Volume 11 | Issue 4 |

 Abstract

The current attendance mechanism is thought of as manual. Both teachers and students must put in a significant amount of time. Even with manual attendance, there is still a chance that there will be proxies in the class. The work's key contribution is the creation of an attendance control system that employs student faces as feed input. We have decided to use the Raspberry Pi and a webcam to make it accessible on all platforms. Connected to the Raspberry Pi module is a webcam. The web cam is used to capture student face photographs. The Qt creator IDE implements many face extraction methods utilizing the OpenCV platform. Face recognition technology is used to take attendance in this project, allowing us to identify each student's face

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 Keywords

Attendance management system, Face Recognition, Raspberry Pi.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The level of pollution is increasing rapidly due to factors like industries, urbanization, increasing in population, vehicle use which can affect human health. IOT Based Air Pollution Monitoring System is used to monitor the Air Quality over a web server using Internet. It will trigger an alarm when the air quality goes down beyond a certain level, means when there are sufficient amount of harmful gases present in the air like CO2, smoke, alcohol, benzene, NH3 and NOx. It will show the air quality in PPM on the LCD and as well as on webpage so that air pollution can be monitored very easily. The system uses MQ135 and MQ6 sensor for monitoring Air Quality as it detects most harmful gases and can measure their amount accurately. The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH4, CO, SO2, and H2S as the most influencing gases significantly affecting mine air quality. According to the Mine Safety and Health Administration (MSHA), faulty equipment, negligence of labor towards explosions, structure failure, and gas accumulation are the most common causes of underground mine accidents. During the economic year of 2014, in the salt range coal mine in Punjab, Pakistan, more than 35% of accidents occurred due to the accumulation of toxic gases. Therefore, for the safety of workers and the mine itself, it is extremely important to monitor the mine environment continuously and accurately.

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 Keywords

Arduino, Underground coal mines, Internet of things, Mine environment index, Principal component analysis.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Real estate is a significant investment, and it is essential to know the value of a property before investing hard-earned money. Machine learning techniques have been increasingly used to predict real estate prices in megacities like Mumbai, Chennai, Bangalore, and Pune. This paper focuses on the XGBoost regression algorithm, a powerful technique that can be used to predict housing prices with high accuracy. The XGBoost algorithm is an ensemble method that combines multiple decision trees to create a more robust and accurate model. It is particularly useful in handling non-linear relationships between input variables and real estate prices. The algorithm can efficiently process large datasets with multiple variables, making it an excellent tool for real estate prediction. This study highlights the importance of the XGBoost algorithm in predicting real estate prices accurately. It examines various input variables, including carpet area, number of bedrooms and baths, balcony, amenities, and area type, to build a reliable model. The XGBoost algorithm is evaluated based on various performance metrics, such as mean absolute error, mean squared error, and R-squared, to assess its accuracy and effectiveness. The results show that the XGBoost algorithm outperforms other machine learning techniques such as linear regression, decision trees, random forest, and neural networks, in predicting real estate prices. It can efficiently handle complex non-linear relationships and accurately predict the prices of properties in megacities like Mumbai, Chennai, Bangalore, and Pune. In conclusion, this study demonstrates the effectiveness of the XGBoost algorithm in predicting real estate prices. The algorithm can help investors make informed decisions by providing accurate predictions based on various input variables. The study emphasizes the importance of using advanced machine learning techniques like XGBoost for real estate investments, especially in megacities where property prices are highly volatile.

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 Keywords

: Real estate, investment, machine learning techniques, predicting, housing prices, XGBoost regression algorithm, ensemble method, decision trees, non-linear relationships, input variables, accuracy, performance metrics, mean absolute error, mean squared error, R-squared.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This model involves designing and building of a simple 3 axis Computer Controlled drawing machine. Drawings are a key part of the manufacturing process. Having a programmable machine that can complete the task would make the job that much easier. Though such drawing machine may not be especially practical in a general design and development process of parts for instance, it can be a stepping stone in that direction. This project does provide a great tool for learning the basic functions of a robot. The two in technical terms and by definition are quite synonymous. A drawing machine is not much more than a CNC machine. More specifically a CNC router with an attached writing utensil, rather than a cutting tool. This particular application is an open-source project by BCN3D Technologies, which anyone can replicate for themselves. The parts can be 3D printed using FDM printers. Robot arms area essential thing to learn for any engineering student's looking get into the manufacturing industry. Today robots are employed in virtually all manufacturing and assembly processes. They do the job which are hazardous, strenuous, or too difficult for humans. This paper will present an affordable model of a CNC plotter machine which is able to draw a circuit layout on PCB or any other solid surface using simple algorithm and available components. At first the user needs to convert any image file or text file into G code using Inkscape software and then feed it to the machine using Processing software. Arduino uno with an ATmega328P microcontroller is used as the control device for this project. The microcontroller converts G-code into a set of machine language instruction to be sent to the motor driver of the CNC plotter. Keywords - Arduino, CNC, stepper motors, Inkscape software, G- code file.

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 Keywords

Arduino, CNC, stepper motors, servo motor, Inkscape software, G-code file are some of the keywords.

