User Movement Research Articles

Mobile Data Traffic Prediction by Exploiting Time-Evolving User Mobility Patterns

Understanding mobile data traffic and forecasting future traffic trend is beneficial to wireless carriers and service providers who need to perform resource allocation and energy saving management. However, predicting wireless traffic accurately at large-scale and fine-granularity is particularly challenging due to the following two factors: the spatial correlations between the network units (i.e., a cell tower or an access point) introduced by user arbitrary movements, and the time-evolving nature of user movements which frequently changes with time. In this paper, we use a time-evolving graph to formulate the time-evolving nature of user movements, and propose a model Graph-based Temporal Convolutional Network (GTCN) to predict the future traffic of each network unit in a wireless network. GTCN can bring significant benefits to two aspects. (1) GTCN can effectively learn intra- and inter-time spatial correlations between network units in a time-evolving graph through a node aggregation method. (2) GTCN can efficiently model the temporal dynamics of the mobile traffic trend from different network units through a temporal convolutional layer. Experimental results on two real-world datasets demonstrate the efficiency and efficacy of our method. Compared with state-of-the-art methods, the improvement of the prediction performance of our GTCN is 3.2 to 10.2 percent for different prediction horizons. GTCN also achieves 8.4× faster on prediction time.

An examination of mobile phone pointing in surface mapped spatial augmented reality

We investigate mobile phone pointing in Spatial Augmented Reality (SAR), where digital content is mapped onto the surfaces of a real physical environment. Three pointing techniques are compared: raycast, viewport, and direct. A first experiment examines these techniques in a realistic five-projector SAR environment with representative targets distributed across different surfaces. Participants were permitted free movement, so variations in target occlusion and target view angle occurred naturally. A second experiment validates and further generalizes findings by strictly controlling target occlusion and view angle in a simulated SAR pointing task using an AR HMD. Overall, results show raycast is fastest for non-occluded targets, direct is most accurate, and fastest for occluded targets in close proximity, and viewport falls in between. Using the experiment data, we formulate and evaluate a new Fitts’ model combining two spatial configurations in a SAR pointing task to capture key characteristics, initial target occlusion, target view angle, and user movement. Analysis shows it is a better predictor than previous models.

Development of a Novel Omnidirectional Treadmill-Based Locomotion Interface Device with Running Capability

To achieve an immersive virtual reality (VR) environment, omnidirectional treadmills (ODTs) allow users to perform locomotion in any direction. However, existing ODTs are heavy and complex, and operate at low speeds. This limits fast user motion and prevents natural interactions in real applications such as military training programs and interactive games. In this paper, we introduce a novel locomotion interface device with running capability, which uses an omnidirectional treadmill with a new power transmission mechanism and a locomotion controller that enables the user to make fast movements. As a result of the improved power transmission performance due to the simple and relatively lightweight structure, the proposed two-dimensional treadmill can generate a maximum speed of 3 m/s, with an acceleration of 3 m/s2. Moreover, through a pilot test with the proposed locomotion interface device, we verified that the fast directional changes during walking and running with the designed speed adaptation controller do not exceed the acceleration performance of the proposed system. Due to its wide range of movement speeds and acceleration capabilities, and lack of any motion constraints, the proposed locomotion interface device with a novel ODT can be used as a representative platform in various VR environments to enhance the immersive experience.

The Dynamics of Productive and Non-Productive Spaces in Coastal Tourism Areas in Denpasar

Tourism in Bali has redefined the use of space. The formation of new activities carried out by new users, has changed the way people use space. Spaces exist because they form and some use, create governance and bring up spatial practices that may be hampered by the current digital age. This research will examine the process of redefinition of space, the formation of productive and non-productive spaces in accordance with the representation expected by the community. In this study, Sanur Beach, a traditional area that has become a tourism space, will be used as a case study. The method Qualitative, by mapping activities based on time segments for space use, interviews to determine user expectations and experiences, identifying patterns to find out how governments regulate space and building data representations through simulations of the movement of space users. The most significant result is the presence of a new identity in the meaning of space, which has been transformed due to spatial practices that are influenced by space users and the development of digital technology. Thus, the use of space in the era of global tourism in which different cultural backgrounds of space users affect the definition of space. This is where the space planner needs to consider how the representation of space by the user has implications for the regulations of the government and customary regulation.

