Related papers: Efficient Sensor Scheduling Strategy Based on Spat…
Sparse sensor placement is a central challenge in the efficient characterization of complex systems when the cost of acquiring and processing data is high. Leading sparse sensing methods typically exploit either spatial or temporal…
Fitting statistical models to spatiotemporal data requires finding the right balance between imposing smoothness and following the data. In the context of p-splines, we propose a Bayesian framework for choosing the smoothing parameter which…
The evolution of Internet of Things technologies is driven by four key demands: ultra-low power consumption, high spectral efficiency, reduced implementation cost, and support for massive connectivity. To address these challenges, this…
The Internet of Things (IoT) has important applications in our daily lives including health and fitness tracking, environmental monitoring and transportation. However, sensor nodes in IoT suffer from the limited lifetime of batteries…
In this paper we simulate an ensemble of cooperating, mobile sensing agents that implement the cyclic stochastic optimization (CSO) algorithm in an attempt to survey and track multiple targets. In the CSO algorithm proposed, each agent uses…
The new wave of computing allows users to explore their time in the Internet of Things (IoT) by connecting their smart devices over the network for data transfer without human interventions. While this swing increases the pace in IoT, time…
We propose a space-time reduced-order model (ROM) for nonlinear dynamical systems, building upon previous work on linear systems. Whereas most ROMs are space-only in that they reduce only the spatial dimension of the state, the proposed…
Internet of Things (IoT) devices often come with batteries of limited capacity that are not easily replaceable or rechargeable, and that constrain significantly the sensing, computing, and communication tasks that they can perform. The…
Edge computing has emerged as a prospective paradigm to meet ever-increasing computation demands in Mobile Target Tracking Wireless Sensor Networks (MTT-WSN). This paradigm can offload time-sensitive tasks to sink nodes to improve computing…
The Intelligent Transportation System (ITS) targets to a coordinated traffic system by applying the advanced wireless communication technologies for road traffic scheduling. Towards an accurate road traffic control, the short-term traffic…
The increasing maturity of big data applications has led to a proliferation of models targeting the same objectives within the same scenarios and datasets. However, selecting the most suitable model that considers model's features while…
Complex multi-robot missions often require heterogeneous teams to jointly optimize task allocation, scheduling, and path planning to improve team performance under strict constraints. We formalize these complexities into a new class of…
This paper characterizes and jointly optimizes Age of Information (AoI) and energy efficiency in heterogeneous correlated random access networks, where each sensor adopts a distinct transmission probability and its observations are…
Reconfigurable intelligent surface (RIS) enhances signal quality by adjusting the phase of electromagnetic waves in wireless communication. Spatial modulation (SM), a prominent index modulation (IM) technique, provides high spectral…
In the future, sensor nodes or Internet of Things (IoTs) will be tasked with sampling the environment. These nodes/devices are likely to be powered by a Hybrid Access Point (HAP) wirelessly, and may be programmed by the HAP with a {\em…
The rapid development of Wi-Fi technologies in recent years has caused a significant increase in the traffic usage. Hence, knowledge obtained from Wi-Fi network measurements can be helpful for a more efficient network management. In this…
We present a set of metrics intended to supplement designer intuitions when designing swarm-robotic systems, increase accuracy in extrapolating swarm behavior from algorithmic descriptions and small test experiments, and lead to faster and…
Sensors are an integral part of modern Internet of Things (IoT) applications. There is a critical need for the analysis of heterogeneous multivariate temporal data obtained from the individual sensors of these systems. In this paper we…
Spatial-temporal prediction is a fundamental problem for constructing smart city, which is useful for tasks such as traffic control, taxi dispatching, and environmental policy making. Due to data collection mechanism, it is common to see…
With the increasing emphasis on machine learning and artificial intelligence to drive knowledge discovery in the agricultural sciences, spatial internet of things (IoT) technologies have become increasingly important for collecting…