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 Abstract

Cryptocurrency price prediction using Long Short-Term Memory (LSTM) is a popular method for forecasting future prices of the cryptocurrency It is supervised and organised by a blockchain, a peer-to-peer network that also acts as a secure record of transactions.. LSTM is a type of recurrent neural network (RNN) that is capable of learning long-term dependencies, making it well-suited for time series data like financial markets. In this approach, historical price data is used to train the LSTM model, which can then be used to make predictions about future price movements.To implement this, the first step is to preprocess the data, which involves scaling and transforming the data into a format that can be fed into the LSTM model. Then, using a sliding window technique, the LSTM model is supervised on the preprocessed data to predict the following value in the time series on the basis of a certain number of earlier values. After training, the model can be used to make predictions about future price movements. These predictions can be evaluated using various performance metrics such as mean squared error or root mean squared error to assess the accuracy of the model. Overall, the use of LSTM for Bitcoin price prediction has shown promising results, with some studies reporting high levels of accuracy in predicting future price movements. However, it is important to note that cryptocurrency markets are highly volatile and unpredictable, and there are many factors beyond historical price data that can affect the price of Bitcoin

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 Keywords

Cryptocurrency, Bitcoin, Technology, Block, Network, Blockchain, price of bitcoin, Digital, Transaction, Model. I

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 Abstract

Mental imagery is widely accepted by sport psychologists, coaches, and athletes to be a useful psychological technique in the training of athletes for excellence athletes use mental imagery extensively in their training and in conjunction with competition. The aim of this study is to examine imagery ability of athletes from individual and team game sports and to determine if the groups differ in relation to these imagery attributes. The subject taken for the study were men and women individual and team game players from the representative of the Mangalore university. Data collected from total of 160 subjects of athletes. In that 80 subjects from women individual and team game players and 80 subjects from men individual and team game players. The results showed that a comparative imagery ability for individual men and women, the SIQ subscales like CS, CG, MS, MGA, and MGM. In the first four subscales are represented the women percentage is more than men and (MGA) men percentage is more than women percentage. A comparative of imagery ability for team game men and women in that five SIQ subscales are represented in that women percentage is more than men. This study examined the effects of level of participation and time involvement in sports on mental imagery characteristics and will provide may help coaches and athletes to identify the mental preparation needs of specific sports and to present additional information about individual differences in sports imagery.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

imagery ability, athletes, team sport, individual sport.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A self -reporting oral health impact profile was developed to examine and elicit the children's responses towards various parameters which includes physical pain, physical disability etc. The children to be tested will be in the age range of 6 to 11 years where they can understand and interpret question for proper elicitation. The responses will be recorded by using modified Likert scale (gender specific for boys & girls/ separate questions will be given for both the gender) our newer scale can be an excellent tool for multidimensional assessment of child and his limitations.

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 Keywords

OHIP/OHIP-14, OHIP-35, Oral Health, Functional Limitation, Psychological Discomfort

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 Abstract

The human society is undergoing rapid changes in the knowledge landscape. Keeping in view the role of education as an instrument for change, the National Education Policy -2020 (NEP- 2020) has been approved by Government of India with a vision to rejuvenate Indian Education system in tune with this era of rapid changes and technological advancements in society. The Present paper attempts to discuss the recommendations of NEP-2020 regarding use and integration of technology in Higher education to equip the teaching-learning paradigm for the needs of emerging Knowledge Society and knowledge-based global economy. Enunciating the digital initiatives of the Government for promoting Technology Enabled Learning (TEL) in Higher Education Institutions (HEIs), the paper aims to evaluate NEP-2020 as a step towards coordinating relevance and excellence in Indian Higher Education. Analyzing the role of National Educational Technology Forum (NETF) in shaping the future of technology enabled higher education in the country, the paper also discusses initiatives suggested in NEP-2020 to address the challenges in promotion of TEL in Indian context.

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 Keywords

National Education Policy (NEP-2020), Technology Enabled Learning (TEL), Knowledge-Driven Society, National Educational Technology Forum (NETF) __________

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Our aim is to develop a shortest path finder robot using Arduino Uno, a popular open-source electronic controller that is widely used in the field of robotics and automation. This involves designing and implementing a software algorithm that can calculate the shortest path between two points on a given graph, and then transmitting this information to the Arduino board, which controls the robot's movements. The algorithm used in this project is based on Dijkestra's algorithm, which is a well-known algorithm for graph search that can be used to find the shortest path between two nodes in a graph. The algorithm is implemented using C++ programming language, Arduino library and the Arduino IDE. The hardware used in this project includes an Arduino board, motor driver, IR sensors, DC motors and chassis . The system works by first detecting the starting and ending points on the graph using the sensors. Once the starting and ending points are detected, the algorithm calculates the shortest path between these two points and then transmits the instructions to the Arduino board, which controls the robot's movements. The robot then follows the instructions to navigate along the shortest path, avoiding obstacles along the way. The project is aimed at developing a low-cost and efficient solution for autonomous navigation of robots in various applications such as warehouse management, automated guided vehicles, hospital emergency direction detector and home automation. The system can be further improved by adding more sensors and using more advanced algorithms to optimize the path planning process.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Arduino Controller, IR Sensors, Robot, DC Motor

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Automated Teller Machine (ATM) services are increasingly popular due to their flexibility and easiness for banking systems. To provide high security, fingerprint and face recognition based customer authentication was introduced. This project aims to develop a single smart card ATM (Automated Teller Machine) for multiple bank accounts, reducing the cost of inter banking transactions. The user module is the interactive module through which the user can log into the system and perform transactions of their choice. The proposed system provides the user with a level of higher convenience, efficient and user friendly.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IOT, Biometric authentication, face recognition, OTP,ATM.

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Creative Commons Attribution 4.0 and The Open Definition