Smart Antennas and Intelligent Sensors Based Systems: Enabling Technologies and Applications

open access articleThe growing communication and computing capabilities in the devices enlarge the connected world and improve the human life comfort level. The evolution of intelligent sensor networks and smart antennas has led to the development of smart devices and systems for real-time monitoring of various environments. The demand of smart antennas and intelligent sensors significantly increases when dealing with multiuser communication system that needs to be adaptive, especially in unknown adverse environment [1–3]. The smart antennas based arrays are capable of steering the main beam in any desired direction while placing nulls in the unwanted directions. Intelligent sensor networks integration with smart antennas will provide algorithms and interesting application to collect various data of environment to make intelligent decisions [4, 5]. The aim of this special issue is to provide an inclusive vision on the current research in the area of intelligent sensors and smart antenna based systems for enabling various applications and technologies. We cordially invite some researchers to contribute papers that discuss the issues arising in intelligent sensors and smart antenna based system. Hence, this special issue offers the state-of-the-art research in this field

QoS and QoE Aware N-Screen Multicast Service

The paper focuses on ensuring the quality-of-service (QoS) and quality-of-experience (QoE) requirements of users having heterogeneous devices in a multicast session. QoS parameters such as bit rate, delays, and packet losses are good indicators for optimizing network services but fall short in characterizing user perception (QoE). In N-Screen service, the users have different devices with heterogeneous attributes like screen size, resolution, and access network interface, and the users have different QoE on N-Screen devices with the same QoS parameters. We formulate the objective function of the N-Screen multicast grouping to ensure the minimum user’s QoE with smaller bandwidth requirement. We propose a dynamic user reassignment scheme to maintain and satisfy the QoE by adapting the user’s membership to the varying network conditions. The proposed schemes combine the available bandwidth and multimedia visual quality to ensure the QoS and QoE. In the network architecture, we introduce the functions of the QoS and QoE aware multicast group management and the estimation schemes for the QoS and QoE parameters. The simulation results show that the proposed multicast service ensures the network QoS and guarantees the QoE of users in the varying network conditions

N-Screen Aware Multicriteria Hybrid Recommender System Using Weight Based Subspace Clustering

This paper presents a recommender system for N-screen services in which users have multiple devices with different capabilities. In N-screen services, a user can use various devices in different locations and time and can change a device while the service is running. N-screen aware recommendation seeks to improve the user experience with recommended content by considering the user N-screen device attributes such as screen resolution, media codec, remaining battery time, and access network and the user temporal usage pattern information that are not considered in existing recommender systems. For N-screen aware recommendation support, this work introduces a user device profile collaboration agent, manager, and N-screen control server to acquire and manage the user N-screen devices profile. Furthermore, a multicriteria hybrid framework is suggested that incorporates the N-screen devices information with user preferences and demographics. In addition, we propose an individual feature and subspace weight based clustering (IFSWC) to assign different weights to each subspace and each feature within a subspace in the hybrid framework. The proposed system improves the accuracy, precision, scalability, sparsity, and cold start issues. The simulation results demonstrate the effectiveness and prove the aforementioned statements

Control framework and services scenarios of provisioning N-Screen services in interactive digital signage