A Home-Based Bilateral Rehabilitation System With sEMG-based Real-Time Variable Stiffness.

Bilateral rehabilitation allows patients with hemiparesis to exploit the cooperative capabilities of both arms to promote the recovery process. Although various approaches have been proposed to facilitate synchronized robot-assisted bilateral movements, few studies have focused on addressing the varying joint stiffness resulting from dynamic motions. This paper presents a novel bilateral rehabilitation system that implements a surface electromyography (sEMG)-based stiffness control to achieve real-time stiffness adjustment based on the user's dynamic motion. An sEMG-driven musculoskeletal model that incorporates the muscle activation and muscular contraction dynamics is developed to provide reference signals for the robot's real-time stiffness control. Preliminary experiments were conducted to evaluate the system performance in tracking accuracy and comfortability, which showed the proposed rehabilitation system with sEMG-based real-time stiffness variation achieved fast adaption to the patient's dynamic movement as well as improving the comfort in robot-assisted bilateral training.

Radiation Pressure Field Reconstruction for Ultrasound Midair Haptics by Greedy Algorithm With Brute-Force Search.

Non-contact tactile presentation using ultrasound phased arrays is becoming a powerful method for providing haptic feedback on bare skin without restricting the user's movement. In such ultrasonic mid-air haptics, it is often necessary to generate multiple ultrasonic foci simultaneously, which requires solving the inverse problem of amplitudes and phases of the transducers in a phased array. Conventionally, matrix calculation methods have been used to solve this inverse problem. However, a matrix calculation requires a non-negligible amount of time when the number of control points and the number of transducers in the array are large. In this article, we propose a simple method based on a greedy algorithm and brute-force search to solve the field reconstruction problem. The proposed method directly optimizes the desired field without matrix calculation or target field phase optimization. The empirical results indicate that the proposed method can reproduce the target sound with an accuracy of more than 80%.

Enhancing Virtual Walking Sensation Using Self-Avatar in First-Person Perspective and Foot Vibrations

Walking is a fundamental physical activity in humans. Various virtual walking systems have been developed using treadmill or leg-support devices. Using optic flow, foot vibrations simulating footsteps, and a walking avatar, we propose a virtual walking system that does not require limb action for seated users. We aim to investigate whether a full-body or hands-and-feet-only walking avatar with either the first-person (experiment 1) or third-person (experiment 2) perspective can convey the sensation of walking in a virtual environment through optic flows and foot vibrations. The viewing direction of the virtual camera and the head of the full-body avatar were linked to the actual user's head motion. We discovered that the full-body avatar with the first-person perspective enhanced the sensations of walking, leg action, and telepresence, either through synchronous or asynchronous foot vibrations. Although the hands-and-feet-only avatar with the first-person perspective enhanced the walking sensation and telepresence, compared with the no-avatar condition, its effect was less prominent than that of the full-body avatar. However, the full-body avatar with the third-person perspective did not enhance the sensations of walking and leg action; rather, it impaired the sensations of self-motion and telepresence. Synchronous or rhythmic foot vibrations enhanced the sensations of self-motion, waking, leg action, and telepresence, irrespective of the avatar condition. These results suggest that the full-body or hands-and-feet avatar is effective for creating virtual walking experiences from the first-person perspective, but not the third-person perspective, and that the foot vibrations simulating footsteps are effective, regardless of the avatar condition.

The Impact of an Augmented-Reality Game on Local Businesses: A Study of Pokémon Go on Restaurants

Augmented reality (AR)–based applications have been growing in prominence. Pokémon Go, one of the most popular AR game applications, has been engaging in strategic partnership with businesses. The game combines geospatial elements with gamification practices to incentivize user movement in the physical world. In this study, we examine the value of such strategic partnerships between Pokémon Go and associated businesses. Specifically, we use data of the online reviews for a firm to study consumer engagement and consumer perception after the release of the game on its associated businesses. We find that restaurants associated with Pokémon Go do indeed enjoy a higher level of consumer engagement and more positive consumer perception. We also find that characteristics of the business significantly moderate this impact overall. Using a parsimonious analytical model, we also demonstrate the mechanism behind these results. Our study provides insights into consumer economic behavior in the context of AR applications. We further inform the business owners and policymakers regarding the potential value of such strategic business partnerships with such applications.

