M.Sc. Thesis Defense Session

in

Computer Engineering (Hardware)

Tittle:

Design and Evaluation of Smart Health Networks for Elderly and Disabled Community

By

Alireza Jafari

Supervisor:

Dr. Ghassemian

Advisor:

Dr. Parissa Taheri (MD)

Examination Committee:

Dr. Ali Movaghar – Dr. Maghsoud Abbaspour – Dr. Islam Nazemi

Location: Room 117, Faculty of Computer Science and Engineering.

Time: Monday, December 25 , 2016 (5 Dey 1395) – 15:00.

Abstract: Considering the elderly population growth and the shift in the base of the age pyramid in mainly in developed countries, and given the scientific breakthroughs in the implementation of communication infrastructure in different dimensions, discussions revolving around the smart home and its practical applications is no longer a far-fetched concept. In this report, a system, using paired passive infrared (PIR) sensors at each entry of the house, observes the collective activities of the physically-challenged individual as well as monitors his or her movement pattern. This system is designed in a manner that, while ensuring reliability concerning accuracy and reliability, it minimizes the negative impact on the individual’s privacy and does not add additional complication for the implementation or the installation phase.

Based on a behavioral data collection for a period of three weeks over a smart home testbed , well-known medium access control (MAC) protocols applicable for the scenario under study are reported. Focus regarding the selection of protocols is mainly concerned on the fact that, although numerous researches have been conducted toward the development of MAC protocols, most protocols have been observed or improved, considering their network features, under simulated circumstances. To identify suitable MAC protocols for the smart home application, using collected data is vital. In this research, in a testbed which uses PIR sensors that accurately record movement, the activities of the physically-challenged individual has been monitored for 21 days. The dynamic of this environment works in a way that a most of possible errors can be easily detected through different methods. Afterwards, using the simulator, the collected data will study and compare three protocols, namely X-MAC, RI-MAC and A-MAC, for the three criteria of duty cycle, package delivery ratio, and latency. Furthermore, these criteria are simulated using the previously-mentioned simulated data. The acquired results indicate that, by applying real data, the performance of these protocols is closely similar. It is shown, however, that, by including simulation based on real data, the performance of A-MAC in the work cycle aspect is higher than the RI-MAC and X-MAC protocols by 16.8 and 23.5 percent, respectively. Furthermore with the other simulation results based on well-known CASAS project, we have finished with the nearly same results in comparison with our implemented testbed and the collected data.

Keywords: Smart home, Activity of daily living, Smart home network architecture, MAC layer protocol, X-MAC, RI-MAC, A-MAC

Title:

Internet of Things for Healthcare and Smart Cities  

 Time:

Wednesday, August 31, 2016 (10th of Shahrivar) 14-15:30

at

School of Computer Science and Engineering (main theatre room) , Shahid Beheshti University

Abstract:

Digital data and the connected worlds of physical objects, people and devices are rapidly changing the way we work and interact with our surrounding environments. New technologies have a profound impact on different domains, such as healthcare, environmental monitoring, urban systems and control and management applications, among others. However, these large volumes of heterogeneous data require new methods of communication, aggregation, processing and mining in order to extract efficient and actionable information from the raw data. This talk will focus on Internet of Things technologies and will discuss the opportunities and challenges involved in using large-scale data analytics in smart city and healthcare applications and services.

The talk will also discuss the National Health Services (NHS) funded Internet of Things project for dementia care, called TIHM (https://www.england.nhs.uk/ourwork/innovation/test-beds/tihm/). It is estimated that there will be one million people with dementia in the UK by 2025. Beyond those directly affected, dementia also has a much wider impact on carers, families and health and care services, with social isolation being a key confounding factor. The TIHM project focuses on building the technical and physical infrastructure for an Internet of Things framework to support dementia care and remote monitoring. TIHM uses distributed and secure technologies to capture, analyse and manage the data in order to provide real-time and actionable information to different support groups in dementia care – i.e. clinical, social care, and patients (whenever and wherever appropriate).  TIHM brings together a team of health and care experts, innovation and SMEs with network-enabled products and services and academic and research groups with healthcare, economy and technical expertise to show case the use and effect of the connected technologies in healthcare scenarios.

Biography:

Payam Barnaghi is a Reader in Machine Intelligence at the Institute for Communication Systems (ICS) at the University of Surrey. He is a senior member of IEEE, a Fellow of Higher Education Academy and an associate editor of the IEEE Internet of Things Journal. He was a guest editor of a special issue of IEEE Intelligent Systems on Web of Things and a special issue of IEEE Internet Computing on Physical-Cyber-Social Computing. He is principal investigator and scientific coordinator of the EU FP7 CityPulse project (http://www.ict-citypulse.eu) on the Internet of Things and smart cities. He is also the technical lead for the National Health Services (NHS) funded Internet of Things project for dementia care (https://www.england.nhs.uk/ourwork/innovation/test-beds/
tihm/). His research interests include machine learning, Internet of Things, semantic web, information centric networks, information search and retrieval and their applications in healthcare and smart cities.

http://personal.ee.surrey.ac.uk/Personal/P.Barnaghi/