Kim Fung Tsang

The Generic Design of a High-Traffic Advanced Metering Infrastructure Using ZigBee

A multi-interface ZigBee building area network (MIZBAN) for a high-traffic advanced metering infrastructure (AMI) for high-rise buildings was developed. This supports meter management functions such as Demand Response for smart grid applications. To cater for the high-traffic communication in these building area networks (BANs), a multi-interface management framework was defined and designed to coordinate the operation between multiple interfaces based on a newly defined tree-based mesh (T-Mesh) ZigBee topology, which supports both mesh and tree routing in a single network. To evaluate MIZBAN, an experiment was set up in a five-floor building. Based on the measured data, simulations were performed to extend the analysis to a 23-floor building. These revealed that MIZBAN yields an improvement in application-layer latency of the backbone and the floor network by 75% and 67%, respectively. This paper provides the design engineer with seven recommendations for a generic MIZBAN design, which will fulfill the requirement for demand response by the U.S. government, i.e. a latency of less than 0.25 s.

The design of dual radio ZigBee homecare gateway for remote patient monitoring

A Dual Radio ZigBee Homecare Gateway (DRZHG) has been proposed and implemented to support remote patient monitoring. The novelty of DR-ZHG is two-fold. Firstly, it increases the transmission data rate of ZigBee. The Dual Radio ZigBee design furnishes low latency and highly accurate telehealth service at home. Secondly, the zero-configuration design of the DR-ZHG offers the most user friendly telehealth service to elderly people and long-terms patients. Analysis reveals that, for streaming data devices, the network depth should be confined to three (3) in a ZigBee tree network. As for polling data devices, it is analyzed that nine (9) sensors can be supported in a single hop communication. To align with the maximum hop count of three (3) for streaming devices, seven (7) polling devices can be accommodated. In summary, the developed DR-ZHG supports seven (7) polling service sensors and one (1) streaming service senor. Such a gateway meets the general latency standard of 2s for telemedicine services as stipulated by U.S. NIST.

ZigBee sensor network for Advanced Metering infrastructure

A ZigBee Advance Metering infrastructure (ZAMI) is proposed for automatic meter data collection and energy auditing and management. In the ZAMI, the system operates with multiple channels and frequency hopping and coexists with potential interferers. By incorporating dual channels, the delay is improved by 30% to 50%.

A Mobility Enabled Inpatient Monitoring System Using a ZigBee Medical Sensor Network

This paper presents a ZigBee In-Patient Monitoring system embedded with a new ZigBee mobility management solution. The system enables ZigBee device mobility in a fixed ZigBee network. The usage, the architecture and the mobility framework are discussed in details in the paper. The evaluation shows that the new algorithm offers a good efficiency, resulting in a low management cost. In addition, the system can save lives by providing a panic button and can be used as a location tracking service. A case study focused on the Princes of Wales Hospital in Hong Kong is presented and findings are given. This investigation reveals that the developed mobile solutions offer promising value-added services for many potential ZigBee applications.

Massive Internet of Things for Industrial Applications: Addressing Wireless IIoT Connectivity Challenges and Ecosystem Fragmentation

This article provides an overview of the development and standardizations of connectivity solutions for enabling the Industrial Internet of Things (IIoT). It also highlights key IIoT connectivity technologies and platforms that have the potential of driving the next industrial revolution. In addition, the article addresses the main challenges standing in the way of realizing the full potential of the IIoT, namely attaining secure connectivity and managing a vastly fragmented ecosystem of connectivity solutions and platforms. Finally, IIoT connectivity challenges are illustrated by the example of future building automation.

Toward Distributed Data Processing on Intelligent Leak-Points Prediction in Petrochemical Industries

Focusing on the leak-points in petrochemical industries, this paper discusses the key factors (i.e., equipment temperature, gas pressure, and diffusion rate) in petrochemical industries. Data from sensors of petrochemical industries need to be timely operated because of time sensitivity and it is hard to achieve associated information from sensors located in production sites. To this end, we propose a three-level framework based on improved back propagation (TLBP). The real-time data streams are processed according to the arriving time in input layer. At the same time, a neuron-optimizing solution is introduced in learning process to deal with redundant and invalid neurons, thereby accelerating the response speed of learning and reducing the prediction time. Finally, we propose an improved mechanism of the multidimensional learning factor to lower the learning error and higher convergence rate. Meanwhile, to fulfill the distributed prediction on leak-points, we see one three-level data-processing unit as a logic machine with multiple operators. Using the assignment scheduling, the general scheduling problem is split into the common subproblem of every operator and the system overhead is reduced. With the processed data we can obtain the relative location or diffusion radius of leak-points, as well as the area of leak-points. Simulation results show that the TLBP performs better than related algorithms in different metrics. Besides, the adaptability of TLBP is verified in leak-points prediction of petrochemical equipment from the processed data.

