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Crowdsense Roadside Parking Spaces With Dynamic Gap Reduction Algorithm

IEEE Internet of Things Journal 2025年第9期12卷 11858-11873页

作者： Zheng, Wenjun Shi, Zhan Ou, Qianyu Liao, Ruizhi The Chinese University of Hong Kong School of Data Science Shenzhen Shenzhen518116 China Guangdong Provincial Key Laboratory of Mathematical Foundations for Artificial Intelligence Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology School of Humanities and Social Science Shenzhen518116 China

In the context of smart city development, mobile sensing emerges as a cost-effective alternative to fixed sensing for on-street parking detection. However, its practicality is often challenged by the inherent accuracy limitations arising from detection intervals. This article introduces a novel dynamic gap reduction algorithm (DGRA), which is a crowdsensing-based approach aimed at addressing this question through parking detection data collected by sensors on moving vehicles. The algorithm’s efficacy is validated through real drive tests and simulations. We also present a driver-side and traffic-based evaluation model (DSTBM), which incorporates drivers’ parking decisions and traffic conditions to evaluate DGRA’s performance. Results highlight DGRA’s significant potential in reducing the mobile sensing accuracy gap, marking a step forward in efficient urban parking management. © 2014 IEEE.

关键词： Parking

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Joint Design of Radar Receive Filter and Unimodular ISAC Waveform with Sidelobe Level Control

arXiv

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arXiv 2025年

作者： Zhang, Kecheng Liu, Ya-Feng Wang, Zhongbin Yuan, Weijie Keskin, Musa Furkan Wymeersch, Henk Xia, Shuqiang School of System Design and Intelligent Manufacturing The Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Electrical Engineering Chalmers University of Technology Gothenburg41296 Sweden ZTE Corporation The State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China

Integrated sensing and communication (ISAC) has been considered a key feature of next-generation wireless networks. This paper investigates the joint design of the radar receive filter and dual-functional transmit waveform for the multiple-input multiple-output (MIMO) ISAC system. While optimizing the mean square error (MSE) of the radar receive spatial response and maximizing the achievable rate at the communication receiver, besides the constraints of full-power radar receiving filter and unimodular transmit sequence, we control the maximum range sidelobe level, which is often overlooked in existing ISAC waveform design literature, for better radar imaging performance. To solve the formulated optimization problem with convex and nonconvex constraints, we propose an inexact augmented Lagrangian method (ALM) algorithm. For each subproblem in the proposed inexact ALM algorithm, we custom-design a block successive upper-bound minimization (BSUM) scheme with closed-form solutions for all blocks of variable to enhance the computational efficiency. Convergence analysis shows that the proposed algorithm is guaranteed to provide a stationary and feasible solution. Extensive simulations are performed to investigate the impact of different system parameters on communication and radar imaging performance. Comparison with the existing works shows the superiority of the proposed algorithm. © 2025, CC BY-NC-SA.

关键词： Mean square error

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An Analytical Model for Crowdsensing On-street Parking Spaces

An Analytical Model for Crowdsensing On-street Parking Space...

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2019 International Conference on Internet of Things, Embedded systems and Communications, IINTEC 2019

作者： Zheng, Wenjun Liao, Ruizhi Zeng, Jingliang School of Science and Engineering Chinese University of Hong Kong Shenzhen China Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology China School of Humanities and Social Science Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781728151847

Parking becomes an insurmountable pain in cities as the world continues to urbanize and the car ownership becomes common. Industry and academia have made great efforts to facilitate parking and lessen the drivers' searching time by utilizing real-time sensing techniques or big data based occupancy prediction algorithms. In this paper, we focus on an innovative crowdsensing way to provide the currently unavailable on-street parking information for smart cities, and analyze the number of sensing units required by the crowdsensing approach. An analytical model is developed to find the relationship among the required sensing units, detection accuracy and update time based on historical parking data derived from Open Data portals of two metropolises in China. The model proves that the crowdsensing approach has a great potential in bringing the on-street parking information to drivers by employing significantly fewer sensing units compared with the traditional fixed sensing alternative. © 2019 IEEE.

