Limited Sensing and Deep Data Mining: A New Exploration of Developing City-Wide Parking Guidance Systems

Zou, Wan; Sun, Yen; Lu, Qinghao; Nie, Yong; Sun, Tianfu; Zhou, Yimin; Peng, Lei

doi:10.1109/mits.2020.2970185

Cited by 69 publications

(24 citation statements)

References 19 publications

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“…Whenever the rollers pass over the surface of the crack then the changes were observed and it mainly happened in the form of changes in vibration signal which are generated by different stress levels. During the entry level of defect, it will generate the low or medium-level frequency event and the result was formed which is not so much helpful for the understanding of vibration signature, on further traveling the roller strikes the base will result in the high-frequency event and much more helpful in drawing the complete information regarding stress originating zone [ 67 , 68 , 69 ]. Furthermore, the exit part of the defect will again generate a high level of stress and result in damage to the edge of the crack [ 70 , 71 , 72 ].…”

Section: Resultsmentioning

confidence: 99%

Identification of localized defects and fault size estimation of taper roller bearing (NBC_30205) with signal processing using the Shannon entropy method in MATLAB for automobile industries applications

Kumar¹,

Singh²,

Sharma³

et al. 2022

Heliyon

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Section: Resultsmentioning

confidence: 99%

Identification of localized defects and fault size estimation of taper roller bearing (NBC_30205) with signal processing using the Shannon entropy method in MATLAB for automobile industries applications

Kumar¹,

Singh²,

Sharma³

et al. 2022

Heliyon

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“…According to the idea of policy-based advantage function [20], when the reward of an action is greater than the valuation of Critic V c ritic, its probability goes up, otherwise, goes down. Then, the gradient of Actor (i.e., Selector) ∇ Rs π , can be written as (8).…”

Section: • Selector Updatingmentioning

confidence: 99%

“…Therefore, optimizing the allocation of parking resources is a critical and urgent issue. There have been many solutions proposed to address this problem and parking occupancy prediction (POP) plays a vital role in most of them [3,4], examples including dynamic parking charges [5,6], parking guidance [7,8], and shared parking [9].…”

Section: Introductionmentioning

confidence: 99%

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Adaptation and Learning to Learn (ALL): An Integrated Approach for Small-Sample Parking Occupancy Prediction

Liu

et al. 2022

Mathematics

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Parking occupancy prediction (POP) plays a vital role in many parking-related smart services for better parking management. However, an issue hinders its mass deployment: many parking facilities cannot collect enough data to feed data-hungry machine learning models. To tackle the challenges in small-sample POP, we propose an approach named Adaptation and Learning to Learn (ALL) by adopting the capability of advanced deep learning and federated learning. ALL integrates two novel ideas: (1) Adaptation: by leveraging the Asynchronous Advantage Actor-Critic (A3C) reinforcement learning technique, an auto-selector module is implemented, which can group and select data-scarce parks automatically as supporting sources to enable the knowledge adaptation in model training; and (2) Learning to learn: by applying federated meta-learning on selected supporting sources, a meta-learner module is designed, which can train a high-performance local prediction model in a collaborative and privacy-preserving manner. Results of an evaluation with 42 parking lots in two Chinese cities (Shenzhen and Guangzhou) show that, compared to state-of-the-art baselines: (1) the auto-selector can reduce the model variance by about 17.8%; (2) the meta-learner can train a converged model 102x faster; and (3) finally, ALL can boost the forecasting performance by about 29.8%. Through the integration of advanced machine learning methods, i.e., reinforcement learning, meta-learning, and federated learning, the proposed approach ALL represents a significant step forward in solving small-sample issues in parking occupancy prediction.

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“…Route diversions, parking availability, electronic toll collection, and active prediction help are examples of convenience‐centered applications 1,7,8 . So, vehicle networks must meet some most stringent standards in all these essential application fields 2,9 . Time‐critical Vehicle‐to‐Vehicle (V2V) safety applications necessitate ultra‐reliable low‐latency communication, with the critical cleanliness of status updates 10,11 .…”

Section: Introductionmentioning

confidence: 99%

Dependable and reliable cloud‐based architectures for vehicular communications: A systematic literature review

Yang

et al. 2023

Int J Communication

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Traffic congestion, air pollution, fuel wastage, and car accidents are all exacerbated by increased traffic. Thus, vehicular communications, which refer to information transmission between cars, pedestrians, and infrastructures, have lately gained popularity and been extensively explored due to their enormous potential to enable intelligent transportation and various safety applications. Manually piloted cars and automated vehicles can acquire relevant information via vehicular communications to enhance traffic security and boost entertainment services. The basic concept of automobile clouds was originally published in the literature not long ago, and several suggested structural approaches have been presented in this study thus far. Several academics have concentrated on the structural layout to address various problems and, as a result, satisfy user expectations in order to give dependable services. We examined various vehicular cloud topologies in this study. We also offered a complete summary of current network layer research on allowing efficient vehicle communications and examined specific security, architectural, and reliability concerns in vehicular clouds. Also, the taxonomy of vehicular networks was discussed in terms of the service link between vehicular networks and cloud computing. Ultimately, we discussed the research prospects available. The results showed that security and privacy challenges are among the most important challenges.cloud computing, vehicular ad hoc network, vehicular cloud architecture, vehicular communication | INTRODUCTIONBecause of its vast application domains, like commercial-oriented, safety-relevant, and convenience-centered applications, 1-3 vehicular networks have recently gained much study interest. 4 Real-time traffic, notice after a crash, cooperative message transmission, warning of a coordinated collision, and traffic vigilance are some safety-relevant applications that may be categorized. 5 Distant vehicle personalization/diagnostics, digital map downloading, Internet access, value-added commercials and advertisements, and real-time entertainment video relay are included in the commercial-centered application. 6 Route diversions, parking availability, electronic toll collection, and active prediction help are examples of convenience-centered applications. 1,7,8 So, vehicle networks must meet some most stringent standards in all these essential application fields. 2,9 Time-critical Vehicle-to-Vehicle (V2V) safety applications necessitate

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Limited Sensing and Deep Data Mining: A New Exploration of Developing City-Wide Parking Guidance Systems

Cited by 69 publications

References 19 publications

Identification of localized defects and fault size estimation of taper roller bearing (NBC_30205) with signal processing using the Shannon entropy method in MATLAB for automobile industries applications

Identification of localized defects and fault size estimation of taper roller bearing (NBC_30205) with signal processing using the Shannon entropy method in MATLAB for automobile industries applications

Adaptation and Learning to Learn (ALL): An Integrated Approach for Small-Sample Parking Occupancy Prediction

Dependable and reliable cloud‐based architectures for vehicular communications: A systematic literature review

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