Swarm Intelligence in Internet of Medical Things: A Review (original) (raw)
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An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems
Computational Intelligence and Neuroscience
In today’s environment, electronics technology is growing rapidly because of the availability of the numerous and latest devices which can be deployed for monitoring and controlling the various healthcare systems. Due to the limitations of such devices, there is a dire need to optimize the utilization of the devices. In healthcare systems, Internet of things (IoT) based biosensors networking has minimal energy during transmission and collecting data. This paper proposes an optimized artificial intelligence system using IoT biosensors networking for healthcare problems for efficient data collection from the deployed sensor nodes. Here, an optimized tunicate swarm algorithm is used for optimizing the route for data collection and transmission among the patient and doctor. The fitness function of the optimized tunicate swarm algorithm used the distance, proximity, residual, and average energy of nodes parameters. The proposed method is attributed to the optimal CH chosen under TSA oper...
Next Generation IoMT enabled Smart HealthCare using Machine Learning Techniques
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2023
AI Enabled Internet of Medical Things (AIEIOMT) are playing a very crucial character in medical industry to increase exactness, productivity, and reliability of the electronics instruments. Recent advances and development in conceptual and design science , Technology and connectivity have led to the emergence of Artificial Intelligence and Internet of Things ( IoT) applications in many industries and with an emerging field with great development outlet potential in future years . Nowadays scientists are focusing to establish a digital-physical healthcare system by the interconnections of available medical resources, various healthcare services and digitally smart devices . This paper studies the impart of Technologies such as IoT and AI in healthcare. This analysis further reveals that the application of these technologies in disease diagnosis, forecasting, detection, and treatment, wearables and connectivity, patient care , sensor networks, identified gaps and future research directions related to technical design, acceptance, regulations for data security and privacy and systems efficacy and safety .The relevant impact factors in the blueprint and development of magnified healthcare systems are the related Research fields Artificial intelligence ( AI) , Big Data ( BD), and Internet of Things ( IoT). In the paper the concentration is focused on AI in IoT and healthcare system, which includes utilization and execution of AI methodologies many disciplines of healthcare. This paper work exhibits the principal areas of AI methodology in disease detection, prediction, medicine, robotic surgery, and personalized treatment. Furthermore AIEIOMT addresses numerous heath conditions like diabetes, activated parameters of biophysical supervisions along with subsistence system in decision making. As IoT has various converging domain but our focusing domain is the contribution of IOT in healthcare fields. The Internet of Medical Things has convergence with several domains but our research contribution correlated to AI and IoT in healthcare, previous contribution, ultra-modern contributions in Covid19 Epidemic, Opportunities, applications and subsequent challenges in terms of medical services in healthcare industry. AI Enabled Internet of Medical Things depute the medically interconnected communication devices and their integration in health network towards patient's health improvement. Even so, due to critical behavior of health-related systems, AIEIOMT still facing various challenges specially in terms of security, safety and reliability. In this literature we represent the comprehensive scientific research, new contributions in order to improve AIEIOMT by the usage of traditional methodologies furnished by cyber-physical systems. We outline remarkable experimental and realistic applications of standardization of medical devices for patient itself, guardians of patient, doctors, nurses and healthy people too. We also try to recognize Unexposed research oriented direction and trending potentials to solve uncharted research complications.
AI-Enabled Wearable Medical Internet of Things in Healthcare System: A Survey
Applied Sciences
Technology has played a vital part in improving quality of life, especially in healthcare. Artificial intelligence (AI) and the Internet of Things (IoT) are extensively employed to link accessible medical resources and deliver dependable and effective intelligent healthcare. Body wearable devices have garnered attention as powerful devices for healthcare applications, leading to various commercially available devices for multiple purposes, including individual healthcare, activity alerts, and fitness. The paper aims to cover all the advancements made in the wearable Medical Internet of Things (IoMT) for healthcare systems, which have been scrutinized from the perceptions of their efficacy in detecting, preventing, and monitoring diseases in healthcare. The latest healthcare issues are also included, such as COVID-19 and monkeypox. This paper thoroughly discusses all the directions proposed by the researchers to improve healthcare through wearable devices and artificial intelligence....
AI Enabled Internet of Medical Things
2021
AI Enabled Internet of Medical Things (AIEIOMT) are playing a very crucial character in medical industry to increase exactness, productivity, and reliability of the electronics instruments. Recent advances and development in conceptual and design science , Technology and connectivity have led to the emergence of Artificial Intelligence and Internet of Things ( IoT) applications in many industries and with an emerging field with great development outlet potential in future years . Nowadays scientists are focusing to establish a digital-physical healthcare system by the interconnections of available medical resources, various healthcare services and digitally smart devices . This paper studies the impart of Technologies such as IoT and AI in healthcare. This analysis further reveals that the application of these technologies in disease diagnosis, forecasting, detection, and treatment, wearables and connectivity, patient care , sensor networks, identified gaps and future research direc...
