Development of a Technology for Automation of Work with Sources of Information on the Internet

The article describes the technology for automation of work with sources of information on the Internet. The created technology includes a development of a web service for storing and processing data; creation of a client part for viewing, editing and deleting records from the service; development of a browser extension for instant addition of articles to a web service database. Addition of records to the service is implemented by the development of an extension to Google Chrome browser. Creation of an extension involves getting information about the author of the article, the title of the article, addresses, key expressions, and highlighted text. Regular expressions and recursive search are used to obtain information about the author of the text. The article offers algorithms for finding the name of a literary source and its author. In order to allow the web service to interact with other services or programs, a REST service was developed in the article. A graphical user interface to display and edit records was developed for the web service using the AngularJS JavaScript framework. For the client part, a mechanism of an on request citations search and a mechanism of reference list formation for the selected citations is proposed. For the on request citations search, the article suggests the algorithm of citations ranking. Appropriate plugins for Google Chrome have been developed, which allow to connect content levels, background, and pop-up with each other. Functions for authorization, receiving a token, information search launch, search for an author, and a bibliographic record creation have been created.

A Fisheye Image Matching Method Boosted by Recursive Search Space for Close Range Photogrammetry

Close range photogrammetry (CRP) with large field-of-view images has become widespread in recent years, especially in terrestrial mobile mapping systems (TMMS). However, feature-based matching (FBM) with omnidirectional images (e.g., fisheye) is challenging even for state-of-the-art methods, such as the scale-invariant feature transform (SIFT), because of the strong scale change from image to image. This paper proposes an approach to boost FBM techniques on fisheye images with recursive reduction of the search space based on epipolar geometry. The epipolar restriction is calculated with the equidistant mathematical model and the initial exterior orientation parameters (EOPs) determined with navigation sensors from TMMS. The proposed method was assessed with data sets acquired by a low-cost TMMS. The TMMS is composed of a calibrated poly-dioptric system (Ricoh Theta S) and navigation sensors aimed at outdoor applications. The assessments show that Ricoh Theta S position and attitude were estimated in a global bundle adjustment with a precision (standard deviation) of 4 cm and 0.3°, respectively, using as observations the detected matches from the proposed method. Compared with other methods based on SIFT extended to the omnidirectional geometry, our approach achieved compatible results for outdoor applications.

Computation of Traffic Time Series for Large Populations of IoT Devices

The Internet of Things (IoT) contains sets of hundreds of thousands of network-enabled devices communicating with central controlling nodes or information collectors. The correct behaviour of these devices can be monitored by inspecting the traffic that they create. This passive monitoring methodology allows the detection of device failures or security breaches. However, the creation of hundreds of thousands of traffic time series in real time is not achievable without highly optimised algorithms. We herein compare three algorithms for time-series extraction from traffic captured in real time. We demonstrate how a single-core central processing unit (CPU) can extract more than three bidirectional traffic time series for each one of more than 20,000 IoT devices in real time using the algorithm DStries with recursive search. This proposal also enables the fast reconfiguration of the analysis computer when new IoT devices are added to the network.