information System (PMIS) is a digital platform for collecting various types of data, recording, storing, and disseminating it for various construction processes for the smooth functioning of a construction enterprise or project. In today's scenario, PMIS in the civil engineering industry is not widely known in India due to a lack of proper guidance, application methods, and knowledge about the advantages of effective management systems and control over a project, both in terms of personnel and material. PMIS in the construction industry can help in various ways, such as real-time tracking of a project, risk elimination, handling human resources, procurement, cost reduction, and maintaining the standard quality of a project in a given time period with a proportional cost index. In this paper, through a design thinking approach, an economical PMIS for MCE's (Micro-construction Enterprises) is proposed for design and development. [ABSTRACT FROM AUTHOR]

The safety of the workforce is paramount in the construction sector. The provision of the safety policy, safety assurance, safety risk management, and safety promotion were to be used to manage the workers' safety on the job site. By providing the workers with the ensured safety management measures. The riskiest tasks, such as working at heights on structures, must be adequately managed in terms of safety. Following the safety management policy, the primary thing to deploy at the time of execution was the planning. By conducting a study and survey, it will be possible to update significant safety management policies. Through this survey, we learn that every project adheres to the fundamental safety guidelines set forth by the OHSA. This study led us to the conclusion that small businesses who cannot afford the costs of projects do not adhere to safety management procedures and do not have a safety management strategy in place for their projects. The projects now under construction in India are adhering to a safety management strategy that might assist the workers should a fatality occur. All current projects adhere completely to the labor laws established in India at every firm. Conclusion drawn from this survey is the execution of the safety management strategy results in no fatalities or accidents. The sort of employees that require the greatest training will also be supported by this research, which improves conversations about worker safety and training requirements on elevated building sites and urban areas. In addition to improving worker productivity and the plant's economics, the paper will raise the facility's worth and help the utility build a strong demand in construction sector and measured by using SPSS software. [ABSTRACT FROM AUTHOR]

The degradation and alteration of waterbodies globally have been occurring at an alarming rate, surpassing the pace of their restoration efforts. Brari Nambal Lagoon is an important waterbody located in the Kashmir valley of Jammu and Kashmir, India. The lagoon is a shallow, fresh water body that supports a variety of aquatic plants and animals and is a source of water for the surrounding communities. However, the water quality of the lagoon has deteriorated due to anthropogenic activities such as pollution from agricultural runoff, domestic sewage and industrial effluents. The physico-chemical properties of the lagoon provide evidence of the significant changes in water quality that have occurred since the early 1980's. A noticeable decline in dissolved oxygen levels has been observed, indicating a shift in the lagoon's ecosystem. In addition, the concentrations of harmful substances such as phosphates have increased, suggesting anthropogenic activities are contributing to the lake's degradation. This review paper also gives insights about the trophic status of the lagoon by reviewing the different techniques to assess the condition of the lagoon and the need for effective measures to improve and protect the water quality of lagoon to ensure the sustainability of the surrounding communities and ecosystem. [ABSTRACT FROM AUTHOR]

Investments in Mutual Funds are rapidly increasing in India since last two decades. The investments made in open-ended mutual funds are comparably more than close-end mutual funds. The retail investors in India who are in position take risk on their investment are preferring open-ended equity mutual fund schemes. Open-ended equity mutual funds are the financial instruments and the performance of these funds are largely depending on Market fluctuations. The open-ended equity mutual fund schemes are risky investments compare to other forms mutual funds. These funds returns are based on the risk-taking ability of investors and bring the more returns to the investors in long run as compared to debt funds. The performance of open-ended mutual fund schemes is volatile in nature and majority of the fund depending on company and industry growth and the returns of the funds will give different benefits for short term and long-term investors. The present paper analyses the performance of select Indian open-ended equity mutual fund schemes and also analyse the risk and returns characteristics funds for select time period. [ABSTRACT FROM AUTHOR]

