Mobile Beacon Research Articles

Mobile Real-time Tracking of Acute Stroke Patients and Instant, Secure Inter-team Communication - the Join App.

PurposeThe primary correlate to survival and preservation of neurologic function in patients suffering from an acute ischemic stroke is time from symptom onset to initiation of therapy and reperfusion. Communication and coordination among members of the stroke team are essential to maximizing efficiency and subsequently early reperfusion. In this work, we aim to describe our preliminary experience using the Join mobile application as a means to improve interdisciplinary team communication and efficiency.Materials and MethodsWe describe our pilot experience with the initiation of the Join mobile application between July 2015 and July 2016. With this application, a mobile beacon is transported with the patient on the ambulance. Transportation milestone timestamps and geographic coordinates are transmitted to the treating facility and instantly communicated to all treatment team members. The transport team / patient can be tracked en route to the treating facility.ResultsDuring our pilot study, 62 patients were triaged and managed using the Join application. Automated time-stamping of critical events, geographic tracking of patient transport and summary documents were obtained for all patients. Treatment team members had an overall favorable impression of the Join application and recommended its continued use.ConclusionThe Join application is one of several components of a multi-institutional, interdisciplinary effort to improve the treatment of patients with acute ischemic stroke. The ability of the treatment team to track patient transport and communicate with the transporting team may improve reperfusion time and, therefore, improve neurologic outcomes.

A node localisation approach based on mobile beacon using particle swarm optimisation in wireless sensor networks

A node localisation approach based on mobile beacon using particle swarm optimisation in wireless sensor networks

Node localization algorithm of wireless sensor networks with mobile beacon node

When maximum movement distance of beacon node is limited, in order to improve the localization accuracy of sensor nodes, node localization algorithm of wireless sensor networks with mobile beacon node (NLA_MB) is proposed. NLA_MB algorithm divides the movement area of beacon node into some hexagonal grids, and establishes optimization model of node localization errors according to the movement path constraint, movement distance constraint and other constraints of beacon node. Beacon node uses heuristic method to solve the model approximately based on virtual force theory and location information of guide sensor nodes, and obtains a moving path which is suitable for the current node distribution. According to location information of beacon node or anchor sensor nodes, sensor nodes use maximum likelihood estimation algorithm to calculate their own location coordinates. Simulation results show that NLA_MB algorithm is suitable for the distribution scenarios of sensor nodes, such as full coverage distribution, L-type distribution, Tian-type distribution and U-type distribution. It can increase the number of sojourn locations of beacon node and average number of anchor points of sensor nodes, and reduce average localization error of sensor nodes. Under certain conditions, NLA_MB algorithm outperforms DOUBLE_SCAN, ZSCAN, MLE, RSCAN and DBMS algorithms.

SALA: Smartphone-Assisted Localization Algorithm for Positioning Indoor IoT Devices

This paper proposes a Smartphone-Assisted Localization Algorithm (SALA) for the localization of Internet of Things (IoT) devices that are placed in indoor environments (e.g., smart home, smart office, smart mall, and smart factory). This SALA allows a smartphone to visually display the positions of IoT devices in indoor environments for the easy management of IoT devices, such as remote-control and monitoring. A smartphone plays a role of a mobile beacon that tracks its own position indoors by a sensor-fusion method with its motion sensors, such as accelerometer, gyroscope, and magnetometer. While moving around indoor, the smartphone periodically broadcasts short-distance beacon messages and collects the response messages from neighboring IoT devices. The response messages contains IoT device information. The smartphone stores the IoT device information in the response messages along with the message’s signal strength and its position into a dedicated server (e.g., home gateway) for the localization. These stored trace data are processed offline through our localization algorithm along with a given indoor layout, such as apartment layout. Through simulations, it is shown that our SALA can effectively localize IoT devices in an apartment with position errors less than 20 cm in a realistic apartment setting.

Efficient Distributed Localization Algorithm for Wireless Sensor Networks

Background: WSN covers a wide spectrum of military and hospital monitoring, military surveillance, fire and intruder detection and animal tracking. Objective: Among the various applications mentioned above, WSN plays a vital role in Internet of Things (IoT). It allows us to develop an intelligent system when there is a dynamic change in the environment. Results: It is shown that the localization error of the proposed system is less than the existing system. So it is a precise efficient localization for WSN. Conclusion: The proposed WSN uses distributed, RSS based and mobile beacon localization algorithm which gives relatively high precision. It can be used in a dynamic environment. It can reduce the energy consumption and also localization error.

