The utilization of Building Integrated Photovoltaic (BIPV) systems in high-rise urban buildings is limited despite their potential benefits in reducing electricity costs and greenhouse gas emissions. This paper introduces an advanced methodology that comprehensively evaluates BIPV system performance in high-rise buildings. The approach considers facade orientations, rooftop areas, and PV panel types to assess energy generation potential under different scenarios. Microclimate data obtained using the Urban Weather Generator (UWG) is incorporated for a thorough analysis. A case study on a super high-rise building in Hong Kong demonstrates the effectiveness of the proposed method and highlights the BIPV system's potential. The paper emphasizes the importance of optimizing BIPV systems in urban settings by considering various factors to maximize their effectiveness.

This paper presents a novel approach for estimating the remaining capacity of retired electric vehicle (EV) batteries in agricultural renewable energy systems. The experimental setup for measuring battery parameters, particularly focusing on Lithium Iron Phosphate (LFP) batteries under different room temperatures, is outlined. Grey Relational Analysis (GRA) is utilized to identify significant parameters for input to a Long Short-Term Memory (LSTM) model, which accurately estimates the remaining capacity of retired batteries. Simulation results using a measured battery dataset demonstrate the effectiveness of the proposed GRA-LSTM approach. The findings highlight the potential of repurposing retired EV batteries for sustainable energy storage in agricultural applications, optimizing resource utilization and enhancing energy efficiency in farming practices.

This paper presents a solar tree prototype for implementing agrivoltaics in small suburban farms. Agrivoltaics integrates photovoltaic power generation and agricultural activities, minimizing competition between energy and food production. While technical aspects of agrivoltaics are well-studied, its implementation remains challenging, especially for small farms. The prototype uses IoT, 3D printing, and commercial components. Design principles, structure, solar-to-electricity conversion, and solar tracking mechanisms are discussed. Experiments had been conducted to enhance light-dependent resistor (LDR) accuracy for tracking, exploring shielding and tradeoffs.

By integrating the merits of aerial, terrestrial, and satellite communications, the space-air-ground integrated network (SAGIN) is an emerging solution that can provide massive access, seamless coverage, and reliable transmissions for global-range applications. In SAGINs, the uplink connectivity from ground users (GUs) to the satellite is essential because it ensures global-range data collections and interactions, thereby paving the technical foundation for practical implementations of SAGINs. In this article, we aim to establish an accurate analytical model for the uplink connectivity of SAGINs in consideration of the global distributions of both GUs and aerial vehicles (AVs). Particularly, we investigate the uplink path connectivity of SAGINs, which refers to the probability of establishing the end-to-end path from GUs to the satellite with or without AV relays. However, such an investigation on SAGINs is challenging because all GUs and AVs are approximately distributed on a spherical surface (instead of the horizontal surface), resulting in the complexity of network modeling. To address this challenge, this paper presents a new analytical approach based on spherical stochastic geometry. Based on this approach, we derive the analytical expression of the path connectivity in SAGINs. Extensive simulations confirm the accuracy of the analytical model.

Hong Kong's high population density in Public Rental Housing (PRH) and Home Ownership Scheme (HOS) estates and courts presents safety concerns in case of fire accidents, as residents may find it difficult to escape without guidance. To address this issue, a prototype LED arrow indication system has been developed to display a guided route to residents by analyzing real-time data collected from a network of sensors. The data is stored on an online cloud server and transmitted to a central controlling system via Wi-Fi connections, and displayed on LED indication boards and a mobile application. The sensor network can also function as an indoor air quality (IAQ) monitor under non-fire incident situations. Ultimately, the prototype system can operate with the connection of the cloud server and mobile application.

Smart building is a vital part in the development of the smart city framework. Using intelligent solutions, smart building can reduce energy consumption and enhance safety and security of the building to establish a sustainable environment. Smart campus has attracted attention of the education providers as they aim to offer a quality learning environment for their students and staffs. Most of studies concentrated on using smart building technologies in conventional buildings rather than campuses very often. With the advancement of 5G networking and the related smart technologies, the interconnection between the people, devices and campus environment has been reshaped with digital solutions. This article reviews the associated building management technologies and applications in smart campus and their impacts to the operation of facilities on campus.

Existing electrical and electronic laboratories in different industries have normally equipped with four types of basic electrical compliance testers (Hi-potential tester, leakage current tester, insulation resistance tester and earth continuity tester) that may be an old or a standard model. They operate separately and the operator has to record the test data one by one manually. In recent years, manufacturers have introduced new models to combine the four testers and provide Internet-of-Things (IoT) and data analysis software upgrades. However, it is not cost-effective to replace properly functioning equipment for these upgrades. Therefore, by upgrading these compliance testers with IoT capabilities, the test data from the four testers can be organized, thus correlating the four major electrical compliance tests. This paper reveals the feasibility on enhancing the efficiency of testing operations with a reasonable cost of less than USD 100.

