[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120815-en":3,"doc-seo-120815-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120815,8796095360427,"Lucas Martin","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",6,"Technology","Application of IoT Framework for Prediction of Heart Disease using Machine Learning","Prognosis of illnesses is a difficult global challenge, particularly for adults aged twenty years and above who face increased risk from chronic conditions. The work proposes using an IoT-based approach to evaluate threat factors related to heart disease, aiming to support diagnosis and prevention through machine learning. It addresses the gap between machine learning architects, healthcare researchers, patients, and physicians, and highlights how IoT-embedded devices and modern diagnostic and medical research can enable effective predictive care.","Application ofIoT Framework for Prediction of Heart Disease using Machine Learning  \nSatyaprakash Swain1,*,Naliniprava Behera2, Anil KumarSwain3, Suvendra Kumar Jayasingh4,*, Kumar Janardan Patra5,*,Binod Kumar Pattanayak6,*, Mihir Narayan Mohanty7,*, Kodanda Dhar Naik8, Sefali Surabhi Rout9  \n1,6 Department of Computer Science & Engineering,Institute of Technical Education & Research(ITER), SoA University, Odisha, India  \n2,3 School of Computer Engineering, KIIT University, Bhubaneswar, BPUT, Odisha, India  \n4,5 Department of Computer Science & Engineering,Institute of Management and Information Technology, Cuttack, BPUT, Odisha, India  \n7 Department of Electronics and Communication Engg, Institute of Technical Education & Research(ITER), SoA University, Odisha, India  \n8 Department of Computer Science & Engineering,Gandhi Institute of Engineering and Technology University, Gunupur, Odisha, India  \n9 Department of Computer Science & Engineering,Parala Maharaja Engineering College, Brahmapur, Odisha, India  \n1,*[satyaimit@gmail.com](satyaimit@gmail.com),[2](2 nalini.behera@gmail.com)[ nalini.behera@gmail.com](2 nalini.behera@gmail.com), [3](3 anilkumarswain@gmail.com)[ anilkumarswain@gmail.com](3 anilkumarswain@gmail.com),  \n4,*[sjayasingh@gmail.com](sjayasingh@gmail.com),5,*[janardanpatra1997@gmail.com](janardanpatra1997@gmail.com),6,*[binodpattanayak@soa.ac.in](binodpattanayak@soa.ac.in) ,7,*[mihirmohanty@soa.ac.in](mihirmohanty@soa.ac.in),  \n[8](8 kodandadhar.naik@giet.edu)[ kodandadhar.naik@giet.edu](8 kodandadhar.naik@giet.edu),[9](9 sefalisurabhi4@gmail.com)[ sefalisurabhi4@gmail.com](9 sefalisurabhi4@gmail.com)  \nAbstract—Prognosis of illnesses is a difficult problem these days throughout the globe. Elder people of twenty years and over are taken into consideration to be laid low with this sickness now a days. For example, human beings having HbA1c level more than 6.5% are diagnosed as infected with diabetic diseases. This paper uses IoT to evaluate threat factors which have been similar to heart diseases which are not treated properly. Diagnosis, prevention of heart disease may be done by use of machine learning (ML) . There has been an extensive disconnect among Machine Learning architects, health care researchers, patients and physicians in their technology. This paper intends to perform an in-intensity evaluation on Machine Learning to make us of new advance technologies. Latest advances within the development ofIoT implanted devices and other medicine delivery gadgets, disease diagnostic methods and other medical research have considerably helped human beings diagnosed heart diseases. New soft computing models can be helpful for remedy of various heart diseases. The Food and Drug Administration (FDA) employs several particularly creative thoughts to get their capsules to the client. Artificial Neural Community offers a first-rate chance to deal with heart diseases with advance IoT and cloud applications.  \nKeywords-IoT, Machine Learning, GPS, Human to Machine Interaction, NBM, RF,LMT,DT.  \nI. INTRODUCTION  \nIoT is shaping the way we live our lives. Today IoT is being used extensively to lessen the burden on humans. It is a vision to connect all devices with the power of internet always learning and always growing. It is a non-standard computing device connected wirelessly to network and has ability to transmit data. We use it in several sectors like health sector, farming home automation, industry etc. Example in healthcare industry it helps to detect the equipment and also patient asset such as wheelchairs, available of ventilators etc. any equipment with IoT sensor then it can track easily. Mainly two types of IoT devices are planted inside the physical objects they are either switch (that sends command to things) or a sensor (that collect and send data elsewhere) . It transmits and receives data over wireless network with limited human intervention, realtime data collect and analysis, no need of Human to Human (","cbCaieAwYdEiW24w","https://ap.wps.com/l/cbCaieAwYdEiW24w","pdf",636103,1,9,"English","en",105,"# Introduction\n## IoT Layered Architecture\n## Common IoT Devices for Health Care Application","[{\"question\":\"How does the proposed approach use IoT for heart disease prediction?\",\"answer\":\"The paper uses IoT to collect and evaluate risk-related data, then applies machine learning to support diagnosis and prevention of heart disease.\"},{\"question\":\"What is the IoT layered architecture described in the paper?\",\"answer\":\"It presents a 4-stage architecture: application layer, data processing layer, network layer, and sensing layer.\"},{\"question\":\"Which types of IoT devices are highlighted for healthcare use?\",\"answer\":\"The paper discusses IoT sensors and devices deployed in physical objects, emphasizing data collection and transmission with limited human intervention for healthcare monitoring.\"}]","Application of IoT Framework for Prediction of Heart Disease using Machine Learning | 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does the proposed approach use IoT for heart disease prediction?","Question",{"text":76,"@type":77},"The paper uses IoT to collect and evaluate risk-related data, then applies machine learning to support diagnosis and prevention of heart disease.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What is the IoT layered architecture described in the paper?",{"text":81,"@type":77},"It presents a 4-stage architecture: application layer, data processing layer, network layer, and sensing layer.",{"name":83,"@type":74,"acceptedAnswer":84},"Which types of IoT devices are highlighted for healthcare use?",{"text":85,"@type":77},"The paper discusses IoT sensors and devices deployed in physical objects, emphasizing data collection and transmission with limited human intervention for healthcare 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