The demand for reliable health monitoring systems has surged in today's health-conscious society. Body temperature monitoring is crucial for preserving health and preventing infectious disease outbreaks. In this study an Arduino uno hardware board with a touchless temperature sensor is proposed to detect elevated body temperature, indicating fever and early signs of illness. The system prioritizes real-time health surveillance, accessibility, and usability, blending seamlessly with normal life. Arduino's versatility allows the system to function covertly, uphold privacy and autonomy, and foster wellbeing. The goal is to highlight the system's ability to function covertly, uphold privacy and autonomy, and foster wellbeing. This technology exemplifies the synergy between personal wellness and contemporary technologies, offering a useful and adaptable fever detection solution for various contexts, including homes and public areas.

Climate change, biodiversity loss, soil degradation, water scarcity, and food insecurity are just a few of the issues threatening India's food system's sustainability. We require a more sustainable approach to food production and consumption in order to address these issues. We can influence lasting change in the food system by using the method to problem-solving known as "design thinking." This research paper aims to explore how design thinking can be used to design a better food system in India. We conducted a literature review of relevant studies, reports, and case studies and analyzed the findings to identify common themes and best practices. Our analysis revealed that design thinking can be used to design a better food system in India in several ways, including user-entered design, cross-sector collaboration, innovation and experimentation, and systems thinking. We present a case study of a design thinking approach to addressing food waste in India and discuss the implications and potential of design thinking for designing a better food system in India.

The goal of this study is to assess the many benefits and drawbacks that Metaverse offers to education as a platform for technology teaching and learning. Look at how consumers’ interest in using the Metaverse education application platform has changed, as well as how they may improve their services, boost usage, and understand how to manage and use older Metaverse technology in the classroom. The Edu Metaverse is a sizable collection of numerous technologies that transform education in ways that have never been seen before. Integration and multidimensional interactions, an inclusive learning environment that help people learn, enhance their skills, and become skilled workers are all aspects of EduMetaverse that have contributed to this transition. Smart learning is a collaborative and collaborative technique that employs the most recent technology to achieve learning results, as opposed to traditional classroom teaching approaches. To improve students’ learning, it is necessary to figure out how to develop an intelligent learning model supported by Edu-Metaverse. In such a scenario, Edu-Metaverse should be addressed with an intelligent learning environment, copious teaching resources, and AI assessment. In order to motivate students to engage in in-depth learning and self-development, this study proposes an intelligent learning model backed by the EduMetaverse with immersive, varied interaction, high levels of cooperation, and ownership. recognising critical thinking abilities and being intelligent in a virtual learning environment.

This study focuses on the use of computer vision technology and motion detection sensors to create an intelligent system that recognizes human presence in monitored spaces. The system uses a relay module for automation and control of household appliances while sensing motion detection, operated by an ESP32 microcontroller. This innovative solution addresses two major issues in home automation: reliable human presence recognition and seamless appliance control. The research merges a camera-based vision system with motion sensors, comparing motion and vision-based identification. The ESP32 microcontroller improves motion detection precision and context awareness by integrating motion sensors and computer vision technologies. The integration of a camera module allows real-time analysis and recognition of human presence, reducing false alarms. The relay module also enables automated control of home appliances, synchronizing and feedbacking operations with sensed human presence. The dynamic adaptation of the system improves user convenience and energy efficiency.

The study explores the use of internet of things (IoT) devices in agriculture to improve sustainable practices and environmental concerns. It uses the ESP8266 microcontroller and the Blynk platform to create a revolutionary plant health monitoring and automated care system. The system is designed to handle continuous monitoring and plant maintenance in various environmental conditions. Sensors measuring light, temperature, humidity, and soil moisture are strategically placed to receive real-time data. The ESP8266 microcontroller analyzes this information and links it to the Blynk cloud for accessibility via mobile or web applications. The system is effective in monitoring ideal growing conditions, such as soil moisture and weather conditions. Automated care elements like irrigation and supplemental lighting have been shown to improve plant growth and health. The study contributes to smart farming by offering an affordable and easy way to automate and monitor plant health, demonstrating how IoT technologies can enhance agricultural practices, conserve resources, and enable remote management of plant ecosystems.