Banking sector in India is one of the most important sector playing an important role in growth of Indian economy. After the liberalization the role of banks is increased to provide monetary services to entrepreneurs, customers and common people. Banking sector operations are increased due to growth of industrialization. The rapid growth in industrialization encouraged both public and private sector banks to expand their services to meet requirements of bank customers. The performance of banks is measured based on performance indicators like ROA (Return on Assets), ROE (Return on Equity) and NIM (Net Interest Margin). The said three factors are the key bank performance indicators to assess the concern bank performance. The ROA, ROE and NIM are most important factors in measuring the bank performance and the growth of any commercial banks is largely depends on these three financial ratios. The growth of ROA is very important for any bank to increase their assets in long run, ROE is concern with market movements and it is influenced by the different market conditions linking to banking sectors. NIM is very important to increase the internal operation efficiency of bank and to improve the liquidity and profitability conditions in banks. The current paper emphasizes on key performance indicators of select public and private banks and compare their performances and analysed the factors influencing the key performance indicators. [ABSTRACT FROM AUTHOR]

Information technology revolutionized education system. Knowledge now could spread to the remote corners of the country. It caters to the needs of many and the best part is, it is not time bound and has no time limits to the knowledge inputs. A little awareness of operating the gadgets will help to browse and explore the world of knowledge. The use of mobile phone is just made it easy that all the data is available with the finger touch. Books are now made available through online libraries and even audio books which help us in pronunciation and help the students to improve their vocabulary. Technology has helped us to reduce and save paper also to conserve the environment. This helps the students to pursue out of the curriculum subjects. The aids can be derived through focus and without deviation. Space consumption for E-Resources is too less and the devices we use are also portable and handy. We can attach any information to our mail as this secure feature helps us in storing the material land accessible at any place and at any point of time even during our travel. Electronic resources consists of data representing numbers, text graphics, images, moving images, music, sounds etc. All these utilize the multiple ways of brain simulation. Colorful videos and games improve to build the vocabulary and create interest in learning. It is said that imitation is best form of appreciation. Students appreciate and enjoy exposure to these resources and tend to learn quickly. [ABSTRACT FROM AUTHOR]

The derivatives markets for crude oil, corn, soybeans, and other global economic mainstays are well developed, with active trading in financial contracts that derive their value from the asset. Notably, while the value of a derivative is based on a resource, possession of a derivative does not necessitate ownership of the asset. Derivatives are widely used by producers of commodities to lock in the prices of the goods they will sell or acquire at some point in the future. rude-oil futures are the top commodity contract traded on the commodity exchange MCXNSE-0.14%, allowing a wide range of investors to hedge their positions or merely to speculate on the volatility of crude oil. The contract gets its price cues from the New York Mercantile Exchange's futures contracts for West Texas Intermediate crude oil (NYMEX). The study concluded that there was high volatility in the crude oil futures market before and during COVID – 19. The macro factors throughout the world have contributed to the volatility. In this paper, the data which is taken from a secondary source i.e. from MCX (Multi commodity Exchange) website, India, related to crude oil future market Total Averages Daily Turn Overvalues in Lakhs during the period September 2019 to May 2020 attempted to present the crude-oil data graphically and to study the characteristics of volatility, descriptive statistics have been defined and also made the comparison of the data sample means using Z-statistic. [ABSTRACT FROM AUTHOR]

Water is closely linked with all living beings and it is the source of all developments in the form of societal, cultural, rituals and religious beliefs. The river Cauvery is the only perennial river in Tamil Nadu and the water level is raised during rainy season. Out of 133 chapters in Thirrukkural, one of the famous Tamil literature, the second chapter itself deals with the importance of water management and the need for the water cycle. All most all the ancient Tamil literatures have evidenced of various water management practices which were carried out to manage the water throughout the year. Several thousand years ago, the olden civilizations were invented to consume the water flowing through the canals and drainages to the maximum extent. Various dynasty were ruled in India before 1000 years onwards and the emperors handled the water management in a systematic approach and managed the floods and droughts in an effective manner. Various structures like canals, dams and water diversion were built by the emperors for the effective utilization of rain water. This paper deals with the effective water management exercises practiced in more than 1000 old Chozha dynasty in Tamil Nadu. [ABSTRACT FROM AUTHOR]

