scholarly journals Blockchain and IPFS Integrated Framework in Bilevel Fog-Cloud Network for Security and Privacy of IoMT Devices

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Abolfazl Mehbodniya ◽  
Rahul Neware ◽  
Sonali Vyas ◽  
M. Ranjith Kumar ◽  
Peter Ngulube ◽  
...  
Keyword(s):  
Real Time ◽  
Health Monitoring ◽  
Data Security ◽  
Patient Data ◽  
Biological Data ◽  
Security And Privacy ◽  
Complex Data ◽  
Number Of Patients ◽  
Wide Range ◽  
Smart Health

Internet of Medical Things (IoMT) has emerged as an integral part of the smart health monitoring system in the present world. The smart health monitoring deals with not only for emergency and hospital services but also for maintaining a healthy lifestyle. The industry 5.0 and 5/6G has allowed the development of cost-efficient sensors and devices which can collect a wide range of human biological data and transfer it through wireless network communication in real time. This led to real-time monitoring of patient data through multiple IoMT devices from remote locations. The IoMT network registers a large number of patients and devices every day, along with the generation of huge amount of big data or health data. This patient data should retain data privacy and data security on the IoMT network to avoid any misuse. To attain such data security and privacy of the patient and IoMT devices, a three-level/tier network integrated with blockchain and interplanetary file system (IPFS) has been proposed. The proposed network is making the best use of IPFS and blockchain technology for security and data exchange in a three-level healthcare network. The present framework has been evaluated for various network activities for validating the scalability of the network. The network was found to be efficient in handling complex data with the capability of scalability.

scholarly journals Traffic sensor health monitoring using spatiotemporal graphical modeling

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Linjiang Wu ◽  
Chao Liu ◽  
Tingting Huang ◽  
Anuj Sharma ◽  
Soumik Sarkar
Keyword(s):  
Health Status ◽  
Real Time ◽  
Sensor Network ◽  
Health Monitoring ◽  
Series Data ◽  
Spatiotemporal Pattern ◽  
Graphical Modeling ◽  
Traffic Sensors ◽  
Wide Range ◽  
Sensor Health

Accurate traffic sensor data is essential for traffic operation management systems and acquisition of real-time traffic surveillance data depends heavily on the reliability of the traffic sensors (e.g., wide range detector, automatic traffic recorder). Therefore, detecting the health status of the sensors in a traffic sensor network is critical for the departments of transportation as well as other public and private entities, especially in the circumstances where real-time decision is required. With the purpose of efficiently determining the sensor health status and identifying the failed sensor(s) in a timely manner, this paper proposes a graphical modeling approach called spatiotemporal pattern network (STPN). Traffic speed and volume measurement sensors are used in this paper to formulate and analyze the proposed sensor health monitoring system and historical time-series data from a network of traffic sensors on the Interstate 35 (I-35) within the state of Iowa is used for validation. Based on the validation results, we demonstrate that the proposed approach can: (i) extract spatiotemporal dependencies among the different sensors which leads to an efficient graphical representation of the sensor network in the information space, and (ii) distinguish and quantify a sensor issue by leveraging the extracted spatiotemporal relationship of the candidate sensor(s) to the other sensors in the network.

NEW CHALLENGES FACING INTEGRATIVE BIOLOGICAL SCIENCE IN THE POST-GENOMIC ERA

2006 ◽  
Vol 14 (02) ◽  
pp. 275-293 ◽  
Author(s):  
CHRISTOPHER S. OEHMEN ◽  
TJERK P. STRAATSMA ◽  
GORDON A. ANDERSON ◽  
GALYA ORR ◽  
BOBBIE-JO M. WEBB-ROBERTSON ◽  
...  
Keyword(s):  
Paradigm Shift ◽  
Large Scale ◽  
Experimental Testing ◽  
Spatial Scales ◽  
Geographical Area ◽  
Biological Data ◽  
Biological Research ◽  
Complex Data ◽  
Discovery Research ◽  
Wide Range

The future of biology will be increasingly driven by the fundamental paradigm shift from hypothesis-driven research to data-driven discovery research employing the growing volume of biological data coupled to experimental testing of new discoveries. But hardware and software limitations in the current workflow infrastructure make it impossible or intractible to use real data from disparate sources for large-scale biological research. We identify key technological developments needed to enable this paradigm shift involving (1) the ability to store and manage extremely large datasets which are dispersed over a wide geographical area, (2) development of novel analysis and visualization tools which are capable of operating on enormous data resources without overwhelming researchers with unusable information, and (3) formalisms for integrating mathematical models of biosystems from the molecular level to the organism population level. This will require the development of algorithms and tools which efficiently utilize high-performance compute power and large storage infrastructures. The end result will be the ability of a researcher to integrate complex data from many different sources with simulations to analyze a given system at a wide range of temporal and spatial scales in a single conceptual model.

scholarly journals A Real-Time Health Monitoring System for Remote Cardiac Patients Using Smartphone and Wearable Sensors

