Mobile Tracking Research Articles

Multi-Level and Multiple Aspect Semantic Trajectory Model: Application to the Tourism Domain

Here we design a semantic trajectory model responding to specific needs expressed by tourism analyst experts. Thus, this model takes into account: (i) the description of sequences of imbricated semantic segments, (ii) the definition of enrichment data integrating spatial, temporal and thematic dimensions and (iii) the association of such data with positions or with trajectory segments. Each of these features is necessary for the processing and analysis of tourist mobility data, which we will detail. For validation purposes, we experiment our model on two outdoor mobility track scenarios computed in a processing chain. We also show that our model is generic and extensible thanks to two other scenarios on different datasets.

Buckling under the action of loading by aerodynamic and inertial forces during ground track tests of aviation equipment

The article analyses the choice of a rational layout of the test object with a propulsion system (PS). One of the design examples of calculating the longitudinal stability and strength of the structure is given. The purpose of the article is to solve the problem of bending the elastic line of a cantilever tubular rod with a hinged termination during tests of a propulsion system for various aircrafts. On the example, the estimates of the approximate test object, accelerated on the track to a speed of 1200 m/s, are carried out. The aerodynamic loading of the structure of the mobile track installation is considered using the methods of mathematical modelling and the development of an algorithm for the numerical solution of the problem of bending the elastic line of a cantilever tubular rod. The deflection from the forces of external and internal loads of the outer shell of a movable track installation is considered, provided that the diameter of the outer contour is equal to the minimum and it is constant along the entire length.

The Digital Forest: Mapping a Decade of Knowledge on Technological Applications for Forest Ecosystems

AbstractForest ecosystem resilience is of considerable interest worldwide, particularly given the climate crisis, biodiversity loss, and recent instances of zoonotic diseases linked to deforestation and forest loss. Novel, digital‐based technologies are also increasingly ubiquitous. We provide a more comprehensive understanding of how these new technologies are being used for forest management in different sectors and contexts, and discuss potential implications and future research needs for forestry researchers, managers, and policymakers. We carried out a literature database search and scoping review to collect peer‐reviewed articles from 2010 to 2020, and developed a forest‐technology classification to identify hardware and/or software technologies and techniques, methodology used, forest management application(s), spatial and temporal context, subsequent challenges and limitations, and opportunities. A qualitative analysis revealed a strong emphasis on remote sensing‐based innovations for forest monitoring, planning, and management, where machine‐learning techniques also play an important role in data collection, processing, and analysis. Data fusion approaches are also becoming more common, enabled by open‐source data sets and data sharing practices. More emerging technologies and applications include virtual/augmented environments for understanding human‐nature relationships and behavior patterns, automated workflows for forestry operations, and urban green infrastructure mapping and ecosystem services assessments via social media and mobile tracking applications. The continued adoption of digital‐based tools will likely bring about new research questions about forest ecosystems as dynamic social, ecological, and technological landscapes, and future work should more closely examine how forestry researchers, managers, and stakeholders can anticipate and adapt to both environmental and technological uncertainty change in a forest‐ecosystem context.

Designing a prototype for Mentally Challenged and Alzheimer Patients

This work is the prototype of this system is mobile application which uses the GPS technology to track the patient and it help the gathering of information from satellites in order to find the exact coordinate of the Alzheimer patient, whenever the patient move away fro thr specific boundary which is given in the tracker like mobile and the mobile tracks the GPS location and the location send a message in the computer or smartphone through the cellular network system that the patient is out of location or boundary.