When it comes to combating climate change and global warming, the best course of action is to promote the use of renewable energy sources (RESs) and reduce reliance on fossil fuels. In this regard, most nations have resolved to boost the use of solar photovoltaics (PV) and wind turbines (WTs) to generate clean green energy and curb carbon emissions. India is actively contributing to the international change of the energy sector. When it comes to renewable energy and encouraging the use of electric vehicles, India is among the top five countries in the world. There has been a recent push to increase the world's renewable energy generation capacity to 450 GW by 2030, up from its current level of around 400 GW. Getting India's total generation beyond 60%using the low-carbon energy sources is encouraged because it will help the country meet its larger climate goals and push it above the amount agreed upon in the Paris Agreement. Economic growth, increased energy security, and expanding access to energy for the rural population are only a few of the goals, roles, and responsibilities of government. As part of India's progress toward modernization, this paper details a number of related efforts, policy shifts, technical and economic hurdles, and regulatory rules for rolling out renewables and EVs. [ABSTRACT FROM AUTHOR]

After globalization and the emergence of new technology, differentiated services, an innovation revolution, a creative explosion, and numerous alternatives, the working environment is under increasing strain. Education isn't an exception. Each educational institution competes for superb efficiency, enormous performance, and unequalled distinctiveness. The educational sector's administration expects too much from faculty members to stand out from competitors. Education's competitiveness challenges emotional intelligence and work-life balance. The goal of this paper is to look at the connection between work-life balance and emotional intelligence among university teachers at Private University in the Telangana district of Warangal. During the study process, a descriptive type of research design is used. The number of educators in the study was 30. The teachers were chosen through a method called "convenience sampling." The research tool was made by putting together Hayman's WLB scale from 2005 and Daniel Goleman's EI dimensions from 1997 into a structured questionnaire. Statistical tools were used to come up with and test two hypotheses. According to the findings, educators with a medium level of emotional intelligence have an equal number of educators who agree that work interferes with personal life, personal life interferes with work, and work and life are enhanced. The study has been limited to the faculty members of SR University, and it can be extended to other universities in India for further significant insight in understanding the levels of work-life balance and emotional intelligence. Educational policies and improving teaching pedagogies can help to improve the levels of WLB and EI among universities. [ABSTRACT FROM AUTHOR]

One of the most important results of contemporary technological growth is the sharp increase in vehicle numbers, which has gotten more severe in the wake of the astounding rise in the overall population. Thus, the primary issue at hand is the delay in getting there. Sometimes the delay is explained by how long it takes to get to the hospital or receive initial care.I ndia's dire situation is made worse by traffic. A comprehensive solution is required to reduce the time taken at each step, even if the government is taking several initiatives. Some examples of these include evaluating the patient's status, calling for medical assistance, or making the nearest aid available. As a consequence, most countries in the globe today consider traffic congestion to be a serious problem. Using IOT, a system may be developed to enable emergency vehicles, such ambulances, to get at their destination as soon as feasible. The development of a smartphone application that will facilitate communication between traffic controllers and drivers is ongoing. We would provide the ambulance driver the option to choose the source and destination sites. Near traffic lights, digital screens will display the lane that the traffic controller selected. If other drivers can see the alert on the screen, they will be able to remove themselves from the scene or switch lanes before the ambulance comes. Thousands of fatalities may occur from ineffective traffic management if an ambulance won't be able to reach the hospital in time. However, the problem is becoming worse since, in emerging countries like India, annual road expansion is just around 4% while annual car growth is already at 11%. In light of this, the paper provides a novel, straightforward approach to traffic control in emergency situations. [ABSTRACT FROM AUTHOR]

Small hydropower is one of the most cost-effective and environmentally benign energy technologies for production of electrical power worldwide. In India, the available potential of small hydro is at about 15,000MW and small hydro can provide electricity to 120,000 unelectrified rural villages. Hence, this paper focuses the status of small hydro development in India and discusses the barriers/obstacles to the development of small hydro in India by taking government policy, economical aspects and environmental benefits of few countries into account. [ABSTRACT FROM AUTHOR]

