A scalable cloud Platform for Active healthcare monitoring applications
- Authors: Balasubramanian, Venki , Stranieri, Andrew
- Date: 2015
- Type: Text , Conference paper
- Relation: 2014 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2014; Melbourne, Australia; 10th-12th December 2014 p. 93-98
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- Description: Continuous, remote monitoring of patients using wearable sensors can facilitate early detection of many conditions and can help to manage the growing healthcare crisis worldwide. A remote patient monitoring application consists of many emerging services such as wireless wearable sensor configuration, patient registration and authentication, collaborative consultation of doctors, storage and maintenance of electronic health record. The provision of these services requires the development and maintenance of a remote healthcare monitoring application (HMA) that includes a body area wireless sensor network (BASWN) and Health Applications (HA) to detect specific health issues. In addition, the deployment of HMAs for different hospitals is not easily scalable owing to the heterogeneous nature of hardware and software involved. Cloud computing overcomes this aspect by allowing simple and easy maintenance of ICT infrastructure. In this work, we report a real-time-like cloud based architecture known as Assistive Patient monitoring cloud Platform for Active healthcare applications (AppA) using a delegate pattern. The built AppA is highly scalable and capable of spawning new instances based on monitoring requirements from the health care providers, and are aligned with scalable economic models. © 2014 IEEE.
AppA : Assistive patient monitoring cloud platform for active healthcare applications
- Authors: Balasubramanian, Venki , Stranieri, Andrew , Kaur, Ranjit
- Date: 2015
- Type: Text , Conference paper
- Relation: 9th International Conference on Ubiquitous Information Management and Communication, ACM IMCOM 2015; Bali, Indonesia; 8th-10th January 2015
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- Description: Continuous, remote monitoring of patients using wearable sensors can facilitate early detection of many conditions and can help to manage the growing healthcare crisis worldwide. A remote patient monitoring application consists of many emerging services such as wireless wearable sensor configuration, patient registration and authentication, collaborative consultation of doctors, storage and maintenance of electronic health record. The provision of these services requires the development and maintenance of a remote healthcare monitoring application (HMA) that includes a body area wireless sensor network (BASWN) and Health Applications (HA) to detect specific health issues. In addition, the deployment of HMAs for different hospitals is not easily scalable owing to the heterogeneous nature of hardware and software involved. Cloud computing overcomes this aspect by allowing simple and easy maintenance of ICT infrastructure. In this work, we report a realtime- like cloud based architecture known as Assistive Patient monitoring cloud Platform for Active healthcare applications (AppA) using a delegate pattern. The built AppA is highly scalable and capable of spawning new instances based on the monitoring requirements from the health care providers, and is aligned with scalable economic models.
Energy-efficient priority-based routing scheme for the healthcare wireless sensor networks
- Authors: Saeed, Ather , Stranieri, Andrew , Dazeley, Richard
- Date: 2014
- Type: Text , Conference paper
- Relation: 9th WSEAS International Conference on Remote Sensing, Budapest 10/12/2103 pg 19-27
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- Description: Abstract: - In time-critical and data intensive applications, efficient acquisition of sensitive datasets is a challenge because of network congestion, void regions and node failures that commonly occur in wireless sensor networks (WSN), while monitoring the wellbeing of patients with serious medical conditions. The sensor devices attached to such patients are used for monitoring the vital signs of those with serious heart problems, Parkinson disease, Epilepsy and high blood pressure. This paper typically focuses on the reliable acquisition of datasets and provides a fault-tolerant priority based routing scheme with Dynamic Jumping (FTMPR-DJ) for the energy-efficient acquisition and dissemination of datasets. A new fault-tolerant scheme has been proposed that will significantly minimize data loss and network congestion and is well supported with extensive experiments to show effectiveness of the proposed routing scheme.