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Priyanka Kakria ◽  
N. K. Tripathi ◽  
Peerapong Kitipawang
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Health Monitoring ◽  
Data Security ◽  
High Speed ◽  
Low Cost ◽  
Wearable Sensors ◽  
Healthcare Services ◽  
Cardiac Patients ◽  
The Cost

Online telemedicine systems are useful due to the possibility of timely and efficient healthcare services. These systems are based on advanced wireless and wearable sensor technologies. The rapid growth in technology has remarkably enhanced the scope of remote health monitoring systems. In this paper, a real-time heart monitoring system is developed considering the cost, ease of application, accuracy, and data security. The system is conceptualized to provide an interface between the doctor and the patients for two-way communication. The main purpose of this study is to facilitate the remote cardiac patients in getting latest healthcare services which might not be possible otherwise due to low doctor-to-patient ratio. The developed monitoring system is then evaluated for 40 individuals (aged between 18 and 66 years) using wearable sensors while holding an Android device (i.e., smartphone under supervision of the experts). The performance analysis shows that the proposed system is reliable and helpful due to high speed. The analyses showed that the proposed system is convenient and reliable and ensures data security at low cost. In addition, the developed system is equipped to generate warning messages to the doctor and patient under critical circumstances.

scholarly journals A review of internet of medical things (IoMT) - based remote health monitoring through wearable sensors: a case study for diabetic patients

2020 ◽  
Vol 20 (1) ◽  
pp. 414
Author(s):  
Omar AlShorman ◽  
Buthaynah AlShorman ◽  
Mahmood Al-khassaweneh ◽  
Fahad Alkahtani
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Health Monitoring ◽  
Security And Privacy ◽  
Diabetic Patients ◽  
Time Data ◽  
Remote Health Monitoring ◽  
Internet Of Medical Things ◽  
Remote Health

<span>The latest advances and trends in information technology and communication have a vital role in healthcare industries. </span><span>Theses advancements led to the Internet of Medical Things (IoMT) which provides a continuous, remote and real-time monitoring of patients. The IoMT </span><span>architectures still face many challenges related to the bandwidth, communication protocols, big data and data volume, flexibility, reliability, data management, data acquisition, data processing and analytics availability, cost effectiveness, data security and privacy, and energy efficiency. The goal of this paper is to find </span><span>feasible </span><span>solutions to enhance the healthcare living facilities using remote health monitoring (RHM) and IoMT. In addition, the enhancement of the prevention, prognosis, diagnosis and treatment abilities using IoMT and RHM is also discussed. </span><span>A case study of monitoring the vital signs of diabetic patients using real-time data processing and IoMT is also presented</span><span>. </span>

scholarly journals CYBER SECURITY AND PRIVACY INTERNAL ATTACKS MEASUREMENTS THROUGH BLOCK CHAIN

2021 ◽  
Vol 9 (1) ◽  
pp. 1033-1044
Author(s):  
Dr. K. SAI MANOJ, Dr. P. S. AITHAL
Keyword(s):  
Real Time ◽  
Cyber Security ◽  
Data Security ◽  
Critical Role ◽  
Security And Privacy ◽  
New Technique ◽  
Efficient Manner ◽  
Unauthorized Access ◽  
Block Chain ◽  
Security Concern

Cyber Security plays critical role in privacy and now a day’s its assumesanimportanttask in the field of data security. Security concern Block chain gives best fruitful results to overcome unauthorized access and internal counter attacks operations| we propose new technique to reduce and identify internal privacy leaks and attack to measure with efficient manner. These technique very useful to cyber internal avoid attacks with accountability way and real-time environment operations. 

scholarly journals A Smart Way of Monitoring Health Using IOT-A Study

2020 ◽  
Vol 5 (9) ◽  
pp. 946-947
Author(s):  
Pratheksha Rai N
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Health Monitoring ◽  
Wireless Sensor ◽  
Smart Devices ◽  
Healthcare Applications ◽  
Health Monitoring System ◽  
The People ◽  
Wide Range ◽  
Smart Health

Health is the important key for any living. The monitoring of one’s health is so important in today’s busy world ,that most of the people run out of time when they get to know the disease, which actually is not fatal. Smart Health Monitoring system gives you a track of your health, making your work easier to know the data of your health without running every time to hospital. This paper is a study about Smart health Monitoring system using Internet of things (IOT).Internet of things plays An very prominent role in wide range of healthcare applications and it also serves as a catalyst for the healthcare. Smart devices and wireless sensor networks are used here for the analysis of different health parameters in real-time.

scholarly journals Integration of Blockchain with Connected and Autonomous Vehicles: Vision and Challenge

2022 ◽  
Vol 14 (1) ◽  
pp. 1-10
Author(s):  
Tooska Dargahi ◽  
Hossein Ahmadvand ◽  
Mansour Naser Alraja ◽  
Chia-Mu Yu
Keyword(s):  
Data Protection ◽  
Intelligent Transportation Systems ◽  
Data Security ◽  
Autonomous Vehicles ◽  
Personal Data ◽  
Transportation Systems ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Blockchain Technology ◽  
Wide Range