The Perils and Possibilities of the Urban Library as Digital Inclusion Institution

Recently several libraries in the U.S. have sought to extend their services and ameliorate local digital divides by instituting hotspot lending programs. These programs essentially move Internet connectivity into people’s homes by loaning out devices that connect to 3G or 4G cellular networks, and then allow patrons subsidized access to the Internet from anywhere on that network. The largest one, in New York City, has loaned 10,000 hotspot devices, targeting people with no home broadband service. New York Public Library (NYPL) partnered with rural libraries in Maine and Kansas to develop hotspot lending programs. Other library programs in St. Paul, Chicago, Kansas City, Seattle, and Bellingham, Massachusetts also are experimenting with providing their users loaned devices that use cell phone networks to provide simultaneous, at-home connectivity capable of supporting several devices (such as desktop computers, tablets, or mobile phones). Non-profit Mobile Beacon, a hotspot and connectivity broker working with many hotspot lending programs, cites possible benefits associated with these programs, including providing opportunities for children to do homework at home using the Internet and thus reducing the “homework gap;” searching for job opportunities; staying in touch with distant family; and facilitating seniors as they search for health information. However, to date there has been no formal, publicly available investigation of the library hotspot programs. The research reported here examines several questions associated with supporting this cost-effective method of providing home-based Internet connectivity. It aims to shed light on policy options for urban broadband challenges even as many larger cities are embarking on their own Digital Inclusion programs and as the FCC transitions to a universal service program espousing a threshold broadband service. Our core questions examine: (1) the affordances in offering a subsidized, relatively easy but still limited source of home-based broadband to distinctive urban populations and environments; and (2) the role of locally-based access and expertise represented by libraries specifically. Library hotspot programs could remediate broadband access, but beyond that libraries offer teaching and support roles that are neighborhood-based. Should they be a significant part of the solution to the current digital divide? Initiated in December, 2015, our research on New York City’s hotspot program - the largest in the country – includes some user survey data as well as the results of focus groups with users. While this study is ongoing, preliminary data suggest the program successfully reached a low income population, and that the types of Internet uses were varied but included instrumental applications such as continuing education and employment. While the intended population of parents with school-age children was not as present as anticipated, there was clear evidence of a widespread need for affordable Internet. The users were not Internet naifs, but there is some evidence that the longer connection availability afforded by having a hotspot increased both skills levels and confidence with the Internet. The hotspots appeared to assist with homework gap problems, and the data suggest that adults outside of a child’s direct family also had a role in assisting with Internet-based homework.

Mobile beacon based range free localization method for wireless sensor networks

The existing mobile beacon based range free localization method has two basic problems: (1) the accuracy of position estimation depends on closer beacon broadcasting intervals and (2) varying radio...

Dynamic Improved Path Planning for Mobile Beacon in Wireless Sensor Network

The main intention of wireless sensor network is to provide the information about the spatiotemporal characteristics of the observed physical world. In many wireless sensor network applications, namely forest fire detection, animal tracking etc., it is important to locate the sensor with accuracy. Locating the sensors after they have deployed is termed as localization. Most of the localization algorithm relies on the availability of reasonably accurate location information. This is valid only in few networks which has location sensing devices, such as GPS receivers are available at all nodes. In real time, equipping GPS with all sensor nodes are rare due to its cost, power. To overcome these limitations various path have been proposed to derive approximated locations of all nodes using the mobile beacon. In existing systems, Localization techniques that are proposed for sensor nodes are calculated by receiving the mobile beacon signal with their coordinates by incorporating the various path planning scheme like SCAN, DOUBLE SCAN, HILBERT and Z curve for trajectory of mobile beacon. Those path planning strategies resulting in existence of collinear problem and localization error of nodes. In this paper, a novel Tree - Climbing path planning mechanism is proposed. The proposed path ensures to overcome collinear problem by travelling in a tree based path. The performance of a novel tree climbing is analysed using the NS2 simulator.