关键词： Analytical models

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An evolutionary note on smart city development in China

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Frontiers of Information technology & Electronic Engineering 2022年第6期23卷 966-974页

作者： Ruizhi LIAO Liping CHEN School of Humanities and Social Science The Chinese University of Hong Kong(Shenzhen)Shenzhen 518172China Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology Shenzhen518172China Enterprise&Technology Security IBMDublinIrland

Urbanization is an important indicator of a country's degree of *** to the World Urbanization Report by the Department of Economic andSocial Affairsof the United Nations,morethan 55%of the world's population lives in cities,with this figure projected to rise to 70%by 2050(United Nations,2018).China's urban population accounts for 60%of the national total in 2020,and is expected to reach a very ambitious rate,80%,by 2050(Deloitte,2018).

关键词： Urbanization smart evolutionary

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On the " of a Cut-Set Bound on network Function Computation

On the " of a Cut-Set Bound on Network Function Computation

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2018 IEEE International Symposium on Information Theory, ISIT 2018

作者： Wang, Jie Yang, Shenghao Li, Congduan Chinese University of Hong Kong Shenzhen School of Science and Engineering Shenzhen China Chinese University of Hong Kong Shenzhen Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology Shenzhen China City University of Hong Kong Department of Computer Science Hong Kong Hong Kong

ISBN: (纸本)9781538647806

The following model of network function computation in directed acyclic networks is considered: A sink node desires to compute correctly a target function with all possible inputs of the function generated at multiple source nodes. The network links have limited capacity and are error-free. The intermediate network nodes perform network coding without any computation bound. The computing rate is measured by the average number of times that the target function can be computed for one use of the network. Guang, Yang and Li recently proposed a general upper bound on the computing capacity that is tight for all the instances of the problem with known computing capacity in literature. In this paper, we show that their upper bound is not tight in general by explicitly characterizing the computing capacity of an example. Our technique can be extended to characterize upper bounds on the computing capacity of a general instance of the network function computing problem. © 2018 IEEE.

关键词： network coding

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Magnetic Field Strength Sequence-based Indoor Localization Using Multi-level Link-node Models

Magnetic Field Strength Sequence-based Indoor Localization U...

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IEEE International Conference on Communications (ICC)

作者： Sheng Guo Guanchong Niu Zewei Wang Man-On Pun Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology The Chinese University of Hong Kong (Shenzhen) Shenzhen China

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

This work investigates geomagnetism-based indoor localization by exploiting the magnetometers built-in smartphones. The main challenge arises from the fact that the localization accuracy is handicapped by the limited dimensionality of the magnetometer data. To cope with this problem, the magnetic field strength (MFS) sequence has been proposed to improve the localization accuracy. However, it remains an open challenge to derive the exact location through the MFS. In this work, a novel multi-level link-node model containing geometry and topology information is first proposed to construct the MFS sequence fingerprint database which can be easily constructed by crowdsourced technology. By exploiting this database, a hybrid approach combining dynamic time warping (DTW), pedestrian dead reckoning (PDR) and k-nearest neighbor (kNN) is developed to achieve efficient MFS sequence matching and accurate indoor localization. The proposed method provides a convenient and pervasive indoor localization solution that uses only the built-in sensors of smartphones. Without knowing the initial position, the user's location can be quickly determined. Extensive experimental results confirm that the proposed approach can achieve accurate and efficient MFS sequence matching results while providing accurate initial and end position estimation in the indoor environments.

关键词： Magnetometers Trajectory Databases Sensors Acceleration Elevators Smart phones

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3-D Placement of UAVs Based on SIR-Measured PSO Algorithm

3-D Placement of UAVs Based on SIR-Measured PSO Algorithm

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IEEE Globecom Workshops

作者： Wentao Liu Guanchong Niu Qi Cao Man-On Pun Junting Chen Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology The Chinese University of Hong Kong (Shenzhen) Shenzhen China

