Chin-Feng Lai

Cloud-enabled wireless body area networks for pervasive healthcare

With the support of mobile cloud computing, wireless body area networks can be significantly enhanced for massive deployment of pervasive healthcare applications. However, several technical issues and challenges are associated with the integration of WBANs and MCC. In this article, we study a cloud-enabled WBAN architecture and its applications in pervasive healthcare systems. We highlight the methodologies for transmitting vital sign data to the cloud by using energy-efficient routing, cloud resource allocation, semantic interactions, and data security mechanisms.

Big data analytics: a survey

AbstractThe age of big data is now coming. But the traditional data analytics may not be able to handle such large quantities of data. The question that arises now is, how to develop a high performance platform to efficiently analyze big data and how to design an appropriate mining algorithm to find the useful things from big data. To deeply discuss this issue, this paper begins with a brief introduction to data analytics, followed by the discussions of big data analytics. Some important open issues and further research directions will also be presented for the next step of big data analytics.

On the computation offloading at ad hoc cloudlet: architecture and service modes

As mobile devices are equipped with more memory and computational capability, a novel peer-to-peer communication model for mobile cloud computing is proposed to interconnect nearby mobile devices through various short range radio communication technologies to form mobile cloudlets, where every mobile device works as either a computational service provider or a client of a service requester. Though this kind of computation offloading benefits compute-intensive applications, the corresponding service models and analytics tools are remaining open issues. In this paper we categorize computation offloading into three modes: remote cloud service mode, connected ad hoc cloudlet service mode, and opportunistic ad hoc cloudlet service mode. We also conduct a detailed analytic study for the proposed three modes of computation offloading at ad hoc cloudlet.

Future Internet of Things: open issues and challenges

AbstractInternet of Things (IoT) and its relevant technologies have been attracting the attention of researchers from academia, industry, and government in recent years. However, since the requirements of the IoT are quite different from what the Internet today can offer, several innovative techniques have been gradually developed and incorporated into IoT, which is referred to as the Future Internet of Things (FIoT). Among them, how to extract “data” and transfer them into “knowledge” from sensing layer to application layer has become a vital issue. This paper begins with an overview of IoT and FIoT, followed by discussions on how to apply data mining and computational intelligence to FIoT. An intelligent data management framework inspired by swarm optimization will then given. Finally, open issues and future trends of this field will be addressed.

Detection of Cognitive Injured Body Region Using Multiple Triaxial Accelerometers for Elderly Falling

This paper aimed to use several triaxial acceleration sensor devices for joint sensing of injured body parts, when an accidental fall occurs. The model transmitted the information fed by the sensors distributed over various body parts to the computer through wireless transmission devices for further analysis and judgment, and employed cognitive adjustment method to adjust the acceleration range of various body parts in different movements. The model can determine the possible occurrence of fall accidents, when the acceleration significantly exceeds the usual acceleration range. In addition, after a fall accident occurs, the impact acceleration and normal (habitual) acceleration can be compared to determine the level of injury. This study also implemented a sensing system for analysis. The area of the body parts that may sustain greater impact force are marked red in this system, so that more information can be provided for medical personnel for more accurate judgment.

A review of industrial wireless networks in the context of Industry 4.0

Abstract There have been many recent advances in wireless communication technologies, particularly in the area of wireless sensor networks, which have undergone rapid development and been successfully applied in the consumer electronics market. Therefore, wireless networks (WNs) have been attracting more attention from academic communities and other domains. From an industrial perspective, WNs present many advantages including flexibility, low cost, easy deployment and so on. Therefore, WNs can play a vital role in the Industry 4.0 framework, and can be used for smart factories and intelligent manufacturing systems. In this paper, we present an overview of industrial WNs (IWNs), discuss IWN features and related techniques, and then provide a new architecture based on quality of service and quality of data for IWNs. We also propose some applications for IWNs and IWN standards. Then, we will use a case from our previous achievements to explain how to design an IWN under Industry 4.0. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make IWNs truly ubiquitous for a wide range of applications.

Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring

Traditional wearable devices have various shortcomings, such as uncomfortableness for long-term wearing, and insufficient accuracy, etc. Thus, health monitoring through traditional wearable devices is hard to be sustainable. In order to obtain healthcare big data by sustainable health monitoring, we design “Smart Clothing”, facilitating unobtrusive collection of various physiological indicators of human body. To provide pervasive intelligence for smart clothing system, mobile healthcare cloud platform is constructed by the use of mobile internet, cloud computing and big data analytics. This paper introduces design details, key technologies and practical implementation methods of smart clothing system. Typical applications powered by smart clothing and big data clouds are presented, such as medical emergency response, emotion care, disease diagnosis, and real-time tactile interaction. Especially, electrocardiograph signals collected by smart clothing are used for mood monitoring and emotion detection. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make smart clothing ubiquitous for a wide range of applications.

Adaptive Body Posture Analysis for Elderly-Falling Detection with Multisensors

Multisensors explore the collaborative analysis of body posture modes to detect accidental-falling incidents and provide relevant data to medical personnel for rescue and treatment.

Defending Against Collaborative Attacks by Malicious Nodes in MANETs: A Cooperative Bait Detection Approach

In mobile ad hoc networks (MANETs), a primary requirement for the establishment of communication among nodes is that nodes should cooperate with each other. In the presence of malevolent nodes, this requirement may lead to serious security concerns; for instance, such nodes may disrupt the routing process. In this context, preventing or detecting malicious nodes launching grayhole or collaborative blackhole attacks is a challenge. This paper attempts to resolve this issue by designing a dynamic source routing (DSR)-based routing mechanism, which is referred to as the cooperative bait detection scheme (CBDS), that integrates the advantages of both proactive and reactive defense architectures. Our CBDS method implements a reverse tracing technique to help in achieving the stated goal. Simulation results are provided, showing that in the presence of malicious-node attacks, the CBDS outperforms the DSR, 2ACK, and best-effort fault-tolerant routing (BFTR) protocols (chosen as benchmarks) in terms of packet delivery ratio and routing overhead (chosen as performance metrics).

Survey on context-awareness in ubiquitous media

Context-awareness assists ubiquitous media applications in discovering the changeable contextual information and adapting their behaviors accordingly. A wide spectrum of context-aware schemes have been proposed over the last decade. However, most of them provide partial functionalities of context-awareness in ubiquitous media applications. They are specified to a certain task and lack of systematic research on context-awareness. To this end, this survey aims at answering how close we are to developing context-aware applications in ubiquitous media in a systematic manner. This survey proposes a reference framework to identify key functionalities of context-awareness. Then, it investigates the state-of-the-art advances in every functionality of context-awareness. Finally, it points out potential directions in context-awareness research and tools for building and measuring context-aware ubiquitous media systems.