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Localization is a highly important topic in wireless sensor networks as well as in many Internet of Things applications. Many current localization algorithms are based on the Sequential Monte Carlo Localization method (MCL), the accuracy of which is bounded by the radio range. High computational complexity in the sampling step is another issue of these approaches. We present Tri-MCL which significantly...
A localization method for mobile sensor networks is presented in this paper. In order to reduce localization errors, the artificial bee colony (ABC) algorithm is used to refine the estimated coordinates. The fundamental concept of the ABC algorithm is to find better feasible solution (food source) from food sources in the specific space. Using the idea, this paper study integrates the ABC algorithm,...
The node localization is one of the most important research issues in wireless sensor networks (WSNs). Traditionally, hop-count-based localization methods only take on integer value and have a same distance estimation to all of a node's one-hop neighbors. In this paper, a novel approach termed hop-count-based expectation of distance (HCED) algorithm is proposed. By partitioning an anchor's neighbor...
Positioning and tracking of wireless devices in indoor environment is a challenging research problem. Accurate localization of a moving target is a fundamental requirement in Wireless Sensor Networks monitoring applications. In this paper, a novel location tracking algorithm which combines learning methods is proposed. In previous work, regression tree using received signal strength method is proposed...
GPS (Global Positioning System) cannot be used for localization object in indoor environments. Even though, estimation of localization is an important requirement in wireless sensor networks to determine the position of the object. Localization based on RSSI (Received Signal Strength Indicator) has low accuracy because of attenuation of the transmitted signal as a function of the distance between...
Target tracking is an application in WSN (Wireless Sensor Network) that estimating directly the mobile target position. However, in indoor location with large coverage area it is difficult to get the precision estimation, especially using RSSI (received strength signal indicator) with poor accuracy. The condition of an indoor location with many walls, obstacle, pillar, doors, multipath fading, and...
As part of a larger scope work that studies network-based positioning, that employs timing measures, this article proposes a methodology to add Cramer-Rao Bounds (CRBs) information to the propagation model. Moreover, it enables a very quick computation of CRBs for timing, avoiding the growing computational effort resulting from Fisher's matrix formulation and its inversion for each required position...
Accuracy and precision of positioning in UWB localization system depends on the quality of clock oscillators. Usually clock frequencies in particular nodes have different offsets what influences system performance. The paper presents a method for nodes synchronization and distribution of reference time interval. Anchor nodes measure time of arrival of packets conveying reference time information....
The diffusion of the Internet of Things paradigm, in the last few years, has led to the need of deploying and managing large-scale Wireless Sensor Networks (WSNs), composed by a multitude of geographically distributed sensors, like the ones needed for Smart City applications. The traditional way to manage WSNs is not suitable for this type of applications, because manually managing and monitoring...
Connected vehicles extend the capability of information collection, and thus open more opportunities for innovative advanced driver assistance systems (ADAS). In this paper, we propose a Lane Speed Monitoring (LSM) application based on vehicle-to-vehicle (V2V) communication. This application takes advantage of Basic Safety Messages (BSM) transmitted from equipped vehicles via dedicated short range...
Latest research in composite metrics has shown potential to improve the delivery rate and the power consumption of wireless sensor networks. Nevertheless, leveraging this potential in collection applications brings significant challenges such as: collecting multiple samples of the metric, isolating the quality of the uplink, and returning the link quality information to the nodes that need it for...
Over the past decade, wireless sensor networks (WSNs) have gained more research attention for their potential applications in, e.g., healthcare, defence and environmental monitoring. However, limited channel capacity and battery life of sensors are the main design challenges in WSNs. The use of cooperative multiple-input multiple-output (MIMO) technology is one of the most promising techniques that...
Accurate occupancy information of indoor environments is one of the key prerequisites for many pervasive and context-aware services, e.g. smart building/home systems. Some of the existing occupancy inference systems can achieve impressive accuracy, but they either require labour-intensive calibration phases, or need to install bespoke hardware such as CCTV cameras, which are privacy-intrusive by default...
Data collection is a fundamental task in many wireless sensor networks applications. It is impracticable to send all sensed data to base station for each sensor node, due to the constraints in communication cost and the bandwidth. Filter can provide sensed data estimation with the error bound guarantee. For given filter [li, ui], node i sends data if and only if the sensed data is beyond the range...
In conventional wireless localization techniques, the performance is generally constrained by the number of reference nodes available in the communication range. Recently, alternative localization schemes have been proposed to utilize the internal sensors embedded in wireless devices to acquire additional useful location dependent parameters. The accelerometer based localization has attracted much...
One of the applications of wireless sensor networks is target tracking. There are several methods to target tracking and among these methods, particle filter has high capability in solving nonlinear/non-Gaussian systems. Particle filter is one of the methods for Bayesian recursive estimation for position estimation in wireless sensor networks. Clustered management of dense networks is a famous known...
In order to solve the problem of clock synchronization under the condition of small sample set, a state optimal estimation method of data fusion bases on natural selection PSO algorithm is proposed. First, use Kalman filtering algorithm and Bootstrap method to local filtering process the measurement data under the condition of Monte Carlo simulation experiment, and the reliability of the data is improved...
Ship detection is a crucial surveillance problem for the country with long coastlines. The problems are such as border security, illegal fishing, and harbor protection. To overcome those problems, radar and satellite surveillance have been used widely. However, radar and satellite are very expensive. Particularly, satellite is easily affected by the cloud which makes difficult for detection. Moreover,...
Localization is an important requirement in wireless sensor networks to determine the position of the object. Localization based on RSSI (Received Signal Strength Indicator) has low accuracy is caused by attenuation of the transmitted signal as a function of the distance between nodes. In indoor environment, the PLE (path loss exponent) values are varied depend on the environment characteristic. This...
In this paper, we propose a new distributed sensor fusion algorithm for environmental monitoring by wireless sensor networks (WSNs). The considered WSNs are assumed to have limited communication capabilities. For each sensor node, a set of local estimation algorithms are maintained as its fused model for environmental variable to be sensed. The proposed algorithm relies on local information exchange...
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