Internet of Things for Healthcare Technologies
Studies in Big Data, 2021
The series "Studies in Big Data" (SBD) publishes new developments and advances in the various areas of Big Data-quickly and with a high quality. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer science, physics, economics and life sciences. The books of the series refer to the analysis and understanding of large, complex, and/or distributed data sets generated from recent digital sources coming from sensors or other physical instruments as well as simulations, crowd sourcing, social networks or other internet transactions, such as emails or video click streams and other. The series contains monographs, lecture notes and edited volumes in Big Data spanning the areas of computational intelligence including neural networks, evolutionary computation, soft computing, fuzzy systems, as well as artificial intelligence, data mining, modern statistics and Operations research, as well as self-organizing systems. Of particular value to both the contributors and the readership are the short publication timeframe and the worldwide distribution, which enable both wide and rapid dissemination of research output.
IEEE Access
Healthcare services (HCS) based on cloud computing and the Internet of Things are a great opportunity for the development of medical information technology. Task scheduling in cloud computing is one of the most critical problems facing health care services, as it affects the time required to fulfill user requests and the cost and quality of service delivery. The proposed HCS model structure consists of major components such as user devices, user requests, cloud broker, IoT endpoints, and HCS cloud. This paper proposes a new method to improve task scheduling in healthcare services based on cloud computing in the IoT environment (cloud-IoT). Specifically, A hybrid optimization algorithm HPSOSSA is proposed that combines the best existing swarm intelligence algorithms and integrates the advantages of particle swarm optimization (PSO) and the Salp Swarm Algorithm (SSA). The proposed model was implemented using the Cloudsim simulation package run on Eclipse with specific parameters. The proposed hybrid algorithm was compared to the most popular optimization algorithms that were previously used, such as Ant Colony Optimization (ACO), PSO, SSA, and hybrid PSO-GA. The experimental results showed that HPSOSSA in all cases outperforms the other existing algorithms in terms of makespan, waiting time, and resource utilization. INDEX TERMS Cloud computing, HCS, swarm intelligence, Internet of Things, task scheduling, makespan.
Swarm intelligence and multi agent system in healthcare
2014 6th International Conference of Soft Computing and Pattern Recognition (SoCPaR), 2014
The domain of Healthcare is characterized by difficulty, dynamism and variety. In the 21 st century healthcare represents different challenges (the increasing cost of care and the growing of populations). For that, Agent Technology can provide better healthcare than the traditional medical system. In the hospital, several types of medical problems can be solved by agents. As examples of problems, which emerge in the hospital, we mention: collaboration between hospital wards, elaborations of diagnostics, the collection of information about patients etc. The adaptation of cooperative Multi Agent System (MAS) can solve these problems. In this regard, this study proposes a general architecture that integrates Swarm Intelligence into Multi Agent healthcare System in order to make care as efficient as possible.
Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress
Computational Intelligence and Neuroscience
Internet of Medical Thing (IoMT) is the most emerging era of the Internet of Thing (IoT), which is exponentially gaining researchers’ attention with every passing day because of its wide applicability in Smart Healthcare systems (SHS). Because of the current pandemic situation, it is highly risky for an individual to visit the doctor for every small problem. Hence, using IoMT devices, we can easily monitor our day-to-day health records, and thereby initial precautions can be taken on our own. IoMT is playing a crucial role within the healthcare industry to increase the accuracy, reliability, and productivity of electronic devices. This research work provides an overview of IoMT with emphasis on various enabling techniques used in smart healthcare systems (SHS), such as radio frequency identification (RFID), artificial intelligence (AI), and blockchain. We are providing a comparative analysis of various IoMT architectures proposed by several researchers. Also, we have defined various...
A Comprehensive Survey of the Internet of Things (IoT) and AI-Based Smart Healthcare
IEEE Access
Smart health care is an important aspect of connected living. Health care is one of the basic pillars of human need, and smart health care is projected to produce several billion dollars in revenue in the near future. There are several components of smart health care, including the Internet of Things (IoT), the Internet of Medical Things (IoMT), medical sensors, artificial intelligence (AI), edge computing, cloud computing, and next-generation wireless communication technology. Many papers in the literature deal with smart health care or health care in general. Here, we present a comprehensive survey of IoT-and IoMTbased edge-intelligent smart health care, mainly focusing on journal articles published between 2014 and 2020. We survey this literature by answering several research areas on IoT and IoMT, AI, edge and cloud computing, security, and medical signals fusion. We also address current research challenges and offer some future research directions. INDEX TERMS Internet of Things (IoT), Internet of Medical Things (IoMT), edge computing, cloud computing, medical signals, smart health care, artificial intelligence.
Biosensors
Artificial intelligence (AI) is a modern approach based on computer science that develops programs and algorithms to make devices intelligent and efficient for performing tasks that usually require skilled human intelligence. AI involves various subsets, including machine learning (ML), deep learning (DL), conventional neural networks, fuzzy logic, and speech recognition, with unique capabilities and functionalities that can improve the performances of modern medical sciences. Such intelligent systems simplify human intervention in clinical diagnosis, medical imaging, and decision-making ability. In the same era, the Internet of Medical Things (IoMT) emerges as a next-generation bio-analytical tool that combines network-linked biomedical devices with a software application for advancing human health. In this review, we discuss the importance of AI in improving the capabilities of IoMT and point-of-care (POC) devices used in advanced healthcare sectors such as cardiac measurement, ca...