ISBN: (数字)9781728109602

ISBN: (纸本)9781728109619

This work studies the deployment of unmanned aerial vehicles (UAVs) as emergency access points to provide wireless services to users in a green field. Specifically, three fundamental design issues are explored under practical 3D air-to-ground (ATG) channel models, namely the minimum number of UAVs, their optimal deployment locations and the optimal transmit power allocation. To decouple these design goals, a particle swarm optimization (PSO)-based scheme in conjunction with the balanced Signal to Interference plus Noise Ratio (SINR) transmit power allocation is proposed. Exploiting the closed-form expressions of the SINR-balanced optimal power allocation and the resulting SINR, the proposed PSO-based scheme optimizes the UAV location generation by generation. Furthermore, a K-means clustering-based initialization scheme is developed to improve the performance of the proposed PSO-based scheme. Finally, a power fine-tuning scheme is devised to further reduce the total transmit power. Extensive simulation is performed to confirm the good performance of the proposed scheme.

关键词： Interference Signal to noise ratio Resource management Unmanned aerial vehicles Channel models Three-dimensional displays Optimization

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A reservation system with an efficient matching-and-scheduling mechanism for private parking-sharing programs 25

A reservation system with an efficient matching-and-scheduli...

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25th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2021

作者： Yan, Pengyu Cai, Xiaoqiang Chu, Feng Ni, Debing School of Management and Economics University of Electronic Science and Technology of China Chengdu China Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology The Chinese University of Hong Kong Shenzhen Guangdong China Shenzhen Research Institute of Big Data Guangdong China Laboratoire IBISC Univ Evry Universitie Paris-Saclay Evry91025 France

ISBN: (纸本)9781713835196

We design a smart parking-sharing reservation system composed of three modules: Pre-processing, matching, and pricing. With the announced supply and demand information, the pre-processing module identifies a set of feasible parking slots for each driver concerning the compatibility of slot supply for the driver's demand. The matching module generates a system-wide optimal matching solution and further schedules the driver's parking time by using the flexibility of driver travel plans. The pricing module adopts a novel VCG-based pricing to determine the parking fees of drivers under an incomplete information setting in which each driver (player) cannot obtain the knowledge of the other competitors (players) who will compete against her. We find that the designed reservation system can not only elicit drivers' truthful demand reports but also achieve the optimal performance of the system. In this short paper we briefly describe our system and the main solution approaches we use. © WMSCI *** right reserved.

关键词： Costs

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Upper Bound Scalability on Achievable Rates of Batched Codes for Line networks

Upper Bound Scalability on Achievable Rates of Batched Codes...

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IEEE International Symposium on Information Theory

作者： Shenghao Yang Jie Wang School of Science and Engineering and the Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology The Chinese University of Hong Kong Shenzhen Shenzhen China

ISBN: (数字)9781728164328

ISBN: (纸本)9781728164335

The capacity of line networks with buffer size constraints is an open, but practically important problem. In this paper, the upper bound on the achievable rate of a class of codes, called batched codes, is studied for line networks where the channels have 0 zero-error capacity. Batched codes enable a range of buffer size constraints, and are general enough to include special coding schemes studied in the literature for line networks. Existing works have characterized the achievable rates of batched codes for several classes of parameter sets, but leave the cut-set bound as the best existing general upper bound. In this paper, we provide upper bounds on the achievable rates of batched codes as functions of line network length for these parameter sets. Our upper bounds in order of the network length match with the existing achievability results.

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R-N Algorithm for Crowdsensing On-street Parking Spaces

R-N Algorithm for Crowdsensing On-street Parking Spaces

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International wireless Communications and Mobile Computing Conference, IWCMC

作者： Wenjun Zheng Ruizhi Liao School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology China

Parking becomes an insurmountable problem in cities as the usage of cars becomes common and the urbanization trend continues. Many efforts have been made to reduce the parking pressure by developing real-time sensing techniques or big data based parking occupancy prediction models. In this paper, we focus on a crowdsensing solution where ultrasonic sensors are chosen as the detecting devices. An R-N algorithm based on an innovative crowdsensing solution is developed to enhance the detection accuracy. The performance of the proposed R-N algorithm is evaluated by an analytical model. The results prove that the crowdsensing detection accuracy can be improved by employing the proposed R-N algorithm.

关键词： Performance evaluation wireless communication Crowdsensing Urban areas Predictive models Prediction algorithms Market research

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