Connected and Autonomous Vehicles (CAVs) are introduced to improve individuals’ quality of life by offering a wide range of services. They collect a huge amount of data and exchange them with each other and the infrastructure. The collected data usually includes sensitive information about the users and the surrounding environment. Therefore, data security and privacy are among the main challenges in this industry. Blockchain, an emerging distributed ledger, has been considered by the research community as a potential solution for enhancing data security, integrity, and transparency in Intelligent Transportation Systems (ITS). However, despite the emphasis of governments on the transparency of personal data protection practices, CAV stakeholders have not been successful in communicating appropriate information with the end users regarding the procedure of collecting, storing, and processing their personal data, as well as the data ownership. This article provides a vision of the opportunities and challenges of adopting blockchain in ITS from the “data transparency” and “privacy” perspective. The main aim is to answer the following questions: (1) Considering the amount of personal data collected by the CAVs, such as location, how would the integration of blockchain technology affect transparency , fairness , and lawfulness of personal data processing concerning the data subjects (as this is one of the main principles in the existing data protection regulations)? (2) How can the trade-off between transparency and privacy be addressed in blockchain-based ITS use cases?

scholarly journals Security Framework for IoT Based Real-Time Health Applications

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 719
Author(s):  
Aamir Hussain ◽  
Tariq Ali ◽  
Faisal Althobiani ◽  
Umar Draz ◽  
Muhammad Irfan ◽  
...  
Keyword(s):  
Real Time ◽  
Health Systems ◽  
Health Monitoring ◽  
Security And Privacy ◽  
Sensor Data ◽  
Monitoring Systems ◽  
Area Network ◽  
Security Framework ◽  
Health Monitoring Systems ◽  
End To End

The amazing fusion of the internet of things (IoT) into traditional health monitoring systems has produced remarkable advances in the field of e-health. Different wireless body area network devices and sensors are providing real-time health monitoring services. As the number of IoT devices is rapidly booming, technological and security challenges are also rising day by day. The data generated from sensor-based devices need confidentiality, integrity, authenticity, and end-to-end security for safe communication over the public network. IoT-based health monitoring systems work in a layered manner, comprising a perception layer, a network layer, and an application layer. Each layer has some security, and privacy concerns that need to be addressed accordingly. A lot of research has been conducted to resolve these security issues in different domains of IoT. Several frameworks for the security of IoT-based e-health systems have also been developed. This paper introduces a security framework for real-time health monitoring systems to ensure data confidentiality, integrity, and authenticity by using two common IoT protocols, namely constrained application protocol (CoAP) and message query telemetry transports (MQTT). This security framework aims to defend sensor data against the security loopholes while it is continuously transmitting over the layers and uses hypertext transfer protocols (HTTPs) for this purpose. As a result, it shields from the breach with a very low ratio of risk. The methodology of this paper focuses on how the security framework of IoT-based real-time health systems is protected under the tiers of CoAP and HTTPs. CoAP works alongside HTTPs and is responsible for providing end-to-end security solutions.

scholarly journals Real-Time Remote Healthcare and Telemedicine Application Model using Ontology Enabled Clustering of Biomedical & Clinical Documents

2020 ◽  
Vol 9 (3) ◽  
pp. 73-79
Keyword(s):  
Real Time ◽  
Health Monitoring ◽  
Patient Data ◽  
Sensor Nodes ◽  
Remote Health Monitoring ◽  
Time Saving ◽  
Swarm Optimization ◽  
Remote Healthcare ◽  
Chicken Swarm Optimization ◽  
Remote Health

Remote health monitoring has become a hot topic research due to its multi-dimensional benefits to the society. This paper is aimed at developing a novel remote health monitoring model through wireless sensor networks to ensure efficient telemedicine process. The proposed model, Real-time Remote Healthcare and Telemedicine (RRHT) utilizes the concept of model based design to provide low cost and time saving efficiency. First the low power consuming sensor nodes are placed at specified body points with facility to monitor and reduce the power consumption at each stage of the designed model. These nodes collect the patient data and transmit them in wireless medium through the gateway where the data are combined to form documents/notes. Autonomous optimized routing algorithm is employed at this stage for transmission through efficient wireless paths to the processor connected at the hospitals or health centers. At the processor, the transmitted patient data documents are clustered using ontology enabled clustering models using chicken swarm optimization (CSO) and genetic chicken swarm optimization (GCSO). The clustered results are comparatively analyzed with the previous patient database and to determine the change in health readings. Based on these findings, the suitable medication details along with advice on hospital visits are suggested by the decision module and are sent to the physicians or medical experts for approval and further diagnosis. The performance analysis shows that the proposed RRHT system with GCSO clustering is highly reliable and accurate with better speed and lower cost. These results also prove that the RRHT significantly improved the healthcare application through the utilization of better strategies in document clustering of patient data.

Sign in / Sign up

Export Citation Format

Share Document