Service migration in multi-access edge computing: A joint state adaptation and reinforcement learning mechanism

With the development of the internet of things (IoT), the concept of an edge network has been gradually expanding to other fields including internet of vehicles, mobile communication networks and smart grids. Because the resources of terminals are limited, the long-distance movements of users will increase the running costs of the services that are offloaded to edge servers, and even the services on terminals will stop running. Another problem is that resource shortages or hardware failures of these edge networks can affect the service migration policy. In this paper, a novel service migration method based on state adaptation and deep reinforcement learning is proposed to efficiently overcome network failures. Before migration, we define four edge network states to discuss the migration policy and adopt the two-dimensional movement around the edge servers to adapt to the applications scenarios of our work. Then, we use the satisfiability modulo theory (SMT) method to solve the candidate space of migration policies based on cost constraints, delay constraints and available resource capacity constraints to shorten the interruption time. Finally, the service migration problem can be transformed into the optimal destination server and low-cost migration path problem based on the Markov decision process by the deep Q-learning (DQN) algorithm. Moreover, we theoretically prove the rate of convergence in the learning rate function of our algorithm to improve the convergence rate. Our experimental results demonstrate that our proposed service migration mechanism can effectively shorten the delays from service interruptions, and better avoid the impact of edge network failure on the migration results and, thus, improve the users’ satisfaction.

Development and feasibility of a soft pneumatic-robotic glove to assist impaired hand function in quadriplegia patients: A pilot study

One of the common disorders in people with quadriplegia is having a weak grip strength that can affect activities of daily living (ADL). This study presents the design of a soft robotic glove via pneumatic actuators and feasibility according to a range of motion (ROM) of proximal interphalangeal (PIP) joint and user friendly.The soft robotic glove includes a neoprene cockup, two pumps, a controller that adjusts the pressure of the pumps, two-direction parts, and two silicone tubes placed on an index and middle fingers. A total of seven subjects (2healthy, 5quadriplegia patients) participated in this project. Performance of the device was verified through assessment in healthy participants first and then spinal cord injury (SCI) participants. The device evaluated the range of motion (ROM) of a proximal interphalangeal (PIP) joint. Then, subjects completed a satisfaction questionnaire.Results showed the ROM of the PIP joint (p value = 0.042) increased by using the robotic glove. The average score of the satisfaction questionnaire was 4.24 which was beyond the desirable threshold. In conclusion, the glove obtained ROM requirements to the grip usual objects and underlined the potential for assisting SCI participants in ADLs. Providing motion in all fingers should be investigated and developed in the future.

VIRTUAL CAPSTONE WORKSPACE

- Virtual reality aims at immersing a user in a virtual environment. Dedicated virtual reality technologies of human–computer interaction enables linking the user and a virtual environment in capturing the user's motion. Our primary purpose is to improve communication between the students, especially the team members in STEM schools in Egypt. The application supports students in the capstone project for each grade. It is supported by tools to make a simulation for the project. Also, it is supported by a virtual reality headset. As we mentioned, VR is used in many fields, and it isolates the person from the surrounded environment altogether. VR is used instead of Anesthesia because of its effect in isolating humans from the surrounded environment. That will increase communication and concentration between the team members and make them feel that they are in an actual meeting. Every person will have an avatar in the application represent him. This avatar will translate every member's motion in the meeting by the sensor in the VR headset. A mic supports the VR headset. Every team will have a specific room, this room is where they can make all meetings, and all the work, achievements, and updates of the group will save in this room. Also, the application work as a director for the work

Artificial Lighting Strategies On Campus Pedestrian Path In Increasing The Safety of Walking at Night (Case Study: University of Bengkulu)

Pedestrian path in the campus is strategic route dominated by the movement of students and other users from 06.00 AM until 20.00 PM. The unavailability of artificial lighting at night on the pedestrian paths on the campus of the University of Bengkulu causes low visibility for pedestrian path users and have an impact on walking difficulties, negative behaviour and opportunities for criminal acts. The purpose of this study is identifying frequently used pedestrian paths and examines the principles of artificial lighting must be applied pedestrian users can walk safely and comfortably in the campus at night. These conditions can increasing liveability of pedestrian paths on the campus at night. The study sites were divided into 10 zones. Each zone will be analysed using combination method of field survey methods, online questionnaires, and simulation methods using Dialux evo 9.0. Data from questionnaire and field survey result will be used to decide the artificial lighting plan on the pedestrian path. While Dialux evo 9.0 simulation are to simulate the planned light points The results of the research are determining an artificial lighting strategy is evenly distributed along the pedestrian path.