An Efficient Node Localization Approach with RSSI for Randomly Deployed Wireless Sensor Networks

An efficient path planning approach in mobile beacon localization for the randomly deployed wireless sensor nodes is proposed in this paper. Firstly, in order to improve localization accuracy, the weighting function based on the distance between nodes is constructed. Moreover, an iterative multilateration algorithm is also presented to avoid decreasing the localization accuracy. Furthermore, a path planning algorithm based on grid scan which can traverse entirely in sensor field is described. At the same time, the start conditions of localization algorithm are also proposed to improve localization accuracy. To evaluate the proposed path planning algorithm, the localization results of beacon nodes randomly deployed in sensor field are also provided. The proposed approach can provide the deployment uniformly of virtual beacon nodes among the sensor fields and the lower computational complexity of path planning compared with method which utilizes only mobile beacons on the basis of a random movement. The performance evaluation shows that the proposed approach can reduce the beacon movement distance and the number of virtual mobile beacon nodes by comparison with other methods.

Distance outlier detection with a mobile beacon in wireless sensor networks localisation

Range-based localisation algorithms rely on distance measurements between nodes. If outlier distances exist, they make the estimated positions deviate from the true positions. Thus, it is important to detect and remove outlier distance measurements to achieve high localisation accuracy. In this paper, we propose a novel outlier detection approach called middle distance mobile beacon placement MDMP. Different from the traditional triangle-inequality-based approach that can detect only the existence of outlier distances but cannot distinguish which measurements are outliers, MDMP can exactly find which distances are outliers and exclude them from the localisation process. This prevents nodes from getting wrong position estimates caused by these outlier measurements. Simulation results show that MDMP improves the outlier detection accuracy by identifying more outliers than the traditional triangle inequality violation TIV-based method does. The evaluation results also show remarkable improvement in location accuracy by deleting outliers with MDMP.

Mobile beacon control algorithm that ensures observability in single range navigation

Abstract: Mobile beacon vehicles are used as navigational aid for autonomous underwater vehicles when performing navigation using single range measurements. They remove the constraints imposed on the underwater vehicle trajectory by executing trajectory that provides persistent range measurements. In this paper, control algorithm for beacon vehicle which ensures observability of the underwater vehicle’s navigation filter is presented. It is characterized by small communication overhead, low computational complexity and it is deployable on both fully actuated and underactuated vehicles. The algorithm was tested in real-life environment and the acquired experimental results show that despite the presence of uncertainties and communication delays, the algorithm accomplishes its task.

An analytical geometric range free localization scheme based on mobile beacon points in wireless sensor network

In many applications of wireless sensor network, the position of the sensor node is useful to identify the actuating response of the environment. The main idea of the proposed localization scheme i...

Coordinates and Bearing of Submerged Sensors Using a Single Mobile Beacon (CSMB)

This paper investigates the problem of localizing submerged sensors and provides a new mechanism to determine the coordinates and bearing of those sensors using only one beacon node. In underwater wireless sensor networks (UWSN), precise coordinates of the sensors that actuate or collect data is vital, as data without the knowledge of its actual origin has limited value. Mostly, the multilateration technique is used to determine the location of the sensors with respect to three or more known beacon nodes, besidesincorporated nonlinear distance equations are solved in conventional method whereby degree-of-freedom does not guarantee a unique solution. In this study, a new method of determining the coordinates of submerged sensors with a single mobile beacon has been devised which requires no preinstalled infrastructure or reference point. Moreover, Cayley-Menger determinant and linearized trilateration are used to determine the coordinates of the nodes where none of the nodes have a priori knowledge about its location. Simulation results validate the proposed mathematical model by computing coordinates of sensor nodes with bearing information generating negligible errors

Sparse Localization with a Mobile Beacon Based on LU Decomposition in Wireless Sensor Networks

Node localization is the core in wireless sensor network. It can be solved by powerful beacons, which are equipped with global positioning system devices to know their location information. In this article, we present a novel sparse localization approach with a mobile beacon based on LU decomposition. Our scheme firstly translates node localization problem into a 1-sparse vector recovery problem by establishing sparse localization model. Then, LU decomposition pre-processing is adopted to solve the problem that measurement matrix does not meet the re- stricted isometry property. Later, the 1-sparse vector can be exactly recovered by compressive sensing. Finally, as the 1-sparse vector is approximate sparse, weighted Cen- troid scheme is introduced to accurately locate the node. Simulation and analysis show that our scheme has better localization performance and lower requirement for the mobile beacon than MAP+GC, MAP-M, and MAP-M&N schemes. In addition, the obstacles and DOI have little effect on the novel scheme, and it has great localization performance under low SNR, thus, the scheme proposed is robust.