Back to nature: Norwegians sustain increased recreational use of urban green space months after the COVID-19 outbreak

In Oslo, as elsewhere, the COVID-19 outbreak and the following lockdown measures during spring 2020 led to increased use of urban green infrastructure. Whether this has led to more durable changes in recreation patterns remains an open question. We used mobile tracking data from 53,000 STRAVA users to explore the longevity of increases in recreational activity. We compared 2020 activity levels relative to a weather benchmark (i.e. baseline), defined as the activity one would have expected given the time of year and prevailing weather conditions. Recreational activity increased by 240% during the five weeks of comprehensive lockdown and were maintained until the summer vacation period in June/July when they dropped to baseline levels. Yet, during August they increased again to 89% above baseline. Although activity increased across all city land use zones, after lockdown there was a shift away from residential and commercial zones toward city green spaces including forests and protected areas. Cultural landscapes and protected areas received disproportionately high activity levels relative to the length of recreational trails available within them. Recreationists in the teenager demographic (13–19) exhibited a four-fold increase in their share of the STRAVA user-base at the start of lockdown. The COVID-19 pandemic and its disruptions to the status quo has had lasting effects over the short-term on the way Norwegian citizens recreate. Our findings reinforce the value of urban nature and open spaces for societal pandemic preparedness, particularly youths, during and after times of crisis.

Phases of collaborative mathematical problem solving and joint attention: a case study utilizing mobile gaze tracking

Given the recent development of mobile gaze-tracking devices it has become possible to view and interpret what the student sees and unravel the associated problem-solving processes further. It has also become possible to pinpoint joint attention occurrences that are fundamental for learning. In this study, we examined joint attention in collaborative mathematical problem solving. We studied the thought processes of four 15–16-year-old students in their regular classroom, using mobile gaze tracking, video and audio recordings, and smartpens. The four students worked as a group to find the shortest path to connect the vertices of a square. Combining information on the student gaze targets with a qualitative interpretation of the context, we identified the occurrences of joint attention, out of which 49 were joint visual attention occurrences and 28 were attention to different representations of the same mathematical idea. We call this joint representational attention. We discovered that ‘verifying’ (43%) and ‘watching and listening’ (35%) were the most common phases during joint attention. The most frequently occurring problem solving phases right after joint attention were also ‘verifying’ (47%) and ‘watching and listening’ (34%). We detected phase cycles commonly found in individual problem-solving processes (‘planning and exploring’, ‘implementing’, and ‘verifying’) outside of joint attention. We also detected phase shifts between ‘verifying’, ‘watching and listening’, and ‘understanding’ a problem, often occurring during joint attention. Therefore, these phases can be seen as a signal of successful interaction and the promotion of collaboration.

WITHDRAWN: Online geolocation-based mobile tracking system for protection purposes

In the dynamic era in which technological development is thriving and touches all aspects of our lives, it is important to focus on using this technology to retain the safety of human lives, especially when some geographical locations might form a certain threat to them. Therefore, the urge to develop an advanced online alarm system has come to be the most essential part when a person accidentally accesses a dangerous or forbidden zone. This development can be perfectly achieved through the technology of the Global positioning system (GPS). GPS technology was found for a long period, it enriched the geographic information systems (GISs) since it has an extreme demand to be used in different exploration, navigation, and protection in many fields such as the land, the sea, and the airborne. The main goal of the GPS has been focused on data collection and transferring from a targeted zone to a specific Geographic Information System Mapping Technology (GIS). Since computers and mobile devices has been included in the acceleration of rapid technological development, as it became affordable, available, and easy to use in every time and place it becomes easier to be involved in GPS-GIS systems. This paper focuses on designing and implementing a low-cost GPS system based on online tracking technology that has an individual alarming system to avoid entering risky fields through mobile application technology for detecting the movement in dangerous fields and to overcome the problem of expensive GIS solutions.The methodology and the implantation of the proposed system are the next parts of this paper while the results and the conclusions are the final parts.

Three-Dimensional Linear Restoration of a Tunnel Based on Measured Track and Uncontrolled Mobile Laser Scanning.

