International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 03 | Mar 2025
p-ISSN: 2395-0072
www.irjet.net
Blood Donation Application with Health Monitoring Using IOT Wearable’s and Machine Learning Model Aditya Bhalerao1, Anshul Ganvir2, Jitendra Pal3, Shreyas Khobragade4, Dr. Ashutosh Lanjewar5 U.G. Student, Department of Computer Science & Engineering, JD Engineering College, Fetri Nagpur, Maharashtra, India1,2,3,4 HOD, Department of Artificial Intelligence, JD Engineering College, Fetri Nagpur, Maharashtra, India5 -----------------------------------------------------------------------***----------------------------------------------------------------------Abstract: Internet of Things Integration (IoT)Wearables faces several challenges that can be addressed through technical interventions. Traditional blood donation systems often lack real-time health monitoring, personalized donor supply, and efficient data management, which can affect the safety and effectiveness of blood donation drives.
and machine learning in blood donation applications are a major advancement in health technology. This Overview Paper aims to comprehensively overview the current state and future possibilities for blood donation efficiency, security, and commitment. Traditional blood donation systems pose many challenges, including donor health monitoring, real-world data integration, personalised health insights, and data security. IoT devices address these challenges through donor health monitoring via portable sensors that pursue vital signs such as heart rate, temperature, and haemoglobin levels. Using these algorithms, blood donation applications can provide personalized health suggestions, predict potential health risks, and ensure general security and wells for donors. Donation application. You can also look into a variety of machines. A case study of the implementation of machine learning in successful blood donation is presented. In other words, the practical benefits and effects of these technologies over are the efficiency and security of the donation process. These include technical challenges related to the interoperability, accuracy, and reliability of machine learning models of various IoT devices, as well as critical concerns regarding data protection and security. This paper provides detailed explanations of these challenges and proposes potential solutions and future research and development directions.
The advent of IoT has revolutionized a variety of domains, including healthcare, by enabling seamless collection and data transfer through the networking sector. In connection with blood donations, IoT wearables such as heart rate monitors, pulse rates, and temperature sensors can continuously monitor the most important signs of a donor. These devices provide real data to ensure that donors are optimally healthy during the donation process and that medical staff will immediately draw attention to potential health issues. Machine learning, a subgroup of artificial intelligence, further enhances IoT skills in blood donation applications. By analyzing the vast amount of data collected by IoT devices, machine learning algorithms can provide personalized knowledge and health recommendations. These algorithms can predict potential health risks, suggest optimal donation times, and provide donors based on health data. This not only ensures the security of the donor but also increases the overall efficiency of the blood donation process. Despite this advancement, the integration of IoT and machine learning in blood donation systems is not without challenges. Issues like data protection and security, interoperability of various IoT devices, and accuracy of machine learning predictions must be addressed. It is of paramount importance to maintain regulatory trust and compliance in the health system to ensure that donor data is stored and transmitted safely. Furthermore, the development of standardized protocols for the interoperability of IoT devices can improve the reliability and effectiveness of these systems.
Keywords:
Blood Donation Applications, Health Monitoring Systems, IoT Wearables, Machine Learning Models, Real-time Health Monitoring Personalized Health Insights, Donor Safety, Data Integration
I.
INTRODUCTION
In recent years, the health sector has made considerable advances driven by the integration of technology, particularly the Internet of Things (IoT) and machine learning. In many applications of these technologies, blood donation systems are an important area where they can benefit from such innovations. While blood donation is a critical process that saves millions of lives each year, it
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Current trends in blood donation applications include the development of user-friendly interfaces that promote donor
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