Volume 12 | Issue 10 |

 Abstract

Maternal mortality continues to be a significant challenge, particularly in developing countries where inadequate healthcare infrastructure and delayed access to services lead to high death rates. This review explores technological advancements that offer solutions to improve maternal health and prenatal care. Mobile health applications, such as pregnancy apps, provide real-time monitoring, gestational age tracking, and decision-making support for expectant mothers and their partners. Internet of Things (IoT) systems are used to monitor critical health parameters like blood pressure, temperature, and ECG signals, enabling remote care, particularly in regions with limited healthcare access Additionally, machine learning techniques, like the Naive Bayes algorithm, have proven effective in diagnosing mental health conditions such as anxiety and depression in pregnant women, achieving high accuracy rates. Wireless sensors further aid in continuously tracking fetal movements and maternal health, sending real-time alerts to medical professionals when abnormalities arise. Furthermore, Android-based systems have been developed to predict the risk of stunting in newborns by applying forward chaining techniques, providing preventive recommendations for high-risk pregnancies. Collectively, these technological innovations address key challenges in maternal healthcare, offering scalable, data-driven solutions for early diagnosis, continuous monitoring, and improved decision-making. This review emphasizes the potential of integrating mobile apps, IoT, machine learning, and data analytics to reduce maternal mortality and improve both maternal and fetal health outcomes globally, especially in resource-limited settings.

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 Keywords

Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning, Remote Health Monitoring, Alert system

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 Abstract

This paper proposes the development of an Internet of Things (IoT)-based real-time monitoring and control system for food safety management. By leveraging IoT sensors and devices throughout the food production and distribution process, this system aims to continuously monitor food safety parameters, providing immediate data to prevent contamination and ensurecompliance with safety standards. In response to the critical need for enhanced food safety measures, this concept paper proposes the implementation of IoT (Internet of Things) technology to advance food safety through real-time monitoring and control systems. The global food industry faces significant challenges in ensuring food safety throughout the supply chain, including inef- ficiencies, delays in response to potential hazards, and increased risks of contamination. Traditional methods of monitoring and controlling food safety often lack real-time capabilities and are prone to human error. The proposed solution focuses on introducing an IoT-based system for real-time monitoring of critical food safety parameters such as temperature, humidity, and the presence of pathogens.

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 Keywords

Food Safety, Monitoring, Real Time, Authority.

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 Abstract

The Internet of Things (IoT) plays a very Important role in improving cultivation methods for greenhouses ,gardening and providing farmers with relevant information to make decisions for optimal yields. In this project we create an Iot Based plant moniotoring system based on the IoT concept that remotely provides users with information related to temperature, humidity, and soil moisture intensity for monitoring plant conditions. The IoT-based smart plant monitoring system is designed to enhance plant care and cultivation using Internet of Things (IoT) technology. It integrates various sensors such as temperature, humidity, soil moisture, and light intensity sensors to collect real-time data on environmental conditions. The system can also automate watering based on the moisture levels in the soil, ensuring plants get the right amount of water. By providing timely alerts and useful insights, the IoT Smart Plant Monitoring System makes plant care easier and more efficient.

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 Keywords

Plant Monitoring,Sensors,IoT,Smart Plant Care,Automation

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 Abstract

The emergence of Industry 4.0 has revolutionized manufacturing processes through the integration of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), and big data analytics. This abstract presents the development of an Industry 4.0-based robotic arm designed to enhance flexibility, efficiency, and precision in industrial operations. Unlike traditional robotic systems that are limited to fixed tasks, this robotic arm utilizes real- time data and adaptive algorithms to respond to dynamic production environments. By lever- aging IoT connectivity, the robotic arm can communicate with other machines, enabling seam-less integration into smart factory ecosystems. Additionally, AI algorithms allow for predictive maintenance and improved decision-making capabilities, ensuring optimal performance and re- deuced downtime. This innovative approach not only addresses the challenges of customization and scalability in modern manufacturing but also sets the foundation for a more intelligent and responsive industrial landscape. The proposed robotic arm serves as a critical component in advancing automation and promoting sustainable practices in the era of Industry 4.0.