Now days the impact of climate change in India are mostly affected to the agriculture field, most of the agricultural crops are being badly affected in terms of their performance of the crop. The crop yield is used to predict in advance because of its harvest, its help the farmers for taking good decisions in marketing. The results of knowing crop yield and building prototype for the purpose of easily available to the farmer. Thus, for such kind of data analysis in the crop, there are different techniques and algorithms to predict the crop in a field. In this we have used image processing algorithm. The data used are images are taken from the drone system. Our approach starts by seeing rows inside the area (or acre) and finding all the trees in a crop yield, by this knowing the size of plant in the crop can be easily to store the data of plants. Lately there has been a wide source of spatial photogrammetry available for agriculture. Most of this data gives new information about the crops. By analysis of crop statics and methods have not been widely performed due to limitations on the images and software involved. The classification was also validated by comparing dozens of trees in the field, with excellent results. The purpose of this paper is to provide farmers with a method for quickly and automatically classifying trees by size, regardless of the presence or absence of problems, so that they can more easily monitor the health of individual trees and gain a better grasp on how those trees are distributed across a given area. [ABSTRACT FROM AUTHOR]

Biomass in its original form with low bulk density causes large transport and storage costs, and therefore, it cannot be used as an effective combustion fuel. Densification of biomass using briquetting technology can resolve the aforementioned issues and enhance the effectiveness of biomass as a combustible fuel. The relevance of using this fuel in thermal conversion processes is growing because it is abundant and under-explored. Hence, examining the fuel characteristics of these resource materials is imperative for their effective utilization in energy generation. The aim of the present work is to assess the suitability of various agricultural and aquatic residues as sources of briquette production by determining their fuel properties. Sixteen types of agricultural and aquatic residues which are abundantly available in Kerala (southwestern coastal state of India) were selected for this investigation. The fuel properties of the selected feedstock materials were determined using proximate analysis, elemental analysis, and heating value testing. The density, moisture content, volatile matter content, ash content percentage, and fixed carbon percentage of the feedstock material were carried out according to different ISO standards. Furthermore, the elemental analysis and the heating value of all the feedstock materials have been determined. Finally, the paper concludes by comprehensively listing all the fuel properties of the feedstock materials investigated in this study. The density of the feedstock materials ranged from 105.92 to 700.10 kg/m3. The fuel properties showed that Water hyacinth leaves, oil palm fruit bunch, saw dust; grass waste, dry leaves, vegetable market waste, and spent tea waste have significant potential for bio-briquette production. Also, from the characterization of the feedstock material, it is evident that rice husk and banana peel have higher ash content (above 20 %). Therefore, they are not appropriate for the production of biomass briquettes. The fuel properties of various agro aquatic residues for briquette production obtained from this study are expected to be of great use to the manufacturers in the briquetting of these feedstock materials. [ABSTRACT FROM AUTHOR]

Agriculture has always been considered a lifestyle, especially in rural India rather than a revenue making market. In the present trend of automation, machines make decisions which are rational, reasonable and accurate. In this state of art technology Internet of Things (IoT) is paving a new path in automation. Therefore, in this paper, the research is carried to employ the IOT technology in the field of agriculture. A rover, capable of reading all essential parameters like soil moisture, temperature, humidity, air quality, sunlight and rain is developed in this research. These detected parameter values by rover are then transmitted to a comprehensive interface, a Mobile application. Mobile application will then give the customized predictions such as soil moisture and temperature based on soil-type. With the help of these parameter values a farmer can take necessary measures to maintain the crop in optimum conditions [ABSTRACT FROM AUTHOR]

Agriculture is critical to our country's economic success. It yields the most profit in crop production on the farmer's land. India is a developing country, and agriculture is a major component of the Indian economy, accounting for approximately 17% of GDP. India is also the world's second largest producer and the largest exporter of rice. Being the chief grain of India, the country has the largest area under rice cultivation, but the optimal yield would only be guaranteed if the field is free from diseases, whether it be fungal or bacteria, pests and nutritional deficiencies. The presented study will be very beneficial for the researchers to recognize any diseases, pests and nutritional deficiencies of the rice plant. As pest attacks also result in damage to the entire field, causing a reduction in the optimal yield production. Plant nutrients are also required for plants' good overall health. These nutrients are classified into three classes: primary nutrients, micro-nutrients and macronutrients. Each of these nutrients is essential for plant growth and development, but for optimal rice production at least primary nutritional deficiency should be taken care of which includes nitrogen, potassium and phosphorus. Agricultural crop losses directly attributed to fungus are significant, but to increase the productivity to the fullest pest attacks as well as primary nutrition deficiencies must also be detected. In this paper, we have conducted a literature study on various approaches and analysis of rice plant diseases, pests and nutritional deficiencies have been shown in tables which highlight the number of diseases focused, numbers of pests focused and number of nutritional deficiencies focused by different researchers. [ABSTRACT FROM AUTHOR]