For an effective business, a decent location is required where there is less competition for similar kinds of businesses. In the proposed work, venue data is used to recommend good locations for users to open new venues in any neighborhood by selecting the finest locality in the city. Suppose, a person lives in the neighborhood of a city where amenities like hotels, malls, and restaurants are nearby. Due to a job opportunity, the person has to shift to another neighborhood in that city. So, isn't it good that the person can find neighborhoods that are similar to his/her current neighborhood? So, the proposed work also helps to discover similar neighborhoods. Data Science tools, Foursquare, K-medoids (Unsupervised Clustering Algorithm) are applied to segregate the neighborhoods into clusters and to obtain useful outcomes.

To the extent that people experience the scientific and technological revolution, they do not try to understand its adverse effects. An example of this is the use of mobile phones. About 19 crore people are using connectivity in India the most. A natural environment is the antidote to pollution. As far it is concerned we can sustain 100 percent environmental management in all aspects naturally. Whether building a new house, applying for a squatter's license, or seeking admission in colleges, the government should make it compulsory to pass an exam on environmental awareness. Completion of this course is also required to purchase and renew any license. Awareness seminars and programs should be held for those who are polluting the environment. These ideas should come up with process plans suitable for joining the uneducated population

For the purpose of minimising and managing project delays, effective planning and scheduling are essential elements of construction projects. Globalisation has led to an increase in the scale and complexity of construction projects. With the help of project management software, the quantity of paperwork and time required for such initiatives can be reduced. A warning system must be accessible throughout the project to alert the organisation to potential achievements and failures. Today's market offers a variety of computer software applications for project management, including MSP, Primavera P6, and others. Primavera has made it simple to assess the real progress of a construction project to the expected pace of the task. The project management tool Primavera P6 gathers, documents, monitors, regulates, and publishes data on project performance. Planning, allocating, and scheduling resources for a G+4 residential development are all part of this project. This study highlights the value of scheduling and interferes with the software by working on a construction project for a commercial building. This paper effectively demonstrates all the crucial steps, such as generating an EPS, developing a WBS, connecting tasks in accordance with their dependency and resource availability, and determining the Critical Path.

Metaheuristics have already shown useful in solving difficult problems in a broad range of fields over the last several decades. This accomplishment spurs the research group to create new, more successful heuristics and stimulates interest in this area of study. However, recent research has concentrated on constructing innovative algorithms but instead of consolidating the body of current knowledge. A further obstacle to the advancement of the area is the lack of formalization and precision in the identification, design, and development of combinatorial optimization issues and metaheuristics. The basic ideas and issues in this domain are discussed, and formalism is suggested for organizing, designing, and coding combinatorial optimization issues and metaheuristics. We think these contributions might help the discipline advance and make metaheuristics more capable of solving problems comparable to these other machine learning methods.

The researchers in this study analyzed the Supply Chain Management (SCM) strategies of 25 different businesses in India. These businesses ranged from retail chains and logistics providers to FMCG manufacturers and hotels to power plants and automotive manufacturers and their suppliers. The research was undertaken in 2005 via on-site visits, in-depth interviews with both middle and upper-level managers, and secondary data collection. Logistics, transportation, forming strategic alliances, and information and communication technology (ICT) were all areas of concentration. The investigation revealed both commonalities and distinctions in SCM practices among the sampled businesses, as well as new developments and potential trouble spots. In addition, suggestions were made for further investigation.

Today, more events are being recorded more than ever before as technology advance and consumers are incentivized to provide data to firms’ databases. However, since file storage technology have advanced, it is now far more expensive to evaluate, choose, and discard historical material than it is to let it collect. On just one finger, the abundance of data which has been stored must have greatly widened the possibilities to correspond and analyses them, and on the other, the modest excitement that data processing and information retrieval engendered in the early 1980s has been supplemented by a rampant exuberance. But is this really all that great? Based on an examination of quality variables, this report gives a risk evaluation.

Due to technological advancements, the healthcare industry has witnessed the emergence of innovative solutions, and one such solution is the healthcare Chatbot. The primary objective of this paper is to create a healthcare Chatbot capable of offering medical assistance to patients. The healthcare Chatbot serves as an AI-based conversational program designed to assist both patients and healthcare providers. The proposed Chatbot, named “HELPI,” functions as a round-the-clock healthcare provider. It utilizes Natural Language Processing (NLP) and Machine Learning (ML) algorithms such as decision trees to analyse user-provided symptoms and accurately detect specific illnesses or diseases. Subsequently, it offers appropriate healthcare recommendations and suggests relevant medications. This broadens HELPI’s capability to address various healthcare-related concerns. In essence, HELPI aims to alleviate the burden on healthcare providers by providing an alternative platform for basic medical advice and support. The success of the HELPI Chatbot lays the foundation for future enhancements. Additional features, such as appointment scheduling, guidance on lifestyle modifications, and medication reminders, could be incorporated to further enhance the Chatbot’s functionality.