An Efficient Geometric Localization Approach for Distributed Sensor Networks

Localization is a fundamental problem in wireless sensor networks. Many approaches, including range-based and range-free techniques, have been proposed to determine the optimal location for sensor nodes. This paper presents a simple range-free localization scheme that is based on received signal strength indicator (RSSI) geometric localization for wireless sensor networks. The node locations are computed by performing simple geometric calculations that rely on the specific approximate RSSI values with the position of a mobile beacon equipped with a global positioning system. The simulation results showed that the proposed scheme is efficient, and that the node positions can be determined accurately.

Range–only navigation – maximizing system observability by using extremum seeking

Mobile beacon vehicles can be used as navigational aid for autonomous underwater vehicles when performing navigation using single range measurements. Using mobile beacon removes constraints imposed on the underwater vehicle trajectory because mobile beacon executes trajectories that ensure persistent range measurements. In this paper extremum seeking based control of beacon vehicle which ensures good observability with small communication overhead is proposed. First cost function which gives measure of observability is derived. In addition, extremum seeking loop for steering mobile beacon is presented. Finally, simulation results of proposed algorithm are presented.

DV-hop node localisation algorithm with multi-mobile beacons in wireless sensor networks

This paper proposes a node localisation algorithm with multi-mobile beacons in order to improve the accuracy of localisation and avoid scanning the unknown nodes repeatedly. Three mobile beacons are designed to traverse the WSNs and simultaneously maintain the relative location relations between them based on equal distance three-coverage and then trilateration technology and DV-hop algorithm are used to localise the unknown nodes. The simulation results show that the algorithm outperforms DV-hop and MB-DV-hop in the aspects of accuracy and communication overhead and its moving path length of single beacon is also shorter than that of MB-DV-hop.

A 3D localisation method for searching survivors/corpses based on WSN and Kalman filter

Localisation is a key technique in Internet of Things (IoT) and wireless sensor network (WSN). Currently, for indoor localisation there are many approaches, e.g., RFID based, ultrasonic sensor based, etc. However, when an earthquake happens, the devices for localisation in a building may be damaged and how to quickly locate the survivors/corpses buried in a collapse regional is a key issue. In the paper, we propose a 3D localisation method for searching survivors/corpses based on WSN. It mainly consists of two stages. In the first stage, a draft location is calculated based on beacon nodes, and then a detailed location is computed in the second stage based on a mobile beacon node moving along a triangle. Meanwhile, we employed Kalman filter in the method to acquire stable received signal strength indicators (RSSIs). Finally, we implement a robot car with a sensor node acting as a mobile beacon node and evaluate the proposed method through experiments in a gym.

Wireless Sensor Network Localization Based On A Mobile Beacon And Tsvm

Abstract In this paper a new wireless sensor network localization algorithm, based on a mobile beacon and TSVM (Transductive Support Vector Machines) is proposed, which is referred to as MTSVM. The new algorithm takes advantage of a mobile beacon to generate virtual beacon nodes and then utilizes the beacon vector produced by the communication between the nodes to transform the problem of localization into one of classification. TSVM helps to minimize the error of classification of unknown fixed nodes (unlabeled samples). An auxiliary mobile beacon is designed to save the large volumes of expensive sensor nodes with GPS devices. As shown by the simulation test, the algorithm achieves good localization performance.

Impact of static trajectories on localization in wireless sensor networks

A Wireless Sensor Network (WSN) consists of many sensors that communicate wirelessly to monitor a physical region. Location information is critical essential and indispensable for many applications of WSNs. A promising solution for localizing statically deployed sensors is to benefit from mobile location-aware nodes called beacons. However, the essential problem is to find the optimum path that the mobile beacon should travel in order to improve localization accuracy, time and success as well as energy efficiency. In this paper, we evaluate the performance of five mobile beacon trajectories; Random Way Point, Scan, Hilbert, Circles and Localization algorithm with a Mobile Anchor node based on Trilateration (LMAT) based on three different localization techniques such as Weighted Centroid Localization and trilateration with time priority and accuracy priority. This evaluation aims to find effective and essential properties that the trajectory should have. Our simulations show that a random movement cannot guarantee the performance of localization. The results also show the efficiency of LMAT regarding accuracy, success and collinearity while the Hilbert space filling curve has lower energy consumption. Circles path planning can help to localize unknown sensors faster than others at the expense of lower localization precision.