Analysis of the Effect of Common Disturbances on the Safety of a Wearable Tremor Suppression Device

The advent of wearable technology has enabled a large number of externally worn mechatronic devices to be developed and tested on people with movement disorders. The complexity of these disorders and the variety of conditions across different patients have resulted in a pressing demand for the incorporation of intelligent control systems, especially for a wearable tremor suppression device (WTSD) that can suppress tremor without impeding the user's voluntary motion. Several devices have been developed to reduce tremor; however, the evaluations of these devices have only been done in a controlled lab setting, while the functionality and ability to avoid user injury under the effect of disturbances during daily use have not been investigated. In this study, the performance of a WTSD was tested with several commonly used tremor suppression control systems, i.e., Weight-frequency Fourier Linear Combiner (WFLC), Bandlimited Multiple Fourier Linear Combiner, and enhanced High-order WFLC-based Kalman Filter, on a bench-top tremor simulator. These systems were also tested under the influence of three simulated disturbances that are commonly seen in real life, i.e., data mutation, sensor drift, and measurement loss. The experimental evaluation showed that none of these systems are safe under the disturbances. The tremor power suppression ratio (67.8%–94.2%) of the WTSD was not significantly lowered by the disturbances; however, the error when tracking voluntary motion significantly increased by 8.8 $^\circ$ –93.6 $^\circ$ , which may present a safety hazard to the users. The results of this study emphasize the importance of integrating safety measures into intelligent WTSDs.

Predictive Exoskeleton Control for Arm-Motion Augmentation Based on Probabilistic Movement Primitives Combined With a Flow Controller

There are many work-related repetitive tasks where the application of exoskeletons could significantly reduce the physical effort by assisting the user in moving the arms towards the desired location in space. To make such control more user acceptable, the controller should be able to predict the motion of the user and act accordingly. This letter presents an exoskeleton control method that utilizes probabilistic movement primitives to generate predictions of user movements in real-time. These predictions are used in a flow controller, which represents a novel velocity-field-based exoskeleton control approach to provide assistance to the user in a predictive way. We evaluated our approach with a haptic robot, where a group of twelve participants had to perform movements towards different target locations in the frontal plane. We tested whether we could generalize the predictions for new and unknown target locations whilst providing assistance to the user without changing their kinematic parameters. The evaluation showed that we could accurately predict user movement intentions while at the same time significantly decrease the overall physical effort exerted by the participants to achieve the task.

SoundLip

As a natural and convenient interaction modality, voice input has now become indispensable to smart devices (e.g. mobile phones and smart appliances). However, voice input is strongly constrained by surroundings and may raise privacy leakage in public areas. In this paper, we present SoundLip, an end-to-end interaction system enabling users to interact with smart devices via silent voice input. The key insight is to use inaudible acoustic signals to capture the lip movements of users when they issue commands. Previous works have considered lip reading as a naive classification task and thus can only recognize individual words. In contrast, our proposed system enables lip reading at both word and sentence levels, which are more suitable for daily-life use. We exploit the built-in speakers and microphones of smart devices to emit acoustic signals and listen to their reflections, respectively. In order to better abstract representations from multi-frequency and multi-modality acoustic signals, we elaborate a hierarchical convolutional neural network (HCNN) to serve as the front-end as well as recognize individual word commands. Then, for the sentence-level recognition, we exploit a multi-task encoder-decoder network to get around temporal segmentation and output sentences in an end-to-end way. We evaluate SoundLip on 20 individual words and 70 sentences from 12 participants. Our system achieves an accuracy of 91.2% at word-level and a word error rate of 7.1% at sentence-level in both user-independent and environment-independent settings. Given its innovative solution and promising performance, we believe that SoundLip has made a significant contribution to the advancement of silent voice input technology.

