40 research outputs found
Performance evaluation of indoor localization techniques based on RF power measurements from active or passive devices
The performance of networks for indoor localization based on RF power measurements from active or passive devices is evaluated in terms of the accuracy, complexity, and costs. In the active device case, the terminal to be located measures the power transmitted by some devices inside its coverage area. To determine the terminal position in the area, power measurements are then compared with the data stored in an RF map of the area. A network architecture for localization based on passive devices is presented. Its operations are based on the measure of the power retransmitted from local devices interrogated by the terminal and on their identities. Performance of the two schemes is compared in terms of the probability of localization error as a function of the number (density) of active or passive devices. Analysis is carried out through simulation in a typical office-like environment whose propagation characteristics have been characterized experimentally. Considerations obtained in this work can be easily adapted to other scenarios. The procedure used for the analysis is general and can be easily extended to other situations
Unbundling in optical access networks: Focus on hybrid fiber-VDSL and TWDM-PON2014 Fotonica AEIT Italian Conference on Photonics Technologies
Analysing and Visualizing Tweets for U.S. President Popularity
In our society we are continually invested by a stream of information (opinions, preferences, comments, etc.). This shows how Twitter users react to news or events that they attend or take part in real time and with interest. In this context it becomes essential to have the appropriate tools in order to be able to analyze and extract data and information hidden in their large number of tweets. Social networks are a source of information with no rivals in terms of amount and variety of information that can be extracted from them. We propose an approach to analyze, with the help of automated tools, comments and opinions taken from social media in a real time environment. We developed a software system in R based on the Bayesian approach for text categorization. We aim of identifying sentiments expressed by the tweets posted on the Twitter social platform. The analysis of sentiment spread on social networks allows to identify the free thoughts, expressed authentically. In particular, we analyze the sentiments related to U.S President popularity by also visualizing tweets on a map. This allows to make an additional analysis of the real time reactions of people by associating the reaction of the single person who posted the tweet to his real time position in Unites States. In particular, we provide a visualization based on the geographical analysis of the sentiments of the users who posted the tweets
A joint Computer Vision and Reconfigurable Intelligent Meta-surface Approach for Interference Reduction in Beyond 5G Networks
International audienceReconfigurable Intelligent Meta-surfaces (RIMs) are particular devices able to control and manipulate radio frequency wireless signals. This promising technology allows to improve the reliability of wireless networks, thanks to the capacity of reflecting the desired signals through appropriate phase shifts. The joint use of RIMs and Computer Vision (CV) technology is the main objective of this paper. This synergistic approach is used to correctly identify the specific configuration of a radiation pattern, to be used as input for computing optimal coding sequences of the RIM. Indeed, by the means of a CV algorithm it is possible to infer a connectivity graph related to a real scenario, where people is moving. The information about network nodes such as their distance, the relative position, etc. is used for feeding an intelligent logic, able to compute the optimal configuration for redirecting the signals towards a given receiver target node. Numerical results show the huge potentiality of this combined approach in terms of interference reduction. It has been observed that for high traffic load, it is possible to reduce the average interference in the network of 40%. Furthermore, an analysis including the positioning estimation error of the CV algorithm has been addressed, in order to consider how it affects the interference reduction. Results show that, even though there is an increasing effect of interference, when the error is accounted, the interference reduction impact is still important
Analysing and Visualizing Tweets for U.S. President Popularity
In our society we are continually invested by a stream of information (opinions, preferences, comments, etc.). This shows how Twitter users react to news or events that they attend or take part in real time and with interest. In this context it becomes essential to have the appropriate tools in order to be able to analyze and extract data and information hidden in their large number of tweets. Social networks are a source of information with no rivals in terms of amount and variety of information that can be extracted from them. We propose an approach to analyze, with the help of automated tools, comments and opinions taken from social media in a real time environment. We developed a software system in R based on the Bayesian approach for text categorization. We aim of identifying sentiments expressed by the tweets posted on the Twitter social platform. The analysis of sentiment spread on social networks allows to identify the free thoughts, expressed authentically. In particular, we analyze the sentiments related to U.S President popularity by also visualizing tweets on a map. This allows to make an additional analysis of the real time reactions of people by associating the reaction of the single person who posted the tweet to his real time position in Unites States. In particular, we provide a visualization based on the geographical analysis of the sentiments of the users who posted the tweets
Indoor Localization System Based on Bluetooth Low Energy for Museum Applications
In the last few years, indoor localization has attracted researchers and commercial developers. Indeed, the availability of systems, techniques and algorithms for localization allows the improvement of existing communication applications and services by adding position information. Some examples can be found in the managing of people and/or robots for internal logistics in very large warehouses (e.g., Amazon warehouses, etc.). In this paper, we study and develop a system allowing the accurate indoor localization of people visiting a museum or any other cultural institution. We assume visitors are equipped with a Bluetooth Low Energy (BLE) device (commonly found in modern smartphones or in a small chipset), periodically transmitting packets, which are received by geolocalized BLE receivers inside the museum area. Collected packets are provided to the locator server to estimate the positions of the visitors inside the museum. The position estimation is based on a feed-forward neural network trained by a measurement campaign in the considered environment and on a non-linear least square algorithm. We also provide a strategy for deploying the BLE receivers in a given area. The performance results obtained from measurements show an achievable position estimate accuracy below 1 m
Unbundling in Current Broadband and Next-Generation Ultra-Broadband Access Networks
This article overviews the methods that are currently under investigation for implementing multi-operator open-access/shared-access techniques in next-generation access ultra-broadband architectures, starting from the traditional "unbundling-of-the-local-loop" techniques implemented in legacy twisted-pair digital subscriber line access networks. A straightforward replication of these copper-based unbundling-of-the-local-loop techniques is usually not feasible on next-generation access networks, including fiber-to-the-home point-to-multipoint passive optical networks. To investigate this issue, the article first gives a concise description of traditional copper-based unbundling-of-the-local-loop solutions, then focalizes on both next-generation access hybrid fiber-copper digital subscriber line fiber-to-the-cabinet scenarios and on fiber to the home by accounting for the mix of regulatory and technological reasons driving the next-generation access migration path, focusing mostly on the European situation. © 2014 Taylor and Francis Group, LLC