Cardiovascular disease are leading causes of mortality worldwide, accounting for a substantial fatality rate in recent years, In the last several decades, it has been the number one cause of death, not just in India but globally. It is tough for medical practitioners to forecast because it is a complex undertaking that requires expertise and advanced understanding. In the field of healthcare data analysis, predicting heart disease may be difficult. Machine learning can provide a quick and accurate decision-making solution. The main purpose of the paper is to use ML algorithms to predict presence or absence of heart disease. Various ML algorithms have been analyzed such as RF, SVM, DT, LR, XGBoost, Naive Bayes and KNN. And, out of all of these algorithms, Logistic Regression and SVM had the highest accuracy of 81.97%. The maximum accuracy, recall, precision, and f1 score is achieved by Logistic Regression and SVM, whereas the lowest accuracy, recall, precision, and f1 score is achieved by KNN. [ABSTRACT FROM AUTHOR]

The present study is about the detailed analysis of the pandemic Corona Virus 2019 which has rocked the entire world with a maximum impact with its structure, its appearance and nomenclature, Clinical presentation and transmission, diagnostic technique. It's a respiratory illness caused by the virus SARS-CoV2 (Severe Acute Respiratory Syndrome). It's a syndrome is different from other virus syndromes as this might act as Symptomatic also as Asymptomatic. The common symptoms would be cold, fever, cough, sneezing, running nose, breathing issues, Fatigue, etc. The paper may be a vivid picture on the COVID 19 cases in Tamilnadu which is within the Southern part of India and therefore the treatments like Ventilator, Plasma, etc and therefore the remedy offered to the patients like Naturopathy, Ayurvedic, Siddha, Unani, Homeopathy, etc,.for better recovery and immunity to fight against the virus. It analyses the detailed reports and statistics during a regression form with reference to daily new death rate and total death rate with the assistance of statistical tools of the general rectilinear regression equation. the entire confirmed cases and daily new confirmed cases are plotted using Normal P-P plot of regression Standardized Residual. The Pearson correlation value is 0.837 which features a strong direct correlation between active cases and total recoveries. [ABSTRACT FROM AUTHOR]

The Indian government has proposed a national education policy designed by an eminent panel of experts, with the audacious goal of transforming the Indian education system. The policy plans to bring significant changes in the teaching-learning process from the school level to the university level. This paper studies the current information technology infrastructure that is available in Indian Universities for enabling e-learning. The data relating to IT infrastructure to facilitate e-learning was collected from 252 Universities across India. This was used to understand the present scenario of e-learning in the higher education context. An IT governance framework has been proposed which can effectively facilitate e-learning in alignment with the goals of the Indian National Education Policy. [ABSTRACT FROM AUTHOR]

Globally, pesticide use continues to rise, estimated to be over four million tonnes yearly. In 2020, it was almost 2.7 million metric tons, up 57% from 1990. Nanotechnology is an innovative and exciting technology that offers new nanoscale molecule designs, formulations, and delivery systems to diminish the hazardous pesticide effects. Many studies on nano-pesticide production have been published, whereas nano-biopesticides are still limited. The purpose of this research is to answer the question of whether nano-biopesticide formulations will emerge along the development of nano-pesticides. The research was conducted by using bibliometric analysis. All nano-pesticide and nano-biopesticide-related publications are extracted from the Scopus with no limitations year. Using VOSviewer, data on research scope, authorship contributions, number of citations, and global research trends are evaluated and mapped. The results show that the publishing of nanoparticles has an exponential trend, with 125 nano-pesticide documents. However, only 14 nano-biopesticide documents are available. India is the most productive country, publishing both nano-pesticides and biopesticides articles, 52 and 9 publications. India connects the Australian and European continents regarding nano-pesticide publications. China is next, with 36 articles about nano-pesticides currently published. Al-Whaibi (average of 86 citations) and Iavicoli have extremely high citation counts (average of 125.5 citations). In synthesizing nano-biopesticide formulations, we found that essential oils are the most common ingredient in nano-biopesticides. In future, the topic related to the impact of nano-biopesticides on crop production and resistance; the combination of nano-biopesticides and nano-fertilizers; the study of nano-biopesticides' effects on the environment; and microbial as nano-biopesticides are some trend in the nano-biopesticide formulation. We predict that research on nano-biopesticides will increase rapidly in the context of eco-friendly issues. Finally, this paper can serve as a basis for the upcoming research on nano-biopesticide formulations, particularly those involving microorganisms as bioactive substances. [ABSTRACT FROM AUTHOR]

