Related papers: Spatio-Temporal Data Correlation with Adaptive Str…
Time series forecasting is essential for our daily activities and precise modeling of the complex correlations and shared patterns among multiple time series is essential for improving forecasting performance. Spatial-Temporal Graph Neural…
In this paper, we consider an intrusion detection application for Wireless Sensor Networks (WSNs). We study the problem of scheduling the sleep times of the individual sensors to maximize the network lifetime while keeping the tracking…
In this paper, based on the spatio-temporal correlation of sensor nodes in the Internet of Things (IoT), a Spatio-temporal Scope information model (SSIM) is proposed to quantify the scope valuable information of sensor data, which decays…
Due to the limited energy of sensor nodes in wireless sensor networks, extending the networks lifetime is a major challenge that can be formulated as an optimization problem. In this paper, we propose a distributed iterative algorithm based…
This paper proposes a novel time synchronization protocol inspired by the adaptive Newton search algorithm. The clock model of nodes are modeled as an adaptive filter and a pairwise steady state and convergence analyses are presented. A…
We propose a linear time-difference-of-arrival (TDOA) measurement model to improve \textit{distributed} estimation performance for localized target tracking. We design distributed filters over sparse (possibly large-scale) communication…
A wireless sensor network often relies on a fusion center to process the data collected by each of its sensing nodes. Such an approach relies on the continuous transmission of raw data to the fusion center, which typically has a major…
Active sensing refers to the process of choosing or tuning a set of sensors in order to track an underlying system in an efficient and accurate way. In a wireless environment, among the several kinds of features extracted by traditional…
Objective-The main purpose of this paper is to construct a data accuracy model for the maximal set of sensor nodes that sense a point event and forms a cluster with fully connected network between them. We determine the minimal set of…
A distributed spatio-temporal information based cooperative positioning (STICP) algorithm is proposed for wireless networks that require three-dimensional (3D) coordinates and operate in the global navigation satellite system (GNSS) denied…
We propose a distributed algorithm for time synchronization in mobile wireless sensor networks. Each node can employ the algorithm to estimate the global time based on its local clock time. The problem of time synchronization is formulated…
Predicting individual mobility patterns is crucial across various applications. While current methods mainly focus on predicting the next location for personalized services like recommendations, they often fall short in supporting broader…
Spatio-temporal prediction is a pivotal task with broad applications in traffic management, climate monitoring, energy scheduling, etc. However, existing methodologies often struggle to balance model expressiveness and computational…
We study real time periodic query scheduling for data collection in multihop Wireless Sensor Networks (WSNs). Given a set of heterogenous data collection queries in WSNs, each query requires the data from the source sensor nodes to be…
A significantly low cost and tractable progressive learning approach is proposed and discussed for efficient spatiotemporal monitoring of a completely unknown, two dimensional correlated signal distribution in localized wireless sensor…
To meet the demands of wireless sensor networks (WSNs) where data are usually aggregated at a single source prior to transmitting to any distant user, there is a need to establish a tree structure inside to aggregate data. In this paper, an…
Fine-grained air pollution forecasting is crucial for urban management and the development of healthy buildings. Deploying portable sensors on mobile platforms such as cars and buses offers a low-cost, easy-to-maintain, and wide-coverage…
Wireless Sensor networks are dense networks of small, low-cost sensors, which collect and disseminate environmental data and thus facilitate monitoring and controlling of physical environment from remote locations with better accuracy. The…
Energy consumption is the most important factor that determines sensor node lifetime. The optimization of wireless sensor network lifetime targets not only the reduction of energy consumption of a single sensor node but also the extension…
Trajectory prediction (TP) is crucial for ensuring safety and efficiency in modern air traffic management systems. It is, for example, a core component of conflict detection and resolution tools, arrival sequencing algorithms, capacity…