Guest Editorial Industrial Wireless Networks: Applications, Challenges, and Future Directions

Yhe papers in this special section focus on industrial wireless networks. With the rapid advance of wireless technologies, numerous emerging solutions and applications of industrial wireless systems have been developed. The present development of communication in industrial environments drives the need for ubiquitous access to distributed resources and services that are connected to things, devices, and systems. Service completions are typically perfected through smart APPS on wireless data delivery, such as WiFi, Bluetooth, ZigBee, and 5G. The occurrence of Internet of Things (IoT) further catalyzes the advent of the wireless era. These papers cover the comprehensive solutions of wireless network developments, industrial applications, and wireless prototype designs.

Admission Control Scheme for Mobile WiMAX Networks

In this paper, a QoS solution incorporating a dynamic call admission control scheme and a bandwidth allocation algorithm is proposed for WIMAX mobile application. The relationship between the channel utilization, the dropping and blocking probability versus traffic loads has been investigated. The proposed solution supports voice, data and multimedia services with differentiated QoS.

Analysis of Millimeter Wave Scattering by an Electrically Large Metallic Grating Using Wavelet-Based Algebraic Multigrid Preconditioned CG Method

An effective wavelet based multigrid preconditioned conjugate gradient method is developed to solve electromagnetic large matrix problem for millimeter wave scattering application. By using wavelet transformation we restrict the large matrix equation to a relative smaller matrix and which can be solved rapidly. The solution is prolonged as the new improvement for the conjugate gradient (CG) method. Numerical results show that our developed wavelet based multigrid preconditioned CG method can reach large improvement of computational complexity. Due to the automaticity of wavelet transformation, this method is potential to be a block box solver without physical background.

Cardiovascular diseases identification using electrocardiogram health identifier based on multiple criteria decision making

Binary classifier (BC) and multi-class classifier (MCC) are designed and analyzed.A scheme namely MCC-BC will pave the way for speedy and accurate ECGHI.A confidence index is newly proposed to evaluate the performance of ECGHI.MCDM using AHP has been developed to evaluate the optimal hyperplanes of ECGHI. Cardiovascular diseases can wreak havoc on human beings and lead to 30% of global death annually. The World Health Organization has always highlighted that there is a severe shortage of medical personnel, especially cardiologists, in most of the countries. In this paper, an electrocardiogram health identifier (ECGHI) has been proposed and developed for swift identification of heart diseases. The ECGHI has been applied to four most common types of cardiovascular diseases, namely Myocardial Infarction, Dysrhythmia, Bundle Branch Block and Heart Failure since these four types of cardiovascular diseases contribute to 25% of the overall population suffering from heart diseases. In the investigation of ECGHI, the binary classifier (BC) and multi-class classifier (MCC) are designed and analyzed. The MCC features a multi-class support vector machine (SVM) to diagnose the exact type of cardiovascular disease. The BC features a two-class SVM to identify healthiness of heart accurately. In this paper, the following indicators have been investigated, namely the overall accuracy, specificity, sensitivity, the dimensionality of feature vector, the total training and testing time of ECGHI and a newly defined confidence index. These six criteria form the basis to derive an analytic hierarchy process (AHP) to facilitate the multiple criteria decision making (MCDM) for the optimal evaluation of hyperplanes. Four kernels have been analyzed from which both the BC and MCC are evaluated and analyzed. The optimized ECGHI using BC yields an AHP Performance Score of 0.079 with score components (overall accuracy, specificity, sensitivity, average confidence index, dimensionality, total time for training and testing time) of 0.982, 0.978, 0.986, 0.608, 6, and 5.77s respectively. Likewise, the optimized ECGHI using MCC yields an AHP Performance Score of 0.093 with score components of 0.882, 0.89, 0.874, 0.504, 9, and 7.32s respectively. The BC is employed as a supplement of the MCC to achieve a further improvement in all six criteria. Such a novel process of identification and detection with high accuracy is referred as the MCC-BC scheme. The developed ECGHI (MCC) may identify the FOUR most common and important cardiovascular diseases simultaneously (with BC supplementing the MCC to achieve a high accuracy). Such simultaneous identification of cardiovascular diseases is the first of its kind in this research area, so no comparison can be made. The MCC-BC scheme will pave the way for speedy and accurate identification and detection of heart disease. The instant response of the ECGHI minimizes the probability of death from Myocardial Infarction, Bundle Branch Block, Dysrhythmia, and Heart Failure.