Grape is one of the most cultivated fruit crops in India and widely used to produce the food items. Among the world, grapes are considered as most significant fruit and it comprises various nutrients, namely Vitamin C. However, grape plants suffer with diseases which extremely affect good quality grape yield. The major six general grape leaf disease and pests are brown spot, leaf blight, downy mildew, anthracnose, and black rot, which produces severe economic suffers to grape commerce. Thus, the early detection of grape leaf disease is highly needed to produce healthy grape yield. Moreover, computer vision driven approaches have been employed effectively in modern years for detecting and classifying plants diseases. In this paper, hybrid approach with fuzzy logic and neural network has been proposed to classify the grape leaf disease. The work is further extended to identify whether leaf is affected with pesticide or not and percentages of pesticide is calculated if it is affected with pesticides. Optimization approach has been used to find accurate results. This optimization based deep learning approach achieved the accuracy of pesticide identification 93.43%. [ABSTRACT FROM AUTHOR]

With the growing number of security breaches, the necessity for better security procedures and protocols has grown as well. According to a reports, lakhs of robberies are occurring in the United States of America each year. Though India is a developing country, these types of robberies are considerably more common. The primary purpose of this work is to develop a security solution that can help combat this. This paper primarily aims to design a software that is built from the ground up for detection of face, leading to facial recognition and finally, providing information to the user or the owner of the software if any unfamiliar face is there which is not a part of the database. The aim is to notify the owner about any unfamiliar person that is present and unrecognized by the camera. In case if the face is not recognized, alerts will be sent via SMS and Email. Some software has limited forward compatibility and can be difficult to run on weak hardware, thus it is necessary to have a software which is more powerful and easily run on the weak hardware. The proposed work has a great scope in the future applications ranging from simple automatic locking systems in households to an attendance system in corporate offices and even for an antiterrorism system. [ABSTRACT FROM AUTHOR]

Emerging technologies in smart wearables hold great potential to enhance people's day-to-day health by facilitating self-monitoring of physical activities. The research with these devices is in its early stages. In this research paper, using the expectation-confirmation theory (ECT), along with conformity, performance expectancy, and satisfaction, we investigated the factors that influence the intention to use continuously. Based on a sample of 678 smart wearable users, collected from Northern India, we have used structural equation modelling (Smart PLS4) and identified the impact of satisfaction post adoption technology, Habit to wear, data privacy and health information accuracy on the continuing intention of smart-wearable users. According to the findings, consumer satisfaction, health information accuracy, and data privacy are key variables that have a significant influence on the long-term intention to use smart wearables. This study has many implications for smartwatch manufacturers and designers looking to increase users' intent to continue using their products. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI), Blockchain, and the Internet of Things are all new technologies impacting people's lives. These technologies can change how we communicate, run our businesses, and even how governments work for their people. Artificial intelligence has disrupted the way traditional marketing practices are conducted and changed how business processes are done. Organizations and governments increasingly turn to artificial intelligence (AI) to improve customer experience, operational efficiency, fraud detection, and cyber security. The revolutionary buzzword, artificial intelligence (AI), has transformed our personal and professional lives. Industry 4.0 considers AIadoption significant due to its potential benefits. Since its inception, it has presented several possibilities and difficulties to various businesses. As a result, several AI-powered technologies have been created, and they have the potential to raise significantly living standards while also boosting the economy. This paper has conducted a conducive study of the marketing tools and techniques that adopt AI while looking through the loopholes to suggest howAI can be adopted quickly into the day-to-day lives of the human race. Based on this, it has recommended a course of action for India that entails the development of infrastructure, policies and rules, research and development, and humanresources. It is necessary for all parties involved to gather and address these problems. Infrastructure development, applications in the public sector, policy & regulation, technological development, and human resource development are all key responsibilities of the government. However, with the assistance of business, they may be accomplished effectively. For this study, the authors have employed secondary data. Future empirical studies might be conducted to compare the development of artificial intelligence technology in India to that of other emerging nations. The study is based on secondary data to demonstrate the development of artificial intelligence technology in India and overseas. However, empirical research may be conducted in the future. The writers' original points of view are presented in the article. [ABSTRACT FROM AUTHOR]

