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Lightweight Algorithm for MQTT Protocol to Enhance Power Consumption in healthcare Environment

Journal on Internet of Things 2022年第1期4卷 21-33页

作者： Anwar D.Alhejaili Omar H.Alhazmi Department of Computer Science Taibah UniversityMadinahSaudi Arabia

Internet of things(iot)is used in various fields such as smart cities,smart home,manufacturing industries,and *** application in healthcare has many advantages and *** of its most common protocols is Message Queue Telemetry Transport(MQTT).MQTT protocol works as a publisher/subscriber which is suitable for iot devices with limited *** of the drawbacks of MQTT is that it is easy to *** default security provided by MQTT during user authentication,through username and password,does not provide any type of data encryption,to ensure confidentiality or *** paper focuses on the security of iot healthcare over the MQTT protocol,through the implementation of lightweight generating and key exchange *** research contribution of this paper is *** first one is to implement a lightweight generating and key exchange algorithm for MQTT protocol,with the key length of 64 bits through OMNET++*** second one is to obtain lower power consumption from some existing ***,the power consumption through using the proposed algorithm is 0.78%,1.16%,and 1.93% of power for 256 bits,512 bits,and 1024 *** the other hand,the power consumption without using the encryption is 0.25%,0.51%,and 1.03% for the same three payloads length.

关键词： Lightweight algorithm iot healthcare MQTT power consumption

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Integration of Digital Twins and Artificial Intelligence for Classifying Cardiac Ischemia

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Journal on Artificial Intelligence 2023年第1期5卷 195-218页

作者： Mohamed Ammar Hamed Al-Raweshidy Department of Mechanical and Aerospace Brunel University LondonUxbridgeUB83PHUK Department of Electrical and Electronic Brunel University LondonUxbridgeUB83PHUK

Despite advances in intelligent medical care,difficulties *** to its complicated governance,designing,planning,improving,and managing the cardiac system remains ***,including intelligent monitoring,feedback systems,and management practises,is *** platforms cannot deliver lifelong personal health management *** accuracy in patient crisis warning *** frequent,direct interaction between healthcare workers and patients is *** medical systems and intelligent information systems are not *** study introduces the Advanced Cardiac Twin(ACT)model integrated with Artificial Neural Network(ANN)to handle real-time monitoring,decision-making,and crisis *** is used to create an iot platform that accepts patient sensor *** these data sets into MATLAB allows display and analysis.A myocardial ischemia research examined Health Condition Tracking’s(HCT’s)*** the case study,75%of the training sets(Xt),15%of the verified data,and 10%of the test data were *** set feature values(Xt)were given with the ***,Validation,and Testing accuracy rates were 99.9%,99.9%,and 99.9%,*** research accuracy was 99.9%.The proposed HCT system and Artificial Neural Network(ANN)model gather historical and real-time data to manage and anticipate cardiac issues.

关键词： Digital twin hybrid twin cardiac twin cardiac ischemia iot healthcare AI artificial intelligence machine learning

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