The Internet of Medical Things(IoMT)is an online device that senses and transmits medical data from users to physicians within a time interval.In,recent years,IoMT has rapidly grown in the medicalfield to provide heal...The Internet of Medical Things(IoMT)is an online device that senses and transmits medical data from users to physicians within a time interval.In,recent years,IoMT has rapidly grown in the medicalfield to provide healthcare services without physical appearance.With the use of sensors,IoMT applications are used in healthcare management.In such applications,one of the most important factors is data security,given that its transmission over the network may cause obtrusion.For data security in IoMT systems,blockchain is used due to its numerous blocks for secure data storage.In this study,Blockchain-assisted secure data management framework(BSDMF)and Proof of Activity(PoA)protocol using malicious code detection algorithm is used in the proposed data security for the healthcare system.The main aim is to enhance the data security over the networks.The PoA protocol enhances high security of data from the literature review.By replacing the malicious node from the block,the PoA can provide high security for medical data in the blockchain.Comparison with existing systems shows that the proposed simulation with BSD-Malicious code detection algorithm achieves higher accuracy ratio,precision ratio,security,and efficiency and less response time for Blockchain-enabled healthcare systems.展开更多
With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:e...With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:exponential growth in geometric and attribute data,risking data explosion,and low data utilization due to insufficient semantic association among multi-source data across projects and domains.This paper addresses the challenge of reducing system complexity via scenario-driven methods while achieving deep semantic integration of cross-domain BIM data.It proposes an ontology-based“Digital Theater”framework that defines data boundaries based on scenario requirements and employs dynamic trimming strategies to reduce complexity.By combining a simplified data standard with a multi-domain fusion ontology model,the framework constructs scenario-based data integration rules for semantic alignment.An adaptive relational database with object storage design further supports efficient engineering data storage and utilization.The proposed method significantly reduces the complexity of data processing,enabling the integrated application of multi-domain data at a lower cost while enhancing the decision-support capabilities of BIM data.This framework demonstrates potential for application in diverse scenarios,supporting engineering digitalization and smart city development.展开更多
基金Taif University Researchers Supporting Project Number(TURSP-2020/98),Taif University,Taif,Saudi Arabia.
文摘The Internet of Medical Things(IoMT)is an online device that senses and transmits medical data from users to physicians within a time interval.In,recent years,IoMT has rapidly grown in the medicalfield to provide healthcare services without physical appearance.With the use of sensors,IoMT applications are used in healthcare management.In such applications,one of the most important factors is data security,given that its transmission over the network may cause obtrusion.For data security in IoMT systems,blockchain is used due to its numerous blocks for secure data storage.In this study,Blockchain-assisted secure data management framework(BSDMF)and Proof of Activity(PoA)protocol using malicious code detection algorithm is used in the proposed data security for the healthcare system.The main aim is to enhance the data security over the networks.The PoA protocol enhances high security of data from the literature review.By replacing the malicious node from the block,the PoA can provide high security for medical data in the blockchain.Comparison with existing systems shows that the proposed simulation with BSD-Malicious code detection algorithm achieves higher accuracy ratio,precision ratio,security,and efficiency and less response time for Blockchain-enabled healthcare systems.
基金supported by the National Key Research and Development Program of China“Comprehensive Application Demonstration of Self-developed BIM Platform in the Full Life Cycle of Engineering Construction”(Grant No.2024YFC3809700)。
文摘With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:exponential growth in geometric and attribute data,risking data explosion,and low data utilization due to insufficient semantic association among multi-source data across projects and domains.This paper addresses the challenge of reducing system complexity via scenario-driven methods while achieving deep semantic integration of cross-domain BIM data.It proposes an ontology-based“Digital Theater”framework that defines data boundaries based on scenario requirements and employs dynamic trimming strategies to reduce complexity.By combining a simplified data standard with a multi-domain fusion ontology model,the framework constructs scenario-based data integration rules for semantic alignment.An adaptive relational database with object storage design further supports efficient engineering data storage and utilization.The proposed method significantly reduces the complexity of data processing,enabling the integrated application of multi-domain data at a lower cost while enhancing the decision-support capabilities of BIM data.This framework demonstrates potential for application in diverse scenarios,supporting engineering digitalization and smart city development.