Nowadays in India, due to the increase in the number of accidents vehicles are being automated using a variety of Computer vision algorithms. This paper focuses on the detection of tail signals of cars under different illumination circumstances. This system is implemented using FAST and SIFT algorithm which helps to extract features from the images. The obtained features were optimized by using K-Means Clustering Algorithm. This huge feature vector is converted into 8 clusters. These optimized feature vectors were trained on five different classifiers as Decision Tree, SVM(RBF), Random Forest, and Voting Classifier. The trained data set used in this algorithm contains around 9052 images. The obtained accuracy results of different classifiers are as follows, Decision tress has 76.36%, SVM(RBF) has 77.91%, Random Forest has 87.52%, KNN has 89.72%, the Voting classifier has 86.52%. It is observed that KNN gives the highest accuracy among the five used classifiers. This has, to the best of the authors' knowledge, not been presented in literature before. [ABSTRACT FROM AUTHOR]

The Planning Commission, Government of India has estimated the water demand increase from 710 BCM (Billion Cubic Meters) in 2010 to almost 1180 BCM in 2050 with domestic and industrial water consumption expected to increase almost 2.5 times. The trend of urbanization in India is exerting stress on civic authorities to provide basic requirement such as safe drinking water, sanitation and infrastructure. There is a need for finding alternative to the traditional rapid sand filters employed in various cities for filtration purpose. Presently sand is being used as the filtration media which is limited resource. This paper discusses the use pervious concrete with specific aggregates as filtration device. Twelve concrete mixes were used to identify an optimum mix for treating turbidity effectively using lightweight expanded clay aggregates (LECA) considering the properties of w/c ratio and size of LECA and finding their impact on density, Infiltration rate, void ratio and removal of turbidity. It was observed that lower w/c ratio of 0.35 gave a higher density. The void ratio, infiltration rateand turbidity removal for LECA of size 10 mm and w/c ratio 0.4 gave the optimum results. [ABSTRACT FROM AUTHOR]

This paper examines the usage of the Internet of Medical Things (IoMT) in the growing smart technologies of older people. Using the theory of "Unified Theory of Acceptance and Use of Technology" (UTAUT) extended by "Protection motivation" and perceived risks, a model to determine IoMT usage was developed. A survey questionnaire from senior users in India was used to collect information from 259 older people. Empirical outcomes reveal performance expectancy, effort expectancy, facilitating conditions, perceived severity, perceived vulnerability, and perceived response cost determined the motivation to use IoMT for older adults. The findings also show that novelty-seeking moderates significantly the relationship between motivation and IoMT usage. This study advances the understanding of the motivators for IoMT usage among older people to engage them with smart technologies to monitor their health better. The research outcomes can be helpful to healthcare practitioners, having theoretical, practical, and social implications for building an intelligent well-being ecosystem for elderly people. [ABSTRACT FROM AUTHOR]

Hydrogeochemical behavior has an important factor to analysis the groundwater quality. The quality of the GW is directly interlinked with the GW recharge. GW management and protection is the important task not only for the Government but also it is responsibility of every human. The report of WHO told that 80 percentage of the disease of the whole world related with the water. In India as per the report of Niti Aayog 60 crore of our own country people are facing water problem. In this paper a brief review was done for the GW quality and its different types of analysis such as ANN, SCS-SN and many other different types of method. In our review we found that there is a significant spatial and temporal change in the GW and its parameters. Rainfall, Evapotranspiration are also the significant factors which influence the GW. In the coastal areas sea water intrusion is a major issue, to determine the hydrogeochemical characteristics of that influence region geophysical, geochemical and stable isotopes techniques are used. [ABSTRACT FROM AUTHOR]

