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Fast access through retrieval and insertion of data is critical to spatial big data analytics applications. This access is however one of the bottlenecks in large-scale spatial data-centric applications. Distributed spatial indexing structures such as quadtrees have been proposed to help alleviate this bottleneck. Some of the proposed solutions use a static sample of the data to build a quadtree as...
Barrier coverage is a natural application of sensor networks in which sensors are deployed to detect intruders or protect crucial resources. In this paper, we consider a hybrid sensor network with a two-phase deployment, in which less-expensive static sensors are first randomly deployed in an area, and then more-expensive mobile sensors are deployed to fill coverage gaps. We use a probabilistic model...
Mobile crowd sensing (MCS) arises as an appealing paradigm, which utilizes participants to contribute sensing data generated from sensors embedded in smart devices in the internet of things (IoT) for the people-centric service delivery and crowd intelligence extraction. Due to the inherent selfishness of human and network's openness, the quality of the data submitted by the participants is not always...
Mobile Crowd Sensing (MCS) is a promising paradigm in which mobile users collect and share sensor data from their local environment using wireless mobile devices. The inherent openness of this platform and the selfishness of individuals make it easy to contribute low-quality sensor data, so the recruitment of suitable participants who are trustable and contribute high-quality sensor data, becomes...
This paper presents an approach for autonomous and reliable localization of fugitive methane emissions and quantification of source emission rates over large regions of interest. Previous methods have used single mobile unmanned ground vehicle (UGV) leak localization, but as a result cannot disambiguate multiple sources when plumes overlap. The novel method presented in this paper implements a mobile...
The paper is aimed at researching the subject area, models and prototypes of secure mobile communication mesh networks providing support and operational management in critical emergency situations. Such a network represents a command technical complex that provides services of text messages and media data transfer, database services, web services, etc. A two-layer network architecture using Arduino...
Advances in the Internet of Things (IoT) infrastructures are enabling the gathering, processing and inference of a wide array of data, enabling more agile decision management frameworks in several contexts, including vehicle routing and navigation. Coupled with crowd-sensing, these decision management frameworks gain further advantage in terms of data availability. This work concerns itself with safety...
The deployment of long term evolution (LTE) in unlicensed spectrum (LTE-U) is a promising solution to overcome the spectrum shortage. However, the interaction between LTE-U and Wi-Fi in unlicensed spectrum has not been well understood. In this paper, we use stochastic geometry to develop a framework for the co-existence between LTE-U and Wi-Fi in unlicensed spectrum. To reduce the intra-and inter-RAT...
People-centric sensing is a research topic that aims to obtain and analyze urban data from crowdsourcing, such as participatory and opportunistic sensing. Data provided by these sources increase our knowledge about different aspects of our lives in urban scenarios, which can help us to understand and address issues that cities face. Thus, the sustainable people participation is crucial to the development...
In wireless networks, the nodes are generally distributed in a field randomly. The topological information about the nodes is only supported from the distances between each node. This distance information may not be available due to the imperfect conditions among nodes. The positions of the distributed nodes on the field by using available distance data is called node localization problem. One of...
Continuous growing interest in IoT applications particularly for a smart city setting has attracted many researchers. E-health applications in IoT networks are the newest area of interest in this research field. On the other hand, networking and communications fields are witnessing a revolution through the new concepts of Mobile Edge Computing (MEC) characterised by latency sensitivity and geographical...
In wireless sensor networks, sensors typically aim to transmit their own readings to the sink node. Constructing an efficient data collection tree is very important since it can determine the lifetime of the given WSNs. In literature, may studies have investigated this issue and proposed algorithms for mobile sink to visit each sensor such that the readings of the sensors can be directly transmit...
Wireless rechargeable sensor networks are becoming crucial and important in recent years for the advancement of wireless energy transmission technology. The previous research shown that not all of sensors can be recharged due to the limitation of energy capacity that mobile chargers can carry. If a sensor playing a critical role in a sensing task cannot function as usual due to the exhausted energy,...
The rapid development of smart-phone technology in recent years has lead to many smart-phone owners owning out-of-date devices, equipped with useful technologies, which are no longer in use. These devices are valuable resources that can be harnessed to improve users' lives. This project aims at leveraging these older, unused devices to help improve road safety, specifically through the improved response...
This paper discusses the design and development efforts made to collect data using an opportunistic crowdsensing mobile application. Relevant issues are underlined, and solutions proposed within the CHIST-ERA Macaco project for the specifics of collecting fine-grained content and context data are highlighted. Global statistics on the data gathered for over a year of collection show its quality: Macaco...
The ability to detect gunshots can provide someone with invaluable information in various circumstances. For the military and public servants, detecting gunshots can help save lives and potentially target offenders. People participating in shooting sports as beginners or professionals can also benefit from the use of sensors for improving their reaction and self control during training. Most current...
In disaster situations or on emergency terrains, Internet and Cloud access may be restricted; it may still be important to process complex resource-intensive tasks and to acquire distributed information for emergency response, using ad-hoc networks among, e.g., first responder mobile devices. Corresponding approaches towards coordination, resource utilization, and interoperability are still challenging...
With the rise of smart mobile devices, context-aware mobile applications became an integral part of our everyday life. However, testing, evaluating or demonstrating context-aware mobile applications for outdoor environments remains a resource-intensive and cumbersome task. The investigations need to be conducted in real-world experiments in order to gain proper insights into how well an application...
Mobile Crowdsensing is a promising paradigm for ubiquitous sensing, which explores the tremendous data collected by mobile smart devices with prominent spatial-temporal coverage. As a fundamental property of Mobile Crowdsensing Systems, temporally recruited mobile users can provide agile, fine-grained, and economical sensing labors, however their self-interest cannot guarantee the quality of the sensing...
The surveillance for data collection in wireless sensor networks (WSNs) setting is recognized as an important application of WSNs. Given an area of interest and a number of wireless sensors, typical problems to be addressed are covering the whole area while prolonging the network lifetime. It is explicitly observed that most existing studies focus on limited case in which the interested area is static...
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