U ovom radu predstavljamo upravljački sustav i scenarije za osiguranje N-Screen usluga u interaktivnom digitalnom znakovlju. Digitalno znakovlje osigurava niz displeja s obavijestima i sadržajem visoke rezolucije na različitim javnim mjestima i događajima. Osiguranje N-Screen usluga u interaktivnom digitalnom znakovlju omogućuje pružatelju usluge osiguranje sadržaja raznovrsnim uređajima, omogućuje krajnjem korisniku slanje sadržaja digitalnog znakovlja do N-Screen uređaja korisnika i obratno, na različitim lokacijama i u različito vrijeme. Pružamo N-Screen usluge u interaktivnom digitalnom znakovlju prilagođavajući sadržaj korisničkom sučelju u skladu s dimenzijom, rasporedom, adaptacijom lokaliziranog sadržaja, sinhronizacijom i trajanjem poruke u različitim uređajima korisnikovog N-Screen uređaja. Predstavljamo N-Screen User Interface Management Server (NUIMS), Digital Signage Management Server (DSMS), i Localized Content and Session Management Agent (LCSMA) kao podršku N-Screen uslugama. Nadalje, N-Screen Devices Repository (NDR) u DSMS-u osigurava da statički profil N-Screen uređaja korisnika raspoređuje sadržaj na sve njihove uređaje, a LCSMA omogućuje da dinamički profil sinhronizira sadržaj na različitim uređajima. Uz to, predlažemo postupke, protokole i scenarije usluga u svrhu slanja sadržaja digitalnog znakovlja do N-Screen uređaja korisnika, metode kontinuiranog sinhroniziranja sadržaja displeja kroz displeje različitog znakovlja i dijeljenja s drugim korisnicima uz upotrebu informacijskog servera korisnika.In this article, we present the control framework and services scenarios of provisioning N-Screen services in interactive digital signage. Digital Signage provides a variety of high-resolution content and information displays at different public places and events. Provisioning N-Screen services in interactive digital signage enables the service providers to provide content to heterogeneous devices, allows the end user to share content from the digital signage to the user N-Screen devices and vice versa at different locations and times. We provide N-Screen services in interactive digital signage by adapting the content user interface according to user\u27s N-Screen device size, layout, localized content adaptation, synchronization and session continuity over heterogeneous devices. We introduce the N-Screen User Interface Management Server (NUIMS), Digital Signage Management Server (DSMS), and Localized Content and Session Management Agent (LCSMA) to support N-Screen services. Furthermore, the N-Screen Devices Repository (NDR) at the DSMS keeps the users N-Screen devices static profile in order to share the content across all of their devices, and the LCSMA maintains the dynamic profile to synchronize content on heterogeneous devices. In addition, we suggest procedures, protocols and service scenarios to share the content of the digital signage to user’s N-Screen devices, methods to synchronize the content display over heterogeneous signage displays with content session continuity and to share with other users using the user information server

A New Coverage Flight Path Planning Algorithm Based on Footprint Sweep Fitting for Unmanned Aerial Vehicle Navigation in Urban Environments

This paper presents a new coverage flight path planning algorithm that finds collision-free, minimum length and flyable paths for unmanned aerial vehicle (UAV) navigation in three-dimensional (3D) urban environments with fixed obstacles for coverage missions. The proposed algorithm significantly reduces computational time, number of turns, and path overlapping while finding a path that passes over all reachable points of an area or volume of interest by using sensor footprints’ sweeps fitting and a sparse waypoint graph in the pathfinding process. We devise a novel footprints’ sweep fitting method considering UAV sensor footprint as coverage unit in the free spaces to achieve maximal coverage with fewer and longer footprints’ sweeps. After footprints’ sweeps fitting, the proposed algorithm determines the visiting sequence of footprints’ sweeps by formulating it as travelling salesman problem (TSP), and ant colony optimization (ACO) algorithm is employed to solve the TSP. Furthermore, we generate a sparse waypoint graph by connecting footprints’ sweeps’ endpoints to obtain a complete coverage flight path. The simulation results obtained from various scenarios fortify the effectiveness of the proposed algorithm and verify the aforementioned claims

Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective

With the advent of the pandemic (e.g., novel corona virus disease 2019 (COVID-19)), a tremendous amount of data about individuals are collected by the health authorities on daily basis for curbing the disease’s spread. The individuals’ data collection/processing at a massive scale for community well-being with the help of digital solutions (e.g., mobile apps for mobility and proximity analysis, contact tracing through credit card usage history, facial recognition through cameras, and crowd analysis using cellular networks data etc.) raise several privacy concerns. Furthermore, the privacy concerns that are arising mainly due to the fine-grained data collection has hindered the response to tackle this pandemic in many countries. Hence, acquiring/handling individuals data with privacy protection has become a vibrant area of research in these pandemic times. This paper explains the shift in privacy paradigm due to the pandemic (e.g., COVID-19) which involves more and detailed data collection about individuals including locations and demographics. We explain technical factors due to which the people’s privacy is at higher risk in the COVID-19 time. In addition, we discuss privacy concerns in different epidemic control measures (ECMs) (e.g., contact tracing, quarantine monitoring, and symptoms reporting etc.) employed by the health authorities to tackle this disease. Further, we provide an insight on the data management in the ECMs with privacy protection. Finally, the future prospects of the research in this area tacking into account the emerging technologies are discussed. Through this brief article, we aim to provide insights about the vulnerability to user’s privacy in pandemic times, likely privacy issues in different ECMs adopted by most countries around the world, how to preserve user’s privacy effectively in all phases of the ECMs considering relevant data in loop, and conceptual foundations of ECMs to fight with future pandemics in a privacy preserving manner

Enhancement of Text Analysis Using Context-Aware Normalization of Social Media Informal Text

We proposed an application and data variations-independent, generic social media Textual Variations Handler (TVH) to deal with a wide range of noise in textual data generated in various social media (SM) applications for enhanced text analysis. The aim is to build an effective hybrid normalization technique that ensures the use of useful information of the noisy text in its intended form instead of filtering them out to analyze SM text better. The proposed TVH performs context-aware text normalization based on intended meaning to avoid the wrong word substitution. We integrate the TVH with state-of-the-art (SOTA) deep-learning-based text analysis methods to enhance their performance for noisy SM text data. The proposed scheme shows promising improvement in the text analysis of informal SM text in terms of precision, recall, accuracy, and F1-score in simulation

A Fast Global Flight Path Planning Algorithm Based on Space Circumscription and Sparse Visibility Graph for Unmanned Aerial Vehicle

This paper proposes a new flight path planning algorithm that finds collision-free, optimal/near-optimal and flyable paths for unmanned aerial vehicles (UAVs) in three-dimensional (3D) environments with fixed obstacles. The proposed algorithm significantly reduces pathfinding computing time without significantly degrading path lengths by using space circumscription and a sparse visibility graph in the pathfinding process. We devise a novel method by exploiting the information about obstacle geometry to circumscribe the search space in the form of a half cylinder from which a working path for UAV can be computed without sacrificing the guarantees on near-optimality and speed. Furthermore, we generate a sparse visibility graph from the circumscribed space and find the initial path, which is subsequently optimized. The proposed algorithm effectively resolves the efficiency and optimality trade-off by searching the path only from the high priority circumscribed space of a map. The simulation results obtained from various maps, and comparison with the existing methods show the effectiveness of the proposed algorithm and verify the aforementioned claims

Correction: Majeed, A.; Lee, S. Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective. <i>Inventions</i> 2021, <i>6</i>, 24

The authors made a mistake while publishing this paper [...

Social Content Recommendation Based on Spatial-Temporal Aware Diffusion Modeling in Social Networks

User interactions in online social networks (OSNs) enable the spread of information and enhance the information dissemination process, but at the same time they exacerbate the information overload problem. In this paper, we propose a social content recommendation method based on spatial-temporal aware controlled information diffusion modeling in OSNs. Users interact more frequently when they are close to each other geographically, have similar behaviors, and fall into similar demographic categories. Considering these facts, we propose multicriteria-based social ties relationship and temporal-aware probabilistic information diffusion modeling for controlled information spread maximization in OSNs. The proposed social ties relationship modeling takes into account user spatial information, content trust, opinion similarity, and demographics. We suggest a ranking algorithm that considers the user ties strength with friends and friends-of-friends to rank users in OSNs and select highly influential injection nodes. These nodes are able to improve social content recommendations, minimize information diffusion time, and maximize information spread. Furthermore, the proposed temporal-aware probabilistic diffusion process categorizes the nodes and diffuses the recommended content to only those users who are highly influential and can enhance information dissemination. The experimental results show the effectiveness of the proposed scheme