A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system

2018 ◽  
Vol 82 ◽  
pp. 375-387 ◽  
Author(s):  
Gunasekaran Manogaran ◽  
R. Varatharajan ◽  
Daphne Lopez ◽  
Priyan Malarvizhi Kumar ◽  
Revathi Sundarasekar ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Smart Healthcare ◽  
Alerting System ◽  
Healthcare Monitoring ◽  
Data Ecosystem

Big Data Analytics of IoT-Based Cloud System Framework: Smart Healthcare Monitoring Systems

2022 ◽  
pp. 181-208
Author(s):  
Joseph Bamidele Awotunde ◽  
Rasheed Gbenga Jimoh ◽  
Roseline Oluwaseun Ogundokun ◽  
Sanjay Misra ◽  
Oluwakemi Christiana Abikoye
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cloud System ◽  
Monitoring Systems ◽  
System Framework ◽  
Smart Healthcare ◽  
Healthcare Monitoring

Mobile Big Data

2016 ◽  
pp. 138-158
Author(s):  
Shivom Aggarwal ◽  
Abhishek Nayak
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Value Chain ◽  
Mobile Technologies ◽  
Complex Concept ◽  
Current Trends ◽  
Mobile Big Data ◽  
Challenges And Opportunities ◽  
New Challenges ◽  
Data Ecosystem

Mobile technologies have given rise to tremendous amounts of data in real-time, which can be unstructured and uncertain. This growth can be attributed as Mobile Big Data and provides new challenges and opportunities for innovation. This chapter attempts to define the concept of Mobile Big Data, provide description of various sources of Mobile Big Data and discuss SWAI (Sources Warehousing Analytics Insights) model of Big Data processing. To understand this complex concept, it is important to visualize the Big Data ecosystem, respective players. Moreover, mobile computing, Internet of things, and other associated technologies have been discussed in light of marketing and communications based applications. The current trends in Mobile Big Data and associated value chain help us understand where the next frontiers of innovation are and how one can create value. This is linked to the future aspects of the Mobile Big Data and evolution of technologies from now onwards.

Mobile Big Data

2016 ◽  
pp. 1796-1816
Author(s):  
Shivom Aggarwal ◽  
Abhishek Nayak
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Value Chain ◽  
Mobile Technologies ◽  
Complex Concept ◽  
Current Trends ◽  
Mobile Big Data ◽  
Challenges And Opportunities ◽  
New Challenges ◽  
Data Ecosystem

Mobile technologies have given rise to tremendous amounts of data in real-time, which can be unstructured and uncertain. This growth can be attributed as Mobile Big Data and provides new challenges and opportunities for innovation. This chapter attempts to define the concept of Mobile Big Data, provide description of various sources of Mobile Big Data and discuss SWAI (Sources Warehousing Analytics Insights) model of Big Data processing. To understand this complex concept, it is important to visualize the Big Data ecosystem, respective players. Moreover, mobile computing, Internet of things, and other associated technologies have been discussed in light of marketing and communications based applications. The current trends in Mobile Big Data and associated value chain help us understand where the next frontiers of innovation are and how one can create value. This is linked to the future aspects of the Mobile Big Data and evolution of technologies from now onwards.

scholarly journals Analysis on E-Healthcare Monitoring System with Iot and Big Patient Data

2021 ◽  
Vol 10 (5) ◽  
pp. 97-102
Author(s):  
Deepa V. ◽  
Rajeswari, K.
Keyword(s):  
Big Data ◽  
Monitoring System ◽  
Healthcare System ◽  
Health Monitoring ◽  
New Technologies ◽  
Patient Data ◽  
Similar Data ◽  
Time Consumption ◽  
Smart Healthcare ◽  
Healthcare Monitoring

