The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In order to achieve maximum efficiency and benefit through adjusting the places of business-related items, and dig out the frequent infested area that the customers appear and the goods they often purchased in the supermarket, We developed an interactive track tagging system. After gaining the target height information through the multi-camera, we can track the customers and label its trajectory....
This paper calibrates an interrupted traffic flow system model using the trajectory datasets provided by Next Generation SIMulation (NGSIM) program. The realistic lane changing may cut off the traffic flow into discontinuous flow, giving rise to congestion and vehicle delay. The aim of this paper is to study the car-following behaviors of drivers in real traffic scenes in which lane changing happens...
Recent research efforts in data stream management systems (DSMS) focus mainly on processing continuous queries over traditional data streams, and only a few addressed spatio-temporal continuous queries. OCEANUS presents an effort to extend TelegraphCQ DSMS with spatial support providing a platform for spatio-temporal streaming applications. Data type system that represents the formal basis for modeling...
Most of the recent research on Object Tracking Sensor Networks has focused on collecting all data from the entire sensor network and placing it into the sink, which delivers the predicted locations to the corresponding nodes in order to predict an object's movement. This collection method affects the freshness of the data and creates latency in predicting movement patterns. In addition, due to the...
Flickr represents a massive opportunity to mine valuable human movement data from geo-tagged photos. However, existing Flickr trajectory data mining research has not considered mining frequent trajectory patterns whilst also considering the temporal domain. Therefore, a significant opportunity exists to demonstrate the application of a pattern mining algorithm to a large geo-tagged photo dataset....
The increasing availability of large-scale vehicle traffic data provides us great opportunity to explore them for knowledge discovery in intelligent transportation systems. Many mechanisms have been proposed to discover all outliers in a road network lately due to an increasing capability to track moving vehicles. In this paper, we propose a new problem called the road segment-based outliers detection...
Urban spatial structure has long been studied by geographers and economists to understand the development of cities using the activities extracted from surveys. With the popularity of mobile devices, massive urban sensing data has brought the opportunities to study human activities and city dynamics. Location based service has enormous growth in the recent years. Such abundant information benefits...
Location-based services allow users to perform geo-spatial recording actions, which facilitates the mining of the moving activities of human beings. This paper proposes to recommend time-sensitive trip routes, consisting of a sequence of locations with associated time stamps, based on knowledge extracted from large-scale time-stamped location sequence data (e.g. check-ins and GPS traces). We argue...
Spatiotemporal clustering is a process of grouping a set of objects based on their spatial and temporal similarities. In this paper we propose two new spatiotemporal clustering algorithms, called Spatiotemporal Shared Nearest Neighbor clustering algorithm (ST-SNN), and Spatiotemporal Separated Shared Nearest Neighbor clustering algorithm (ST-SEP-SNN), to cluster overlapping polygons that can change...
The increasing pervasiveness of mobile devices along with the use of technologies like GPS, Wifi networks, RFID, etc., allows for the collections of large amounts of movement data. This amount of information can be analyzed to extract descriptive and predictive models that can be profitable exploited to improve urban life. This paper presents an integrated Cloud based framework for efficiently managing...
Inverse Reinforcement Learning (IRL) is an approach for domain-reward discovery from demonstration, where an agent mines the reward function of a Markov decision process by observing an expert acting in the domain. In the standard setting, it is assumed that the expert acts (nearly) optimally, and a large number of trajectories, i.e., training examples are available for reward discovery (and consequently,...
Uncertainty is common in real-world applications, for example, in sensor networks and moving object tracking, resulting in much interest in item set mining for uncertain transaction databases. In this paper, we focus on pattern mining for uncertain sequences and introduce probabilistic frequent spatial-temporal sequential patterns with gap constraints. Such patterns are important for the discovery...
Movement data have been widely collected from GPS and sensors, allowing us to analyze how moving objects interact in terms of space and time and to learn about the relationships that exist among the objects. In this paper, we investigate an interesting relationship that has not been adequately studied so far: the following relationship. Intuitively, a follower has similar trajectories as its leader...
Energy producers are facing a challenging task in trying to monitor the energy conversion processes due to their complexity, nonlinear dynamics, and a large number of affecting factors. There are several methods available which can deal with multidimensionality and which could be used in industrial monitoring systems, but it seems that the methods used by the industry are not necessarily fully compatible...
The recently emerged field of game analytics and the development and adaptation of business intelligence techniques to support game design and development has given data-driven techniques a direct role in game development. Given that all digital games contain some sort of spatial operation, techniques for spatial analysis had their share in these developments. However, the methods for analyzing and...
In most recent Intelligent Video Surveillance systems, mechanisms used to support human decisions are integrated in cognitive artificial processes. Large scale video surveillance networks must be able to analyse a huge amount of information. In this context, a cognitive perception mechanism integrate in an intelligent system could help an operator for focusing his attention on relevant aspects of...
Visual sensors are usually set up to capture the environmental information and/or to monitor traffic road condition. The captured video is then transmitted to end-users for being further analyzed or stored. However, the video data amount and size is too large to store and transmit smoothly with high resolution under capacity and bandwidth limitation. Because consecutive frames have a large-scale overlapped...
As security requirements in coastal water and sea ports, maritime surveillance increases the duty. In this research, we focus on the maritime trajectory data to explore movement behavior for anomaly detection in maritime traffic. Trajectory data records the moving objects' true movement and provides the opportunity to discover the movement behavior for anomaly detection. The multidimensional outlying...
Nowadays, researchers tend to make use of GPS trajectories collected by companies, organizations, or volunteers. GPS trajectories on crowdsourcing websites are less widely used in researches but actually have great potential for various applications. Thus, this paper makes a comprehensive study on GPS trajectories on VGI websites and social websites. The volume, growth rate, and categories of the...
The availability of inexpensive tracking devices, such as GPS-enabled devices, gives the opportunity to collect large amounts of trajectory data from vehicles. In this context, we are interested in the problem of generating the traffic information in time-dependent networks using this kind of data. This problem is not trivial since several works in literature use strong assumptions on the error distribution...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.