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Human mobility patterns refer to the regularities and trends in the way people move, travel, or navigate through different geographical locations over time. Detecting human mobility patterns is essential for a variety of applications, including smart cities, transportation management, and disaster response. The accuracy of current mobility prediction models is less than 25%. The low accuracy is mainly due to the fluid nature of human movement. Typically, humans do not adhere to rigid patterns in their daily activities, making it difficult to identify hidden regularities in their data. To address this issue, we proposed a web platform to visualize human mobility patterns by abstracting the locations into a set of places to detect more realistic patterns. However, the platform was initially designed to detect individual mobility patterns, making it unsuitable for representing the crowd in a smart city scale. Therefore, we extend the platform to visualize the mobility of multiple users from a city-scale perspective. Our platform allows users to visualize a graph of visited places based on their historical records using a modified PrefixSpan approach. Additionally, the platform synchronizes, aggregates, and displays crowd mobility patterns across various time intervals within a smart city. We showcase our platform using a real dataset., Comment: 4 pages, 8 figures. This is an accepted demo paper and it will appear in the Proceedings of the International Conference on Distributed Computing Systems (ICDCS)

Understanding human mobility is essential for the development of smart cities and social behavior research. Human mobility models may be used in numerous applications, including pandemic control, urban planning, and traffic management. The existing models' accuracy in predicting users' mobility patterns is less than 25%. The low accuracy may be justified by the flexible nature of the human movement. Indeed, humans are not rigid in their daily movement. In addition, the rigid mobility models may result in missing the hidden regularities in users' records. Thus, we propose a novel perspective to study and analyze human mobility patterns and capture their flexibility. Typically, the mobility patterns are represented by a sequence of locations. We propose to define the mobility patterns by abstracting these locations into a set of places. Labeling these locations will allow us to detect close-to-reality hidden patterns. We present IMAP, an Individual huMAn mobility Patterns visualizing platform. Our platform enables users to visualize a graph of the places they visited based on their history records. In addition, our platform displays the most frequent mobility patterns computed using a modified PrefixSpan approach., Comment: 3 pages, 2 figures. This is an accepted demo paper and it will appear in the Proceedings of The 28th Annual International Conference on Mobile Computing and Networking (MobiCom 2022)

In contrary to elastic media, it is easy to attain one-way coupling feature among electrical elements, which enables unidirectional transmission of electrical wave. In this paper, we explore and exploit the interaction of a piezoelectric beam with a one-way electrical transmission line to facilitate nonreciprocal transmission of elastic wave in the linear fashion. Theoretical dispersion analysis and numerical simulations are performed to reveal transmission behaviors of elastic wave in the presented piezoelectric metastructure. It is uncovered that, when the one-way electrical coupling feature is introduced, local-resonance bandgaps are maintained in opposite directions of the piezoelectric metastructure. However, the bandgap attenuation capability in one direction is increased compared to conventional local-resonance metastructures, in which no electrical coupling exists between cells, while that in the other direction is decreased. Therefore, nonreciprocal transmission of elastic wave emerges in this system due to the distinct bandgap attenuation capability. It is also revealed that this sort of nonreciprocal wave attenuation capability is adaptive with the one-way electrical coupling coefficient and the resistance of electrical cells. An experimental set-up of the piezoelectric metastructure is built and experimental results verify the nonreciprocity property and its adaptiveness. Overall, the presented piezoelectric metastructure provides a linear and concise approach to realize adaptive nonreciprocal transmission of elastic wave., Comment: 19 pages, 11 figures

In this paper, we present a piezo-metastructure shunted with bistable circuits to achieve adaptive nonreciprocal elastic wave transmission. Static properties of the bistable circuit are first investigated, followed by numerical investigation of wave transmission characteristics on the nonlinear piezo-metastructure. Both the local-resonance bandgap and the bandgap transmission phenomenon, also known as supratransmission, are explored and investigated. By introducing circuit asymmetry, the supratransmission thresholds, critical excitation amplitudes to enable bandgap transmission, are found at different levels for the different wave transmission directions and hence creating an excitation amplitude range within which nonreciprocal wave transmission can be facilitated. Effect of the asymmetry factor on nonreciprocity properties is subsequently analyzed and the trade-offs between the forward transmission amplitude and the range of excitation with nonreciprocity are identified. Additionally, it is demonstrated that wave transmission characteristics of the proposed nonlinear piezo-metastructure can be adaptively tuned by conveniently adjusting stable equilibria of the bistable circuit. Lastly, the observed wave transmission properties are further corroborated by experimental investigations. Overall, the results illustrate a novel means to manipulate unidirectional elastic wave transmission using a nonlinear piezo-metastructure., Comment: 12 pages, 14 figures