Traditional precision measurement adopts discrete artificial static observation, which cannot meet the demands of the dynamic, continuous, fine and high-precision holographic measurement of large-scale infrastructure construction and complex operation and maintenance management. Due to its advantages of fast, accurate and convenient measurement, mobile laser scanning technology is becoming a popular technology in the maintenance and measurement of infrastructure construction such as tunnels. However, in some environments without satellite signals, such as indoor areas and underground spaces, it is difficult to obtain 3D data by means of mobile measurement technology. This paper proposes a method to restore the linear of the point cloud obtained by mobile laser scanning based on the measured track center line. In this paper, the measured track position is interpolated with a cubic spline to calculate the translations, and the rotation parameters are calculated by combining the simulation design data. The point cloud of the cross-section of the tunnel under the local coordinate system is converted to the absolute coordinate system to calculate the tunnel line. In addition, the method is verified by experiments combined with the subway tunnel data, and the overall point error can be controlled to within 0.1 m. The average deviation in the horizontal direction is 0.0551 m, and that in the vertical direction is 0.0274 m. Compared with the previous methods, this method can effectively avoid the obvious deformation of the tunnel and the sharp increase in the error, and can process the tunnel point cloud data more accurately and quickly. It also provides better data support for subsequent tunnel analysis such as 3D display, completion survey, systematic hazard management and so on.

BTS guideline for the use of long-term macrolides

<h3>Abstract</h3> Standing balance is relatively more unstable when visually pursuing a moving target than when fixating a stationary one. These effects are common across age groups if the head is...

Automated Tracking Approaches for Studying Online Media Use: A Critical Review and Recommendations

ABSTRACT With the increasing importance of online information environments, researchers have started investigating direct measures of online media use, such as online tracking. Most existing studies using tracking data have so far relied on commercial solutions, but these have limitations in terms of their costliness, replicability, and applicability to certain research questions. Hence, different research groups are developing their own tracking solutions for academic purposes. In this paper, we provide a critical review and classification of the existing approaches, apt to guide research decisions on the appropriate tracking approach and tool. First, we develop criteria to distinguish different user-centric desktop and mobile tracking approaches and tools (types of information, technical complexity, privacy implementation, user experience, and availability). Second, we describe different tools and approaches – separately for desktop and mobile tracking – with concrete examples and evaluate them using the aforementioned criteria. Finally, we discuss how different mobile and desktop tracking solutions can complement each other and provide recommendations for future research.

Design of IoT based Real-Time Bus Tracking App using HF-RFID

Public Transportation is the major means of Bus among people. A recent survey by the National Sample Survey Organization says that about 62-66% of people use the bus as their mode of transport. Public Bus tracking system aims at providing the instant status of the bus to the users via an automated system. This paper describes a design of IoT enabled real time bus tracking system. In this work a bus tracking mobile phone app is developed, using that people can exactly locate the bus status and time to bus arrival at bus-stop. This work uses high frequency RFID tags at buses and RFID receivers at bus-stops and with NodeMCU real time RIFD tagging (bus running) information is collected and uploaded on cloud. Users can access the bus running and status from cloud on mobile app in real time.

Movement and Space Use of Grass Carp in the Sandusky River, Ohio: Implications for Lake Erie Eradication Efforts

AbstractThe Grass Carp Ctenopharyngodon idella is an invasive species to the Laurentian Great Lakes that was first detected in the 1980s. The western basin of Lake Erie is the putative invasion front for the Great Lakes, with spawning known to occur in two of the basin’s tributaries (Sandusky and Maumee rivers). Targeted removal is being used to reduce Grass Carp abundance, with an ultimate aim of eradication in part to prevent spread and establishment in the other Great Lakes; response efforts are being concentrated in the Sandusky River due to its heavy use by Grass Carp and because it is the tributary where spawning occurs consistently. The goal of this research was to identify areas in the Sandusky River where Grass Carp aggregate and identify variables that influence movement to improve efficiency of response efforts. Movement and space use of 27 Grass Carp were monitored using acoustic telemetry. Detection data were used to estimate movement and daily detection rates and also used in a spatial capture–recapture model to estimate activity centers of tagged fish. Grass Carp movement was highest when daily discharge and water temperature exceeded 31 m3/s and 18°C, respectively, and next highest when discharge exceeded 31 m3/s and temperature was between 4.5°C and 18.0°C. Daily detection rates at receivers and concentrations of activity centers suggested that aggregations occurred between river kilometers (RKMs) 34 and 36 and at RKM 45. During spawning conditions, Grass Carp also aggregated near RKM 48.6, which is proximal to suspected spawning locations. We recommend concentrating response efforts in these general locations and using passive capture gear when Grass Carp are the most mobile. Response efforts could be further refined by using a variety of acoustic telemetry monitoring techniques, including fine‐scale positioning, real‐time receivers, and mobile tracking to provide precise location and timing for removal actions.

