1st International Workshop on Big Data in Smart Healthcare Applications (BigSHA) in conjunction with MobiQuitous 2018
New York City, United States, November 5-7, 2018
Smart healthcare is an important research area of machine learning, data, science and Internet of Things (IoT), which employs sensors and other information identifying technologies, wireless and wired networks to realize large – scale, the multilayer interaction between patients and medical equipment’s, medical staff and healthcare institutions. At the same time, it is also an important foundation for the healthcare development of healthcare reform, which is vital to the welfare and livelihood for city residents. As a result, smart healthcare can also support smart cities, and smart healthcare is also one of the popular research areas in recent years. With the increasing applications of IoT, smart health care has achieved impressive results and brought better health care experiences not only for patients, but also for other healthy citizens, in contrast with traditional healthcare. Despite this, there are still few challenges in the healthcare system, for instance, as follows:
- Big data, machine learning and sensor fusion technology: Various health data from heterogeneous sources (including wearable, the internet, smart phones, embedded sensors in large numbers deployed for a variety of applications) usually have different health views as well as very large scale. These data can be dealt with and analysed by machine learning, big data analysis and sensor fusion solution, such as wearables, big data mining and machine learning methods. 2. Smart health solution: Smart health can be a prominent choice to medical resource shortness. Smart health enables patient self-treatment and monitoring by using simple devices (e.g., wireless devices and smart phones), which provide standardized outputs for specific physiological conditions, intelligent applications or software capable of analysing and processing body signals, wearable sensors and other smart devices exclusively manufactured for body signal monitoring or processing. 3. Remote health technology: Remote health monitoring system can enhance the usage rate of community health service centres. Remote health care system is the use of telecommunication and information technologies in order to provide clinical health care at a distance, which has the following advantages when applied to community health service centres. 4. Security and Privacy: IoT security is the area of endeavour concerned with safeguarding connected devices and networks in the Internet of things. More and more concerns have been raised in this field and ample methods to secure the data and trustworthiness-enhancing techniques have been proposed to resolve these concerns. Moreover, privacy and data-sharing will be even more difficult to manage in the future as there will be more connected to devices. Although, there are few emerging wearable technologies which provides lightweight and user-friendly models of security and privacy. But It is still not clear that these proposed techniques are useful and effective in practice and how quickly or even possibly they are going to be adopted.
This workshop aims to bring together the technologists and researchers who share interest in the area of big data, wearables, IoT and it security in smart healthcare system, as well as explore new venues of collaboration. This workshop mainly focuses on brining researchers together to discuss these opportunities and challenges in the research, design, and engineering of cloud, machine learning, mobile computing, algorithms, protocols and application on medical healthcare. We plan to seek papers that address theoretical, experimental research, and work in-progress for security, privacy and trustworthiness related issues in the context of medical cyber physical system. The workshop will focus on, but will not be limited to, the following topics of interest:
- Cloud Based Healthcare System
- Novel case studies and applications for healthcare based on smart and mobile devices
- Mobility and Big Data for Healthcare System
- HCI Challenges for IoT & Big Data Security & Privacy
- Mobile Healthcare Security
- Smartphone Security for Healthcare
- Wearable Device Security
- Visualization Analytics for Big Data and IoT
- Medical Device Security
- Security and Privacy of Implantable Medical Sensors
- Biometrics
- Energy-efficient IoT Based Wearables
- Software Defined Networks (SDN)
- Security in Virtualized Health Systems
- Data Acquisition, Integration, Cleaning, and Best Practices
- Software Systems to Support Big Data Computing
- Differential Privacy for Health Data
- Secure Machine Learning for Health Data
- Privacy Preserving Big Health Data Analysis
- Cryptography for Health Systems
- Security and Privacy Policies in Health Systems
Instructions for Authors
Papers should be in English. Regular papers should be up to 10 pages in length. Previously published work may not be submitted, nor may the work be concurrently submitted to any other conference or journal. Such papers will be rejected without review. The paper submissions must follow the ACM formatting guidelines (see Author’s kit section). Read the Publication Ethics and Malpractice Statement. Papers must be formatted using the ACM Author’s Kit. Detailed instructions and templates are available at https://mobiquitous.org/authors-kit/
TIMELINE
Submission deadline: August 20, 2018
Notification of acceptance: September 15, 2018
Camera-ready deadline: October 1, 2018
Workshop date: November 5, 2018
ORGANIZING COMMITTEE
Workshop Co-Chairs
Dr. Md Shaad Mahmud
University of New Hampshire, USA
Dr. Honggang Wang
University of Massachusetts-Dartmouth, USA