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 Keywords

Hand Gesture, Voice Recognisation,Camera, Controller, Communication

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Context: Musculoskeletal discomfort is an increasingly prevalent issue among gym instructors, reflecting the physical demands and high-intensity nature of their profession. Gym instructors, who play a crucial role in guiding individuals towards their fitness goals, often face a range of musculoskeletal challenges due to the repetitive and strenuous activities inherent in their job. Their daily routines involve demonstrating various exercises, adjusting client's postures, and frequently handling heavy equipment, all of which place considerable strain on their bodies. Aims: The aim of this study was to find out the musculoskeletal discomfort among the gym instructor using Cornell Musculoskeletal Discomfort Questionnaire. Methods and Material: The present cross-sectional study was conducted at South Mumbai regions (Byculla, curry road, chinchpokli, Dadar) on 160 Gym instructors. Data was collected by interview method using Cornell Musculoskeletal Discomfort Questionnaire. Statistical analysis : Descriptive statistical data analysis was done using graphical method by Microsoft excel software. Results: It was found that 95% of participants reported musculoskeletal discomfort and 5% had no discomfort. It was seen that 69% had lower back discomfort followed by shoulder area 16% , knee 14% , wrist and neck 10% each and lastly by foot contributing to 2% of discomfort in gym instructors. Conclusions: The study conducted that musculoskeletal discomfort among gym instructors is found to be as high as 95% and hence it can be reduced by improving the ergonomics of gym instructors' posture and public awareness related to risk factors associated with improper posture gym training. Thus, low back pain followed by shoulder pain and knee pain are the most common sites of pain reported by gym instructors. Index Terms - Musculoskeletal discomfort, Gym instructors, Cornell musculoskeletal discomfort Questionnaire

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Musculoskeletal discomfort, Gym instructors, Cornell musculoskeletal discomfort Questionnaire

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 Abstract

This study utilizes the Homotopy Perturbation Method (HPM), a straightforward and precise semi-analytical approach, to address the nonlinear energy equation governing a straight rectangular fin. The thermal conductivity and surface emissivity are treated as temperature-dependent, along with a constant source of internal heat generation. The results include temperature distribution, efficiency, and optimal dimensionless parameters, all of which are practical and relevant for real-world fin applications. Additionally, the study demonstrates that this method yields more accurate results compared to other techniques reported in the literature

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 Keywords

sink temperature, Homotopy perturbation method, efficiency, variable surface emissivity

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 Abstract

The Hindustani musical instrument tabla is made up of two drums, right handed "daya" and the left handed "baya". The various tones generated from this instrument is determined by the way in which the strokes are being made and its mode of applying . The syahi component fabricated on the playing surface of the drums determines the quality of the sound generated. The significance of the "syahi" preparation and the method of playing in contributing the musical tones of the instrument were investigated. Detailed analysis of the tones using digital audio workstation at various scales with the respective frequencies gave an inner sight into the scientific basis of the quality of the music generated from this percussion instrument. An attempt has been made to characterize the sound formed from tabla in terms of the pitch generated at all the scales from F to F'' using different tabla of varying syahi character.

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 Keywords

Percussion Instrument, Tabla, Strokes, Tones , Syahi , Digital audio work station

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 Abstract

Independence and interdependence are indispensable ingredients to lead a meaningful and satisfying life, and especially in married life interdependence plays a more important role than independence. This paper investigates various aspects of interapersonal relationships. that emerge between the Indian immigrant couple, Shukumar and Shoba, in Jhumpa Lahiri's short story " A Temporary Matter," approaching the topic from different view points and depths of significance. A chasm is created between them for no fault of them. That is, both of them are not responsible for the death of their child and yet the division widens in due course of time as none of them is willing to look at the problem from the viewpoint of the partner. It is lack of interdependence that mars their married life. And Jhumpa Lahiri's conclusion of the story gives room for different interpretations.

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immigrant, Indian-American identity, self-interest, intrapersonal relationships, interpersonal relationships, commitments, marital disharmony

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Traffic Problems is a growing problem in many cities. This system addresses this by introducing a movable divider that can be adjusted based on real-time traffic data. Sensors embedded in the road collect traffic data, which is then transmitted to the cloud platform via IoT. The cloud analyzes the data and sends instructions to the divider mechanism, adjusting its position to optimize traffic flow. The algorithm for divider movement considers factors like traffic volume on each side and historical data to predict future patterns. It prioritizes balanced traffic flow but allows for adjustments to create a dedicated lane for detected ambulances. The proposed system offers a dynamic solution for traffic management. It improves traffic flow during peak hours and ensures expedited passage for emergency vehicles, potentially saving lives. The system can be further enhanced by integrating with traffic light control systems and incorporating machine learning algorithms for even more intelligent traffic management.

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 Keywords

Smart Traffic System, Automatic road Divider, Iot , Deep learning, Density of Traffic

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 Abstract

This study examines the satisfaction levels of rural customers in North Kerala regarding the use of digital banking services. With the growing penetration of smartphones and internet connectivity in rural areas, digital banking has become an accessible alternative to traditional banking methods. This study focuses on identifying customer satisfaction, key challenges, and socio-economic factors influencing the adoption and usage of digital banking among rural customers. A structured questionnaire was distributed among 400 respondents from rural regions in North Kerala, with a particular focus on socio-economic factors like age, gender, education, and occupation. Data analysis includes ANOVA and Kendall's coefficient to assess satisfaction levels and problems faced by customers. The results reveal that factors such as lack of internet literacy, fear of fraud, and poor network connectivity continue to be major hurdles. The findings highlight the need for enhanced awareness, better infrastructure, and customized digital banking solutions for rural customers. The study also suggests that banks must focus on customer education and personalized support to improve satisfaction levels. Recommendations for future research include broader geographical studies and comparative analyses across different demographic segments.

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 Keywords

Digital Banking, Rural Customers, Satisfaction, Problems

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