Combining Social Media and Mobile Positioning Data in the Analysis of Tourist Flows: A Case Study from Szeged, Hungary

Despite the growing importance of mobile tracking technology in urban planning and traffic forecasting, its utilization in the understanding of the basic laws governing tourist flows remains limited. Knowledge regarding the motivations and spatial behavior of tourists has great potential in sustainable tourism studies. In this paper, we combine social media (Twitter) and mobile positioning data (MPD) in the analysis of international tourism flows in Szeged, a secondary urban center in Hungary. First, the content of geotagged and non-geotagged Twitter messages referring to Szeged in a six-month period of 2018 was analyzed. In this way specific events attracting foreign tourists were identified. Then, using MPD data of foreign SIM cards, visitor peaks in the investigated period were defined. With the joint application of the social media and mobile positioning analytical tools, we were able to identify those attractions (festivals, sport and cultural events, etc.) that generated significant tourism arrivals in the city. Furthermore, using the mixed-method approach we were also able to analyze the movements of foreign visitors during one large-scale tourism event and evaluate its hinterland. Overall, this study supports the idea that social media data should be combined with other real-time data sources, such as MPD, in order to gain a more precise understanding of the behavior of tourists. The proposed analytical tool can contribute to methodological and conceptual development in the field, and information gained by its application can positively influence not only tourism management and planning but also tourism marketing and placemaking.

The Effect of Sheltering in Place on Police Reports of Domestic Violence in the US

This study analyzes the effect of sheltering in place in response to COVID-19 on domestic violence incidents in the US using novel daily mobile device tracking data, the timing of shelter-in-place orders, and dispatch and crime data from twenty-eight police departments in eighteen US states. Findings show that reports of domestic violence rise after local shelter-in-place orders are enacted and that domestic violence increases with measures of sheltering in place, as indicated by mobile device tracking data. This result is consistent with an exposure reduction theory of domestic violence and, in the context of the COVID-19 pandemic, underscores the importance of providing potential victims of violence with spaces that are safe from abusers and risk of infection. When applied to the entire US, it is estimated that sheltering in place increased domestic violence by approximately 6 percent, or more than 24,000 cases, from March 16 to April 30, 2020. HIGHLIGHTS Having to confine at home with an abuser can increase violence. Mobile device tracking data was used to measure the percentage of people who stayed at home all day. US police reports of domestic violence rose with shelter-in-place orders and fell when efforts relaxed. The real effect may be larger due to pandemic-related reporting issues. Economic and behavioral interventions for potential victims will not fully counteract the effects of exposure.

The corona crisis, data protection and tracking apps in the EU

The sudden outbreak of COVID-19 put governments under pressure toswiftly introduce measures to protect citizens and react appropriately to theemerging threat. This paper focuses on geo-location tracking mobile phoneapplications developed in the Czech Republic and Austria to monitorpersonal movement of those positively tested for COVID-19 to prevent thefurther spread of the disease. The aim of the analysis is to answer thequestion of whether the appsʼ functionalities complied with the EU dataprotection standards and to what extent the citizensʼ right to control thecollection, evaluation and preservation of their personal data has beenviolated. Both countries belonged to the pioneers in COVID-19 apps. Whilethey differed in several areas such as the legal and political circumstancesunder which the apps were developed and public communication,similarities between them were identified in the area of public trust in theapps and their utilisation. In both countries, certain illiberal issues wererecognised as well.