HYBRID CLASSIFICATION STRATEGY OF EMG SIGNALS FOR ROBOTIC HAND CONTROL

Among the different bio-signals modalities, Electromyographic signal (EMG) has been one of the frequently used signals in the bio-robotics applications field. This is due to the fact that the EMG reflects directly the muscle activity of the user following the human motion intention. Consequently, the decoding of this intention is an essential task for controlling devices such as prosthetic hands and exoskeletons, based on EMG signals. This paper deals with the processing of EMG signals of the forearm muscles, in order to control two degrees of freedom (2 DoFs) robotic hand. The main contribution of this paper is the proposal of a hybrid approach that combines a pattern and a non-pattern recognition-based strategy. The proposed approach aims to take advantage of both strategies and overcome their shortcomings leading to a better analysis of the user movement intention. The EMG recorded signals are processed for feature extraction based on a Wavelet Packet Decomposition (WPD) method and classification using an Artificial Neural Network (ANN). Furthermore, we investigate the effect of the various parameters such as the applied force level, the number of the EMG channels and the window length of the EMG signal. The proposed approach is validated experimentally under realistic conditions. Very interesting results have been obtained for user intention decoding.

Deep Q-Learning for Two-Hop Communications of Drone Base Stations.

In this paper, we address the application of the flying Drone Base Stations (DBS) in order to improve the network performance. Given the high degrees of freedom of a DBS, it can change its position and adapt its trajectory according to the users movements and the target environment. A two-hop communication model, between an end-user and a macrocell through a DBS, is studied in this work. We propose Q-learning and Deep Q-learning based solutions to optimize the drone’s trajectory. Simulation results show that, by employing our proposed models, the drone can autonomously fly and adapts its mobility according to the users’ movements. Additionally, the Deep Q-learning model outperforms the Q-learning model and can be applied in more complex environments.

Multi-Technique Redirected Walking Method

The Room-Scale locomotion method is one of the most realistic locomotion methods used in virtual reality technologies. This is due to the natural interaction obtained through the tracking of its controllers and the head-mounted display with six degrees of freedom. However, its mapping by position between the physical and the virtual world limits the user's movement to the physical workspace provided by the corresponding device. Redirected Walking methods use gain algorithms that add modifications to the virtual movement of the user, optimizing the virtual workspace in the same physical workspace. In this paper, we develop a new Redirected Walking method, which combines the modification of three gain algorithms (curvature gain, rotation gain, and translation gain), a new algorithm (deviation gain), a path predictive method of the user's locomotion, a proportional distance to the center function, and a user direction smoothing function that softens the effect of the algorithms. Complementing the new method, we offer an automatic calibration system that allows the user to use our method in a personalized way.

The transportation improvement in Tyumen

The article discusses the need to improve the road network in Tyumen. The existing regulatory framework in the field of integrated development of streets and city roads has been analyzed, and the basic requirements that must be met by the city's transport system have been established. In this regard, the main directions are highlighted, which are necessary for accounting to determine measures to improve the network of streets and city roads for any agglomeration unit. On the example of Tyumen, a detailed analysis of these directions is carried out and, through its results, the stages of reorganization of the road network are determined to ensure the comfortable movement of all road users.

Protocol for reliable energy data collection based on mobile fog computing

Fog computing can quickly calculate and store user needs, and cooperate with remote cloud computing to provide more powerful computing capabilities. In this paper, the passive cache is optimized, and the Dynamic Cooperate Proactive Cache (DCPC) algorithm based on user mobility is proposed, which uses user movement information and request records collected by the fog server node to cache the content on the fog server node in advance. The algorithm combines the autoregressive differential moving average model to actively predict the requested content, which greatly improves the utilization of cache space. This paper proposes a wireless sensor network based on Lo Ra WAN to collect energy impact factors. In order to greatly extend the survival time of sensor networks, this paper proposes a data collection method based on the division of similar attribute regions. By selecting representative nodes and turning off redundant nodes, the sensor can be greatly improved while ensuring high accuracy of collected data. After system testing and simulation experiments, it is verified that the wireless sensor network developed in this paper can meet the collection requirements of energy impact factors, and the data collection method proposed can greatly extend the survival time of the sensor network.