Rapid urbanization and the rising demand for sustainable mobility have accelerated the adoption of dockless bike-sharing systems. However, these systems frequently encounter challenges such as oversupply, inefficient resource allocation, and limited responsiveness to localized demand. To address these issues, this paper proposes the novel AIoT-based and user behavior-driven management system (AUMS)—a comprehensive AIoT-based framework that integrates demand prediction, dynamic clustering, and rebalancing algorithms to optimize the management of dockless bike-sharing services. Unlike existing approaches that focus narrowly on demand prediction, AUMS combines real-time IoT sensor data with user behavior analytics to support continuous, data-driven decision-making. The system employs a closed-loop control structure, enabling the dynamic reconfiguration of bike distribution in response to shifting urban mobility patterns. Its architecture includes three core modules: 1) demand prediction based on spatiotemporal behavioral data, 2) dynamic clustering to localize operational zones, and 3) intelligent rebalancing to minimize idle rates and unmet demand. The significance of this work lies in its holistic design and rigorous real-world validation. Over a 15-month period, AUMS was deployed in three escalating phases: a localized pilot, a district-level deployment in Tseung Kwan O, and a city-wide experiment across 13 districts in Hong Kong. Field results demonstrate notable performance improvements, including a 10.8% increase in bike utilization, 11.6% growth in trip frequency, and a 29.2% reduction in unmet demand.

Promoting smart city applications can facilitate sustainable development to achieve carbon neutrality and solve existing problems, such as the frequent occurrence of extreme weather events caused by climate change. However, monitoring a large area in detail is very challenging, and there is currently no cost-effective solution. This research aims to design an artificial intelligence (AI) of Things (AIoT) LoRaWAN-based low-power, extensive coverage monitoring and alarm system at a low cost. Using the LoRaWAN communication system, it can provide point-to-point communication distances of more than 1 km, forming a low-cost remote network. Additionally, low-power consumption cameras and temperature and humidity sensors monitor the environment for a long time, then use the image compression and data transmission methods developed in this research to achieve stable and low data rate transmission of images and data. On the other hand, AI image analysis algorithms are used for image monitoring and object detection to provide alarm functions. Through this research, this system successfully monitored the environmental data and images under different extreme weather conditions in Hong Kong and provided effective warnings. Based on this research, a low-cost remote monitoring network can be further formed to automatically and effectively provide environmental monitoring and alerts to local governments over a long period.

This paper proposes and implements a stepless frequency regulation method for wireless power transfer (WPT) with a simple LC compensation network to provide load-independent transmitter current. It should be mentioned that the capacitor in LC compensation network is controlled by a switch. Different from previous switched capacitor compensation networks, which can only select a limited number of resonant frequency points, this model can choose the resonant frequency arbitrarily in a wide frequency range. In theory, the frequency range can be controlled from a few kilohertz to hundreds of kilohertz. The key is controlling the turn-on time of the switch and adjusting the activation time length of the controlled capacitor in every WPT cycle. Therefore, the proposed system is very suitable for multi-frequency WPT, as the system can work at full resonance with practically arbitrary frequency. A Simulink simulation serves for verification, and the results prove the system can change the resonant frequency from 100 kHz to 300 kHz continuously while keeping the transmitter current load-independent.

This paper proposes an AC-AC converter for the wireless power transfer (WPT) system. Besides, the method can also be applied in high-frequency heating applications. Compared with the traditional AC-DC-AC system, it doesn’t need a DC bus capacitor. Unlike the matrix converter, it just needs 7 MOSFETs/IGBTs. The operation modes can be divided into energy injection and free oscillation. Zero current switchings can be achieved, which allows the system to operate at high frequencies. Furthermore, a modulation method is proposed to achieve a high-quality grid current. The operating principle and system output capacity are analyzed detailly. Finally, simulation results are presented to verify the effect of the system.

Wireless power transfer (WPT) is one of the global highlight techniques with the rapid development of electric vehicles (EV). Currently, inductive power transfer (IPT) for EV charging faces the efficiency problem caused by the low saturation flux in the ferrite core bars. The nanocrystalline ribbon core is an advisable choice for the features of a high saturation flux and low power loss. In this paper, a double-D pads coupler with nanocrystalline core enhanced and ferrite TDK PC40 core will be detailed analyzed and compared regarding the magnetic field flux density, the air flux leakage around the vehicle body, the power loss distribution, and the magnetic shielding for wireless EV charging.

In this paper, a wireless bipolar drive has been proposed and implemented for AC application, which not only performs selective wireless power transfer (WPT), but also secondary-converterless operation for frequency-controllable AC output. The key is to use the proposed self-drive circuit based on the selective WPT with two different resonant frequencies. Besides, the inductor-capacitor-inductor (LCL) compensation network is newly adopted to achieve power equalization so that only one transmitter is needed to serve two receivers and control the low-frequency AC output. As a result, there is no additional battery, controller, and converter at the secondary side and hence the system robustness can be significantly improved. Finally, experimental results are offered to verify the proposed topology.

In this paper, a novel kind of wireless motors, namely, the LCC-compensated wireless switched reluctance motor, is proposed and implemented. The definite advantages are that there is no power converter at the motor side and particularly no switched-capacitor array at the transmitter side to realize the multiple-frequency operation. The key is to develop an LCC compensation involving an inductor and two capacitors (the so-called LCC) for a multiple-frequency wireless power transfer system. As a result, only one transmitter is needed to targetedly feed three receivers, which directly energize the three phase windings of the motor. Particularly, there is no need to control switched capacitors to change the resonant frequency of the transmitter. Meanwhile, the burst firing control method is employed to realize the speed control. Both calculation and experimental results are presented to validate the feasibility of the proposed system. In the system prototype, the transmission distance can reach up to 150 mm and the transmission efficiency can be achieved up to 80%.

This paper is to present an effective wireless power transfer (WPT) system to recharge the battery of electric unmanned aerial vehicle (e-UAV). The proposed system can generate an approximately even magnetic field which allows the e-UAV to get enough energy at different points above the charging pad. Also, based on the design, the proposed system is capable to transmit enough power at a high efficiency. Both simulation and experimentation are carried out to prove the validity of the proposed WPT system for e-UAV charging.