Smart IoMT Framework for Supporting UAV Systems with AI

Shankar, N. Gowri; Nallakaruppan, Musiri Kailasanathan; Ravindranath, Vaishali; Bhagavath, Bhuvanagiri Prahal

doi:10.3390/electronics12010086

Cited by 9 publications

(4 citation statements)

References 22 publications

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“…The effective and reliable implementation of UAVs requires the continuous proposal of new solutions or updating and improvement of the underlying algorithms. For example, in a study by Shankar et al [58], a platform that enables UAVs to transmit medical data effectively, ensuring reliable communication, was successfully developed. The framework also incorporates AI algorithms to enable intelligent decision-making processes for the UAV systems, allowing for the efficient real-time analysis of medical data collected through internet of medical things (IoMT) devices, leading to improved diagnosis and treatment options [58].…”

Section: Healthcare Logisticsmentioning

confidence: 99%

“…For example, in a study by Shankar et al [58], a platform that enables UAVs to transmit medical data effectively, ensuring reliable communication, was successfully developed. The framework also incorporates AI algorithms to enable intelligent decision-making processes for the UAV systems, allowing for the efficient real-time analysis of medical data collected through internet of medical things (IoMT) devices, leading to improved diagnosis and treatment options [58]. Also, a major part of the analyzed experimental research [56,57,60,61,65,73] deals with the solution and optimization of various routing and path planning problems, thus allowing for the whole drone system to minimize the travel time, reduce energy consumption, and improve overall efficiency.…”

Section: Healthcare Logisticsmentioning

confidence: 99%

See 1 more Smart Citation

Challenges for the Routine Application of Drones in Healthcare: A Scoping Review

De Silvestri,

Capasso,

Gargiulo

et al. 2023

Drones

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Uncrewed aerial vehicles (UAVs), commonly known as drones, have emerged as transformative tools in the healthcare sector, offering the potential to revolutionize medical logistics, emergency response, and patient care. This scoping review provides a comprehensive exploration of the diverse applications of drones in healthcare, addressing critical gaps in existing literature. While previous reviews have primarily focused on specific facets of drone technology within the medical field, this study offers a holistic perspective, encompassing a wide range of potential healthcare applications. The review categorizes and analyzes the literature according to key domains, including the transport of biomedical goods, automated external defibrillator (AED) delivery, healthcare logistics, air ambulance services, and various other medical applications. It also examines public acceptance and the regulatory framework surrounding medical drone services. Despite advancements, critical knowledge gaps persist, particularly in understanding the intricate interplay between technological challenges, the existing regulatory framework, and societal acceptance. This review highlights the need for the extensive validation of cost-effective business cases, the development of control techniques that can address time and resource savings within the constraints of real-life scenarios, the design of crash-protected containers, and the establishment of corresponding tests and standards to demonstrate their conformity.

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Section: Healthcare Logisticsmentioning

confidence: 99%

Section: Healthcare Logisticsmentioning

confidence: 99%

Challenges for the Routine Application of Drones in Healthcare: A Scoping Review

De Silvestri,

Capasso,

Gargiulo

et al. 2023

Drones

View full text Add to dashboard Cite

show abstract

“…Koch et al [57] used the ArduCopter plugin in their UAV-based framework. A remote health monitoring system (HMS) based on UAVs is presented in the study [156]. Using IoMT technology [157], it takes readings of vital signs and transmits them wirelessly to doctors for remote analysis.…”

Section: Tools Libraries Framework For Building Ai-integrated Uav Sys...mentioning

confidence: 99%

A Comprehensive Survey on Artificial Intelligence for Unmanned Aerial Vehicles

Sai,

Garg,

Jhawar

et al. 2023

IEEE Open J. Veh. Technol.

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Artificial Intelligence(AI) is an emerging technology that finds its application in various industries. Integration of AI in Unmanned Aerial Vehicles(UAVs) can lead to tremendous growth in the field of UAVs by improving flight safety and efficiency. Machine learning algorithms can enable UAVs to make real-time decisions in complex environments and reach the optimal solution that aims to fulfill a mission's requirements within the hardware constraints such as battery and payload. Several recent works in UAVs employed a variety of machine learning algorithms to enhance the capabilities of UAVs and assist them. Although several reviews have been published examining the various aspects of AI for UAVs, they are all pertaining to particular applications or technologies. Addressing this research gap, we present a comprehensive and diversified review to enable researchers to analyze the current and future requirements and develop the latest solutions utilizing AI. We have classified the reviewed works based on three different classification schemes: 1) application scenario-based, 2) AI algorithm-based, and 3) AI training paradigm-based. We have also presented a compilation of frameworks, tools, and libraries used in AI-integrated UAV systems. We identified that the integration of AI in UAVs has a wide array of applications ranging from path planning to resource allocation. We have observed that Reinforcement Learning based algorithms are more often used in AI-integrated UAV systems than other AI algorithms. Further, our findings reveal that UAV frameworks employing federated learning and other distributed machine learning paradigms are quickly emerging. Furthermore, we also have put forth several challenges and potential applications of AI-integrated UAV systems.

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“…The IoMT is based on a network of connected medical devices, sensors, and information systems, allowing for the collection and transmission of health data automatically and continuously. These devices can include anything from vital signs monitors and medication delivery devices to fitness tracking sensors and home monitoring devices [3,4]. The information collected by these devices can be transmitted to health professionals, hospitals, or information systems in the cloud for analysis and storage [5].…”

Section: Introductionmentioning

confidence: 99%

Framework for a Secure and Sustainable Internet of Medical Things, Requirements, Design Challenges, and Future Trends

2023

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The framework presented in this article provides a guide for designing secure and sustainable internet of medical things (IoMT) solutions. The main objective is to address the challenges related to safety and sustainability in the medical field. The critical conditions driving these challenges are identified, and future trends in the field of IoMT are discussed. To assess the effectiveness of the proposed framework, a case study was carried out in a private medical clinic. In this study, an IoMT system was implemented to monitor patients’ vital signs, even when they were not in the clinic. The positive results demonstrated that the implemented IoMT system met the established security and sustainability requirements. The main statistical findings of the case study include the real-time monitoring of the vital signs of the patients, which improved the quality of care and allowed for the early detection of possible complications. In addition, medical devices such as the blood pressure monitor, pulse oximeter, and electrocardiograph were selected, proving safe, durable, and energy and maintenance efficient. These results were consistent with previous research that had shown the benefits of IoMT in remote monitoring, the early detection of health problems, and improved medical decision-making.

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Smart IoMT Framework for Supporting UAV Systems with AI

Cited by 9 publications

References 22 publications

Challenges for the Routine Application of Drones in Healthcare: A Scoping Review

Challenges for the Routine Application of Drones in Healthcare: A Scoping Review

A Comprehensive Survey on Artificial Intelligence for Unmanned Aerial Vehicles

Framework for a Secure and Sustainable Internet of Medical Things, Requirements, Design Challenges, and Future Trends

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