Study and implementation of IOT based smart healthcare system

Gupta, Naina; Saeed, Hera; Jha, Shambhu Kumar; Chahande, Manisha; Pandey, Sujata

doi:10.1109/icoei.2017.8300718

Cited by 7 publications

(3 citation statements)

References 1 publication

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“…The routing protocol will govern the exchange of data between routers and gives information, enabling route selection between nodes [ 89 , 90 ]. In a smart healthcare system, we collect very sensitive patient data using small and ultralow power IoMT devices [ 91 , 92 ]. Hence, the mentioned challenges cannot be tackled within the implanted/wearable IoMT devices, however, they can be balanced in the network and protocol designing techniques with the consideration of effective network topology, power conservation, and channel effectiveness.…”

Section: Challenges Within a Smart Healthcare System To Be Considered...mentioning

confidence: 99%

Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress

Srivastava

Routray

Ahmad

et al. 2022

Computational Intelligence and Neuroscience

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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 health domains of IoMT, including the analysis of different sensors with their application environment, merits, and demerits. In addition, we have figured out key protocol design challenges, which are to be considered during the implementation of an IoMT network-based smart healthcare system. Considering these challenges, we prepared a comparative study for different data collection techniques that can be used to maintain the accuracy of collected data. In addition, this research work also provides a comprehensive study for maintaining the energy efficiency of an AI-based IoMT framework based on various parameters, such as the amount of energy consumed, packet delivery ratio, battery lifetime, quality of service, power drain, network throughput, delay, and transmission rate. Finally, we have provided different correlation equations for finding the accuracy and efficiency within the IoMT-based healthcare system using artificial intelligence. We have compared different data collection algorithms graphically based on their accuracy and error rate. Similarly, different energy efficiency algorithms are also graphically compared based on their energy consumption and packet loss percentage. We have analyzed our references used in this study, which are graphically represented based on their distribution of publication year and publication avenue.

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Section: Challenges Within a Smart Healthcare System To Be Considered...mentioning

confidence: 99%

Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress

Srivastava

Routray

Ahmad

et al. 2022

Computational Intelligence and Neuroscience

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“…Additionally, maintaining an optimal humidity level within the organ container is also crucial [31]. Utilizing IoT-enabled sensor technology can effectively address a significant concern in organ transportation, specifically the risk of organ contamination during the transfer process from the donor to the recipient [26][27][28][29]. Smart contracts proposed for this purpose relay real-time data from IoT sensors to the decentralized application, enabling authorized stakeholders to access updates on the organ's condition and status during shipment.…”

Section: Objective Of the Studymentioning

confidence: 99%

A Decentralized Application for Managing Organ Donation, Transportation, and Transplantation Processes through Blockchain, Smart Contracts, and Internet of Things Integration

Bawa,

Singh

2024

Preprint

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Currently organ donation and transplantation management systems are designed using either centralized architecture or decentralized architecture. The centralized architectures lack transparency for the stakeholders thereby causing unethical allocation of organs and unauthorized alterations to organ waiting lists. Additionally, centralized models are susceptible to data vulnerability through third-party interference, ultimately eroding trust in the system. On the other hand, the existing blockchain-based decentralized models suffer from high Ether consumption during deployment. Furthermore, both models fail to provide stakeholders with access to vital information regarding the condition of organs during their transportation from the donor to the recipient. This includes factors like temperature, humidity level, and light exposure inside the organ container, and orientation and vibration of the container. This absence of supervision increases the risk of contamination of organs during transit, highlighting a crucial gap in safe organ transportation. The paper presents a decentralized application powered by blockchain and Internet of Things technologies for managing stakeholder registration, efficient patient-donor matching, organ retrieval, transportation, and transplantation. The proposed application ensures complete data security, process transparency, and a trustful environment for stakeholders. Furthermore, the application ensures safe organ transportation and a reduction in the risk of organ contamination. A comparative analysis with existing blockchain-based organ management applications has been presented. Notable improvements in Ether consumption with a deployment cost of approximately 0.00582850 Ether, reduced gas utilization of 446104.333 units, process transparency, organ monitoring, and the assurance of safe transportation within the proposed application have been observed.

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“…To tackle this challenge, resource allocation policy should skilfully implemented at IoT enabled networks. Another novel contribution are LPWANs in expansion of IoT enabled systems to its apex [7][8] [9]. Forthcoming licensedband standards, named as NB-IoT are primus competitor of unlicensed -band standards, notably fit for healthcare systems [12].…”

Section: Introductionmentioning

confidence: 99%

Efficient load balancing Adaptive BNBKnapsack Algorithm for Edge computing to improve performance of network

Nagle,

Kumar

2023

ICST Transactions on Scalable Information Systems

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INTRODUCTION: In present days, Automation of everything has become essential. Internet of things (IoT) play an important role among all medical advances of IT. In this paper, feasible solutions are discussed to compare and design better healthcare systems. A thorough investigation and survey of suitable approaches were done to select IoT based systems in hospitals consisting of various high precision sensors. OBJECTIVES: The challenge healthcare system face is to manage the real time patient’s data with high accuracy. Second challenge is at fog devices level to manage the load distribution to all sensors with limited availability of bandwidth. METHODS: This paper summarizes the selection criterions of suitable load balancing algorithms to reduce energy consumption and computational cost of fog devices and increase the network usage that are supposed to be used in IoT based healthcare systems. According to the survey BNBKnapack algorithm has been selected as best suitable approach to analyze the overall performance of fog devices and results are also verify the same. RESULTS: Comparative analysis of Overall performance of fog devices has been proposed with using SJF algorithm and Adaptive BNBKnapsack algorithm. It has been observed by analysing system performance, which is found as best among other load balancing algorithm Adaptive BNBKnapsack is successfully reduce the energy consumption by (99.29%), computational cost by (98.34%) and increase the network usage by (99.95%) of system CONCLUSION: It has been observed by analysing system performance, Adaptive BNBKnapsack Load balancing is successfully able to reduce the computational cost and energy consumption also increase the network usage of the fog network. The performance of the system is found best among other load balancing algorithm.

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Study and implementation of IOT based smart healthcare system

Cited by 7 publications

References 1 publication

Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress

Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress

A Decentralized Application for Managing Organ Donation, Transportation, and Transplantation Processes through Blockchain, Smart Contracts, and Internet of Things Integration

Efficient load balancing Adaptive BNBKnapsack Algorithm for Edge computing to improve performance of network

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