In this paper, the problem of indoor localization in wireless networks is addressed relying on a swarm-based approach. We assume to know the positions of a few number of sensor nodes, denoted as anchor nodes (ANs), and we aim at finding the position of a target node (TN) on the basis of the estimated distances between each AN and the considered TN. Since ultra wide band (UWB) technology is particularly suited for localization purposes (owing to its remarkable time resolution), we consider a network composed of UWB devices. More precisely, we carry out an experimental investigation using the PulsOn 410 ranging and communication modules (RCMs) produced by time domain. Using four of them as ANs and one of them as TN, various topologies are con...
Abstract This paper presents an ensemble learning particle swarm optimization (ELPSO) algorithm for ...
Localization in indoor environments is a hard task because of several constraints, both in terms of ...
This paper describes and compares two of the algorithms for indoor localization that are implemented...
In this paper, the problem of indoor localization in wireless networks is addressed relying on a swa...
In this paper, we focus on the application of Ultra Wide Band (UWB) technology to the problem of loc...
Abstract. In this paper, we focus on the application of Ultra Wide Band (UWB) technology to the prob...
In this dissertation, the localization of targets in indoor environment by means of the Ultra Wide B...
Wireless Sensor Networks (WSNs) consist of a collection of spatially distributed radio transceivers ...
In wireless sensor networks we often want to know where individual sensor nodesare physically positi...
We propose a low-complexity indoor localization scheme using a hybirid of particle swarm optimizatio...
In this paper we describe a method for localization of multiple persons using a distributed network ...
In this paper, we address the problem of localizing sensor nodes in a static network, given that the...
Interest in the Internet of Things (IoT) is rapidly increasing, as the number of connected devices i...
Position localization is becoming increasingly important in wireless communication networks. Ultra W...
Interest in the Internet of Things (IoT) is rapidly increasing, as the number of connected devices i...
Abstract This paper presents an ensemble learning particle swarm optimization (ELPSO) algorithm for ...
Localization in indoor environments is a hard task because of several constraints, both in terms of ...
This paper describes and compares two of the algorithms for indoor localization that are implemented...
In this paper, the problem of indoor localization in wireless networks is addressed relying on a swa...
In this paper, we focus on the application of Ultra Wide Band (UWB) technology to the problem of loc...
Abstract. In this paper, we focus on the application of Ultra Wide Band (UWB) technology to the prob...
In this dissertation, the localization of targets in indoor environment by means of the Ultra Wide B...
Wireless Sensor Networks (WSNs) consist of a collection of spatially distributed radio transceivers ...
In wireless sensor networks we often want to know where individual sensor nodesare physically positi...
We propose a low-complexity indoor localization scheme using a hybirid of particle swarm optimizatio...
In this paper we describe a method for localization of multiple persons using a distributed network ...
In this paper, we address the problem of localizing sensor nodes in a static network, given that the...
Interest in the Internet of Things (IoT) is rapidly increasing, as the number of connected devices i...
Position localization is becoming increasingly important in wireless communication networks. Ultra W...
Interest in the Internet of Things (IoT) is rapidly increasing, as the number of connected devices i...
Abstract This paper presents an ensemble learning particle swarm optimization (ELPSO) algorithm for ...
Localization in indoor environments is a hard task because of several constraints, both in terms of ...
This paper describes and compares two of the algorithms for indoor localization that are implemented...