Skin illness affects a large percentage of the world's population. The proposed study proposed a deep learning-based model for skin disease predication, In the traditional system it was time taking to predict the result and the accuracy is not accurate, Different machine learning methods can be used to classify skin disorders. In this study, we used machine learning algorithms to categories skin disease classes using ensemble approaches, and then used a feature selection method to compare the findings produced. Specialist can detect the disease type with the help of a web-based framework which is developed in Python Django frame- work. In the proposed study, we present a novel approach to detect the skin disease. Here we have used Support Vector Machine (SVM) Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) classifiers to identify the disease. Specialist need to upload the image and Deep learning algorithms will predict the disease and display the accuracy. The proposed model is easy to use, but it also provides a higher level of accuracy than previous methods. As a result of this model, we were able to achieve a 95% accuracy rate in the diagnosis of various skin conditions. The proposed system provides a state of art accuracy for early skin disease detection

In the chronology of the age of the world, compared to other species, the human race is a creeping spring. However, the human race has acquired the power to move mountains, Move Rivers, penetrate living cells and transform them due to their super-intelligence. This same creative knowledge also indirectly propagates many influences through the milk of biodiversity. Plants cannot live in this flower world today. Birds cannot survive today. Animals cannot live with humans today. Why, microbial species are still unsustainable for humans. But if the human species does not exist in this world, other forms of life can certainly live - not just live, but very happily. Therefore, the human race is not an essential part of this world. Mankind is a thread in nature's spider web. This thread cannot stand alone. If separated, it will flyaway like a sponge.

Stress is a concerning issue in today’s world. Stress in pregnancy harms both the development of children and the health of pregnant women. As a result, assessing the stress levels of working pregnant women is crucial to aid them in developing and growing professionally and personally. In the past, many machine-learning (ML) and deep-learning (DL) algorithms have been made to predict the stress of women. It does, however, have some problems, such as a more complicated design, a high chance of misclassification, a high chance of making mistakes, and less efficiency. With these considerations in mind, our article will use a deep-learning model known as the deep recurrent neural network (DRNN) to predict the stress levels of working pregnant women. Dataset preparation, feature extraction, optimal feature selection, and classification with DRNNs are all included in this framework. Duplicate attributes are removed, and missing values are filled in during the preprocessing of the dataset.

Predicting the stress levels of working professionals is one of the most time-consuming and difficult research topics of current day. As a result, estimating working professionals' stress levels is critical in order to assist them in growing and developing professionally. Numerous machine learning and deep learning algorithms have been developed for this purpose in previous papers. They do, however, have some disadvantages, including increased design complexity, a high rate of misclassification, a high rate of errors, and decreased efficiency. To address these concerns, the purpose of this research is to forecast the stress levels of working professionals using a sophisticated deep learning model called the Deep Recurrent Neural Network (DRNN). The model proposed here comprises dataset preparation, feature extraction, optimal feature selection, and classification using DRNNs. Preprocessing the original dataset removes duplicate attributes and fills in missing values.

Stress is one of the most significant issues in our society because it has been a serious reason for many health-related problems and a giant loss for firms, offices, and universities. Regular high mental workloads and fast technological development, which end up in constant modification and also the want for adaptation, build the matter a lot more serious at the geographic point. This examination intends to investigate the extent of Stress Recognition Research with the help of a bibliometric review. The Scopus database was utilized to acquire data about Stress Recognition. Subject names with keywords titles, abstracts in human Stress Recognition studies were used as a kind of perspective for retrieval of the search results. Search result extraction was utilizing the VOSviewer software. Later, the outcomes of bibliometric mapping were investigated further. A sum of 500 research articles was found in the Scopus information base got to in 2021. After examining we shortlisted 231 articles. There was a significant expansion in the number of publications on Stress recognition from 2019, 2020, and 2021. Among all nations, the USA contributed the foremost publication. In the meantime, the watchwords Physiology, Machine Learning, and Human ended up being the territory's most generally examined. Through VOS Viewer we tend to analyze what numbers of articles are published regarding Stress Recognition and its relationships to a subject area. This review actually will give a reference for more analysis associated with the Stress Recognition happening