Internet of Things (IoT) technology helped the development of healthcare from face-to-face consulting to the telemedicine. Smart healthcare system in IoT environment monitored the patient basic health signs such as heart rate, body temperature, and hospital room condition in real-time applications. The IoT and big data is an important challenge in many fields including smart healthcare systems due to its significance. Big data is employed to analyse the huge volume of data. Big data are significantly used in healthcare technique to determine the normal and abnormal patient condition. The doctors are easily analysed the patient condition in a short time. This system is very easy to design and use. It is employed to enhance the present healthcare system which preserves the lot of lives from death. Healthcare monitoring system in hospitals has experienced large development and portable healthcare monitoring systems with new technologies. Connected healthcare is an essential solution for hospital to record and analyse the patient data and to save money. The clustering and classification methods are used in existing methods. The clustering method is employed to group the similar data. The classification method is utilized to classify the patient data. A lot of healthcare technique was introduced by many researchers ranging from diagnosis to treatment and prevention on efficient e-health monitoring system. But, the accuracy level was not improved and time consumption was not reduced by existing techniques. In order to address these problems, different methods and techniques were reviewed for performing the e-healthcare monitoring system with big data. The machine learning techniques are used for efficient diseased patient health monitoring through the effective performance of feature selection, clustering and patient classification with increase the accuracy and minimum time consumption. The results are is performed using on different factors such as clustering accuracy, clustering time, classification accuracy, classification time, and error rate with respect to number of patient data.

Security in Smart Healthcare System: A Comprehensive Survey

2017 ◽  
Vol 7 (10) ◽  
pp. 39
Author(s):  
P. Jeyadurga ◽  
S. Ebenezer Juliet ◽  
I. Joshua Selwyn ◽  
P. Sivanisha
Keyword(s):  
Secure Communication ◽  
Smart Cities ◽  
Healthcare Systems ◽  
Internet Security ◽  
Security Risk ◽  
System A ◽  
Smart Healthcare ◽  
Comprehensive Survey ◽  
Healthcare Monitoring ◽  
The Internet Of Things

The Internet of things (IoT) is one of the emerging technologies that brought revolution in many application domains such as smart cities, smart retails, healthcare monitoring and so on. As the physical objects are connected via internet, security risk may arise. This paper analyses the existing technologies and protocols that are designed by different authors to ensure the secure communication over internet. It additionally focuses on the advancement in healthcare systems while deploying IoT services.

A Seven-Layered Model Architecture, Network Model, Protocol Stack, Security, Application, Issues and Challenges in Internet of Vehicle

2020 ◽  
Vol 14 ◽  
Author(s):  
Intyaz Alam ◽  
Sushil Kumar ◽  
Pankaj Kumar Kashyap
Keyword(s):  
Internet Of Things ◽  
Network Model ◽  
Transportation Systems ◽  
Vehicle Speed ◽  
Protocol Stack ◽  
Seamless Integration ◽  
Communication Architecture ◽  
Smart Transportation ◽  
Smart Healthcare ◽  
Essential Components

Background: Recently, Internet of Things (IoT) has brought various changes in the existing research field by including new areas such as smart transportation, smart home facilities, smart healthcare, etc. In smart transportation systems, vehicles contain different components to access information related to passengers, drivers, vehicle speed, and many more. This information can be accessed by connecting vehicles with Internet of Things leading to new fields of research known as Internet of Vehicles. The setup of Internet of Vehicle (IoV) consists of many sensors to establish a connection with several other sensors belonging to different environments by exploiting different technologies. The communication of the sensors faces a lot of challenging issues. Some of the critical challenges are to maintain security in information exchanges among the vehicles, inequality in sensors, quality of internet connection, and storage capacity. Objective: To overcome the challenging issues, we have designed a new framework consisting of seven-layered architecture, including the security layered, which provides seamless integration by communicating the devices present in the IoV environment. Further, a network model consisting of four components such as Cloud, Fog, Connection, and Clients has been designed. Finally, the protocol stack which describes the protocol used in each layer of the proposed seven-layered IoV architecture has been shown. Methods: In this proposed architecture, the representation and the functionalities of each layer and types of security have been defined. Case studies of this seven-layer IoV architecture have also been performed to illustrate the operation of each layer in real-time. The details of the network model including all the elements inside each component, have also been shown. Results: We have discussed some of the existing communication architecture and listed a few challenges and issues occurring in present scenarios. Considering these issues, which is presently occurring in the existing communication architecture. We have developed the seven-layered IoV architecture and the network model with four essential components known as the cloud, fog, connection, and clients. Conclusion: This proposed architecture provides a secure IoV environment and provides life safety. Hence, safety and security will help to reduce the cybercrimes occurring in the network and provides good coordination and communication of the vehicles in the network.

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