In this paper, a new wireless charging system with improved energy efficiency for electric vehicles was proposed and simulated by improving efficiency of power conversion through magnetic inductive coupling or magnetic resonance coupling. The relationships between the position of receiver and the magnitude of wireless transfer system were first investigated. The number of turns with different coil structure were also discussed as it can affect the power efficiency. A new method by introducing various number of magnetic bars under coils configuration and shaping magnetic flux is proposed and demonstrated to achieve higher power efficiency. Simulation of this method was conducted to initiate mutual inductance of transmitter and receiver coils. The performance of new methods were simulated in MATLAB and COMSOL in order to compare with the old method. An energy efficiency of 82.5 % with an improvement of 7.45 % was achieved.

In recent years, electric vehicles (EVs) have been widely applied to improve environment. The EV could provide environmentally friendly transportation but have the demerit of low battery capacity. Rapid charging by charging stations (CS) is critically needed especially for those drivers in long distance trip. Thus, a routing optimization problem for EVs charging should be addressed. Furthermore, this problem becomes more practical when the EV density is high at peak. In this scenario EVs are only allowed to obtain energy that render them able to arrive at the destination. In this paper, we formulate an emergent EV charging optimization problem in EV high density area which has not been discussed in related work and a novel genetic algorithm based emergent charging scheduling (GECS) scheme is proposed. The genetic algorithm (GA) is presented to simplify the multi-objectives optimization process in this case. Furthermore, incorporation of the Earliest Deadline First (EDF) which indicates the minimum recharging deadline time as the subject and Nearest Job First (NJF) which indicates the minimum recharging path as the subject into genetic optimization process can relieve the charging emergent condition and improve optimized results. The simulation results show that the proposed scheme can provide an optimal solution to minimize the average distance and waiting time for emergent charging in EV high density region.

In this paper, we demonstrated the application of the monitoring and control system on the unceremonious electrical testing equipment which is unintentionally designed for the testing laboratories. The operating temperature and current would be under surveillance of our design product using the concept of the Internet of Things (IoT). The power supply of the electrical testing equipment would be cut off when it is operated under any hazardous condition.

Electrical testing laboratory is full of hidden hazards. Although there are various safety policies required by legislation or international standards, the accidents in electrical testing laboratory happened frequently. To eliminate the probability of these hazards and accidents, an automatic and comprehensive system is required on top of the safety policies and guidance. In this paper, the current status of hazardous areas in various electrical and electronic testing laboratories was analyzed via a survey in the testing and certification industry. Based on the analytical results, a wireless sensor network combined with various detectors and wireless technology was built to construct a targeted, automatic and convenience wireless sensor system according to the known potential hazards. The effectiveness and efficiency of the proposed wireless sensor network were evaluated in the real electrical testing laboratory.

Smart transportation and smart healthcare are considered as essential Smart City applications. The emerging light-weight sensors facilitate real-time monitoring drivers' status in various applications especially safety and healthcare. As such, the statistics reveals that >60% of adult drivers felt sleepy while driving, and drunk drivers are found in >40% of traffic accidents. In this paper, an electrocardiogram (ECG) based Drivers' Status Monitoring (ECG-DSM) system is developed to detect drowsy and drunk driving. The proposed ECG-DSM extracted similarities of ECG signals under normal, drowsy and drunk conditions, and the corresponding feature vector was built. The classifier is expected to alert drivers accurately and timely to prevent traffic accidents. Hence, the classifier's trade-off between accuracy and detection time was analysed by adjusting the dimensionality of feature vector. Safety analysis using Monte Carlo simulation was carried out to determine the best classifier under practical working environment. The results demonstrated that the best classifier for ECG-DSM achieves 91 % of average accuracy and 4.2s of detection time, and it can prevent >92 % of vehicle collisions due to drowsy and drunk driving. The proposed work will contribute to road traffic safety and save $50 billion US dollars on the cost of traffic injuries.

In this paper, we successfully demonstrated a software application on the android platform of mobile phone which allows users to have a quick insight of radiated emission generated based on the image of a printed circuit board (PCB) by using analytical method and image processing. For benchmarking the application, a study on the radiated emission of PCBs with the use of electromagnetic compatibility (EMC) chamber was also taken. Numerous layouts on PCBs with common problem of electromagnetic interference were made for the comparison with the final results generated by the application. The difference of the emission level between the result measured in the EMC chamber and result predicted by the software application is within 5 dBμV/m.

In this paper, we successfully demonstrated an application in monitoring the capacity of portable power bank by developing a system with the Arduino platform which allows the testing practitioners in the testing laboratories to test, record and analyze the portable power banks under test in a remote manner. For standardizing the measurement, a testing standard for measuring the capacity of portable power bank was drafted according to the circuit design in charging and discharging, environment and users' habits in Hong Kong. The developed system was implemented by analyzing numerous portable power banks existed in the market following the procedures listed in the drafted standard. The result showed that only the tested portable power bank labelled with rated capacity could deliver the capacity mentioned. All of the tested portable power bank labelled with capacity only could not provide adequate information for fair comparison which measured capacity was always lower than the capacity on the package.