Sign language is a crucial mode of communication for individuals who are deaf or hard-of-hearing, and a reliable sign language recognition system can greatly aid in bridging the communication gap. According to statistics provided by the Government of India, there are only around 250 accredited sign language interpreters in India, servicing a deaf population of 1.8 million to 7 million individuals. This paper presents a real-time sign language recognition system for Indian Sign Language (ISL) using YOLOv8 for object detection. The system uses a single convolutional neural network (CNN) architecture to process the entire image in one forward pass and predict the bounding boxes and class probabilities for each sign in the image. The results of the study demonstrate the feasibility and potential of the system in revolutionizing communication for the deaf and hard of hearing community and have applications in gesture-controlled robotics, home automation, game control, human-computer interaction, and sign language interpretation. [ABSTRACT FROM AUTHOR]

With the increasing demand for energy worldwide, it has become imperative to explore and adopt sustainable energy practices. In this regard, predicting household electricity consumption accurately is essential, as it can help optimize energy usage and reduce waste. This paper focuses on using Long Short-Term Memory (LSTM) shows the neural networks to prevent household electricity consumption in India. The LSTM model was implemented using the Keras library in Python. The model was trained using the training set and tested using the testing set. The study demonstrated that LSTM neural networks are a promising approach to predicting household electricity consumption in India. Further research can be conducted to recover the accuracy of the perfect by including more variables such as household size, income, and appliance usage. [ABSTRACT FROM AUTHOR]

India is one of the hugest rice cultivating country in the world. For thousands of years rice is a most major food, consequently every mankind depends on it directly and indirectly. But the Main hindrance in rice production is rice leaf diseases. It greatly reduces the production rate. Rice leaf diseases have specific symptoms that cannot be easily identified by usual human's eye. Using one of the image processing techniques, the rice leaf diseases are detected efficiently. In order to detect the diseased image Median Filter, K-means Clustering, GLCM and SVM classifier algorithms were proposed. Accuracy, Precision and ROC of SVM classifier were calculated as performance metrices. Around 97±2 % accuracy was achieved in this method. This paper discusses the efficient methodology for rice leaf disease detection. By using proposed method diseased leaves are identified at the early stage, which can aid farmers in preventing further damage to their crops. [ABSTRACT FROM AUTHOR]

During COVID-19 pandemic from 2019 onwards emergent demand of online classes has become worldwide prevalent. In the present era of pandemics along with advanced information and communication technology (ICT), institutions have shifted their pedagogy and are providing effective class room learning using web. Students are also joyful getting rid of class room constraints like modality, rigidity and inconveniency. The main objective of this research was to determine quality learning and students career growth as educational outcome via massive open online courses (MOOCS) as compared to that of traditional classes going physically offline and face to face (F2F). A total of 92 students of UG and PG level from different Indian universities and 8 countries including India were interviewed through questionnaire shared to achieve the objective. No significant difference was observed. In many research questions MOOCS were better proved than F2F. This paper will enrich the domain of distance learning, management and promote online learning using ICT. [ABSTRACT FROM AUTHOR]

Indian Consumer traditionally been known for the reusing product through generations to fullest of its life. Globalization has changed Consumer needs, purchasing power & social status which has sparked the changes in consumption pattern. Products are getting manufactured for single use instead of durable. This has been generating the lots of waste in day today life. Increasing population, its demand & consumption pattern has triggered a sharp rise in the input material demand & price. India's limited natural resources makes it difficult to suffice need of population. Circular Economy (CE) is the solution for the imbalance in supply vs. demand. It will bring societal changes towards circularity of product and material. Circularity helps to optimize the manufacturing cost and bring down product cost. CE enables the reduction in the waste generation in manufacturing industry as well as at customer end. CE is one of the biggest contributing factors towards United Nations Sustainable Goal (SDG12) of Sustainable Consumption & Production. CE Model serve the need of different economic layers of society. CE will help India in achieving economic prosperity and environmental goals. This Paper summarize the Circular Economy application areas and benefits in Indian Manufacturing Industry. [ABSTRACT FROM AUTHOR]