A Theoretical Analysis of Mobility Detection in Connectivity-Based Localization for Short-Range Networks

This paper presents a theoretical analysis of mobility detection in connectivity-based localization, which exploits connectivity information as range measurements to anchors at a known location, to investigate how well and how precise mobility can be detected with connectivity in short-range networks. We derive mobility detection, miss detection, and false alarm probabilities in terms of a mobility detection threshold, defined as the minimum distance to detect the mobility, under the shadow fading channel and arbitrary mobility models to take into account practical and general scenarios. Based on the derivations, we address the threshold determination with the criteria in the sense of the minimum average error from miss detection and false alarm. Numerical and simulation evaluations are performed to verify our theoretical derivations, to show that increasing anchor numbers can improve the mobility detection probability with a smaller detection threshold, and that the probabilities are bounded by the weights of miss detection and false alarm. This work is the first attempt at addressing the performance of mobility detection using connectivity, and it can be utilized as a baseline for connectivity-based mobility tracking.

Young Adults View Smartphone Tracking Technologies for COVID-19 as Acceptable: The Case of Taiwan.

Taiwan has been successful in controlling the spread of SARS-CoV-2 during the COVID-19 pandemic; however, without a vaccine the threat of a second outbreak remains. Young adults who show few to no symptoms when infected have been identified in many countries as driving the virus’ spread through unidentifiable community transmission. Mobile tracking technologies register nearby contacts of a user and notifies them if one later tests positive to the virus, potentially solving this issue; however, the effectiveness of these technologies depends on their acceptance by the public. The current study assessed attitudes towards three tracking technologies (telecommunication network tracking, a government app, and Apple and Google’s Bluetooth exposure notification system) among four samples of young Taiwanese adults (aged 25 years or younger). Using Bayesian methods, we find high acceptance for all three tracking technologies (>75%), with acceptance for each technology surpassing 90% if additional privacy measures were included. We consider the policy implications of these results for Taiwan and similar cultures.

The acceptability and uptake of smartphone tracking for COVID-19 in Australia.

In response to the COVID-19 pandemic, many Governments are instituting mobile tracking technologies to perform rapid contact tracing. However, these technologies are only effective if the public is willing to use them, implying that their perceived public health benefits must outweigh personal concerns over privacy and security. The Australian federal government recently launched the 'COVIDSafe' app, designed to anonymously register nearby contacts. If a contact later identifies as infected with COVID-19, health department officials can rapidly followup with their registered contacts to stop the virus' spread. The current study assessed attitudes towards three tracking technologies (telecommunication network tracking, a government app, and Apple and Google's Bluetooth exposure notification system) in two representative samples of the Australian public prior to the launch of COVIDSafe. We compared these attitudes to usage of the COVIDSafe app after its launch in a further two representative samples of the Australian public. Using Bayesian methods, we find widespread acceptance for all tracking technologies, however, observe a large intention-behaviour gap between people's stated attitudes and actual uptake of the COVIDSafe app. We consider the policy implications of these results for Australia and the world at large.

Research on the Method and Application of MapReduce in Mobile Track Big Data Mining

Background: Mass movement trajectory data with real scenarios has been evolved with big data mining to solve the data redundancy problem. Methods: This paper proposes a parallel path based on the Map Reduce compression method, using two kinds of piecewise point mutual crisscross, the classified method of trajectory, and then segment trajectory distribution to multiple nodes to parallelize the compression. Results: Finally, the results based on both compression methods have been simulated for the different real-time data by merging both techniques. Conclusion: The performance test results show that the parallel trajectory compression method proposed in this paper can greatly improve the compression efficiency and completely eliminate the error caused by the failure of the correlation between the segments.

Tracking and promoting the usage of a COVID-19 contact tracing app.

Digital contact tracing apps have been introduced globally as an instrument to contain the COVID-19 pandemic. Yet, privacy by design impedes both the evaluation of these tools and the deployment of evidence-based interventions to stimulate uptake. We combine an online panel survey with mobile tracking data to measure the actual usage of Germany's official contact tracing app and reveal higher uptake rates among respondents with an increased risk of severe illness, but lower rates among those with a heightened risk of exposure to COVID-19. Using a randomized intervention, we show that informative and motivational video messages have very limited effect on uptake. However, findings from a second intervention suggest that even small monetary incentives can strongly increase uptake and help make digital contact tracing a more effective tool.