A fully integrated single-band 2.4 GHz low noise amplifier (LNA) is designed by using 0.18μm CMOS technology for ZigBee applications. For healthcare applications, high power consumption is not preferred. Increasing the sensitivity of receiver, therefore, could be a solution resulting in the use of LNA. The impedance expression is mathematically reconstructed into a quadratic equation and leads to the solutions by adding the LC tank in the matching networks. Besides, by using voltage controlled MOS varactor, the LC tanks at the input and output can be tuned. Such topology is convenient for calibrating the frequency drift due to the process variation and unexpected parasitics. The amplifier works at the supply voltage 1.2 V with current dissipation 10 mA. The gains achieved are over 15 dB at 2.4 GHz and the corresponding noise figure is about 2.1 dB.

This paper introduces a high frequency Point-to-Point (PtP) Microwave Transmitter Module for Telemedicine for hospital(s). Such a telemedicine system links up remote communities from one building to another in hospital environment. The network configurations of the high frequency microwave system are illustrated in details. Key advantages such as high capacity, long propagation distance, and wide range of frequency bands are described. The high frequency PtP serves as a repeater so that paramedical staff or nurse(s) may receive data at appropriate time. Hence important tasks such as first aid, doctor's diagnosis and instructions to patients may be performed through the telemedicine system. This paper describes the design of a telemedicine system based on a high linearity Ku-band transmitter module that can improve the capacity (data rate) as well as increased the propagation distance. The module operates between 13 ~ 15.5 GHz and achieves 25 dB of gain and 33 dBm of output power at 1dB gain compression. The third order intermodulation (IM3) is -41 dBc at 22 dBm Pout/tone, when the two-tone space is 600KMz at the high centre frequency of 15GHz.

Smart transportation is an application of intelligent system on transportation domain, expected to bring the society environmental and economic advantages. By combining with IoT techniques, the concept is being enhanced and raised to a system level. Numerous data are able to collect and effective analysis technique is needed. Here in this paper, we proposed a framework of employing IoT technique to construct a free time navigation system. The system aims at providing a real-time quantification of traffic conditions and suggests optimal route based on the information retrieved. The system can be basically separated into two major components: (i) the traffic condition estimation module and the (ii) real-time routing algorithm. In the first component, traffic conditions of roads will be estimated based the information collected from sensors installed on vehicles. Based on these location and speed information, the traffic condition can be quantified using a weighted kernel density estimation (WKDE) function. This function is a function of time and provides a real time insight of the overall traffic condition. By combining this information and the topological structure of the road network, a more accurate time consumption on each road can be estimated and hence enable a better routing.

The convergence of smart energy system, telemedicine system and smart home/building solution will be the future development focus of next generation building and home automation system. This paper discusses the impact of the convergence on WiMAX development in terms of QoS management and network design. A performance evaluation has been also conduct to visualize the impact and promising result has been found. This confirms that the current WiMAX standard service class definitions and QoS management framework can fulfill the future development of WiMAX convergent automation network after slight modification.

This paper presents a comprehensive analytical model for determining the maximum average data throughput achievable through adaptive modulation in a wireless TDMA network environment. The model allows for designing rate adaptation algorithms that exploit higher transmission rates for data devices operating in superior channel conditions. It incorporates the probability of retransmissions due to device movement and channel estimation errors such that data throughput loss resulting from such retransmissions can be accounted for in designing rate adaptation algorithms while seeking to maximize transmission rate. The model can be used in various system and channel environments to determine the potential benefits of adaptive modulation and to derive the conditions under which these benefits are attainable. As a demonstrating example, the paper considers a rate assignment policy that employs adaptive modulation for every fresh transmission but switches to a safe mode should retransmissions occur, where channel state inaccuracy is accounted for when choosing the transmission rate in the adaptive mode and the lowest transmission rate is used in the safe mode. The results show how the model can be used to assess data throughput for a given system and how it can be used to optimize a rate assignment algorithm by containing retransmissions

The hybrid system is an extension of the state-space system model which allows for random and abrupt changes in the model parameters. In this paper we use the hybrid system to model burst type interference in a direct-sequence spread-spectrum (DS/SS) communication system. The resulting optimum receiver is easily derived but too computationally complex to be practical. Two suboptimal but more practical receivers are presented. In an example, the hybrid system is used to model pulsed narrowband interference. The performance of each suboptimal receiver is evaluated using computer simulations.>

The one-dimensional on-line bin-packing problem is considered, A simple O (1)-space and O ( n )-time algorithm, called HARMONIC M , is presented. It is shown that this algorithm can achieve a worst-case performance ratio of less than 1.692, which is better than that of the O ( n )-space and O ( n log n )-time algorithm FIRST FIT. Also shown is that 1.691 … is a lower bound for all 0 (1)-space on-line bin-packing algorithms. Finally a revised version of HARMONIC M , an O ( n )-space and O ( n )- time algorithm, is presented and is shown to have a worst-case performance ratio of less than 1.636.