Implementasi Hasil Perancangan Sistem Pelacakan dengan Menggunakan Antena Tracking Sistem

Orbital perturbation is a phenomenon in which the orbit of a satellite changes due to one or more external influences such as an anomaly in the Earth's gravitational distribution, gravitational disturbances from the moon, meteor impacts or other objects, or solar radiation pressure. These maneuvers use small rockets (thrusters) that are on the satellite body and the direction is set according to the correction direction. Ignition of these small rockets will consume fuel brought by satellites from Earth as a provision. Communications satellites have demonstrated their capabilities since the last three decades. that the communication satellite mission in the 60s was an alternative point-to-point transmission between continents, due to its ability to see approximately one third of the earth's surface from the geostationary orbit altitude just above the equator

Enhanced Mechanisms for Navigation and Tracking Services in Smart Phones

Combining Global Positioning System (GPS) and Short Message Service (SMS), this paper develops a realisticsystem, called Mobile Navigation and Tracking System (MNTS), to provide navigation and target tracking services.MNTS is an Android based mobile application which integrated many enhanced mechanisms for navigation andtarget tracking services. MNTS not only provides users with the GPS navigation capability, but also supports QuickResponse (QR) code decoding, nearby scenic spot searching, friend positioning and target tracking. In targettracking, MNTS utilizing SMS mainly adopts two proposed novel approaches: location prediction and dynamicthreshold to reduce the number of short message transmissions while maintaining location accuracy within anacceptable range. Location prediction utilizes the current target’s location, moving speed, bearing to predict its nextlocation. When the distance between the predicted location and the actual location exceeds a threshold, the targetsends a short message to the tracker to update the actual location. Based on the movement speed of the target,the threshold is dynamically adjusted to balance the location accuracy and the number of short messages.Furthermore, as MNTS is free and open-source software, service providers or developers can easily extend theirown services based on this system

Implementasi Sistem Pelacakan Kendaraan Bermotor Menggunakan Gps Dan Gprs Dengan Integrasi Googlemap

Abstract— Vehicle tracking system using GPS and GPRS integration googlemap provide information that is maximized with the technology of GPS (Global Positioning System) receiver which can indicate the position of the vehicle with the map and the ability of the appointment of direction and position coordinates (x, y or latitude, longitude) textually and visual at any location. Vehicle tracking system is built using equipment GIS (Geographic Information System) and dedicated to smartphones which support Global Positioning System (GPS), as well as portable computers, using General Packet Radio Service (GPRS) as a connection to the internet. The hardware used is a smartphone that supports GPS with supporting tools used are GoogleMaps, Notepad + +, NetBeans IDE 6.5.1, Mysql, Java (J2ME), PHP, JavaScript. The results of this system in the form of tracking system capable of monitoring the movement of vehicles on an ongoing position by utilizing GPS and GPRS as the sender of the wireless data and Internet connections.  Keywords— GIS, GPS, GPRS, googlemaps, J2ME

Adaptive, reliable, and accurate positioning model for location-based services

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis presents a new strategy in achieving highly reliable and accurate position solutions fulfilling the requirements of Location-Based Services (LBS) pedestrians’ applications. The new strategy is divided into two main parts. The first part integrates the available positioning technology within the surrounding LBS application context by introducing an adaptive LBS framework. The context can be described as a group of factors affecting the application behaviour; this includes environmental states, available resources and user preferences. The proposed adaptive framework consists of several stages, such as defining the contextual factors that have a direct effect on the positioning performance, identifying preliminary positioning performance requirements associated with different LBS application groups, and introducing an intelligent positioning services selection function. The second part of this work involves the design and development of a novel positioning model that is responsible for delivering highly reliable, accurate and precise position solutions to LBS users. This new model is based on the single frequency GPS Standard Positioning Service (SPS). Additionally, it is incorporated within the adaptive LBS framework while providing the position solutions, in which all identified contextual factors and application requirements are accounted. The positioning model operates over a client-server architecture including two main components, described as the Localisation Server (LS) and the Mobile Unit (MU). Hybrid functional approaches were developed at both components consisting of several processing procedures allowing the positioning model to operate in two position determination modes. Stand-alone mode is used if enough navigation information was available at the MU using its local positioning device (GPS/EGNOS receiver). Otherwise, server-based mode is utilised, in which the LS intervenes and starts providing the required position solutions. At the LS, multiple sources of GPS augmentation services were received using the Internet as the sole augmentation data transportation medium. The augmentation data was then processed and integrated for the purpose of guaranteeing the availability of valid and reliable information required for the provision of accurate and precise position solutions. Two main advanced position computation methods were developed at the LS, described as coordinate domain and raw domain. The positioning model was experimentally evaluated. According to the reported results, the LS through the developed position computation methods, was able to provide position samples with an accuracy of less than 2 meters, with high precision at 95% confidence level; this was achieved in urban, rural, and open space (clear satellite view) navigation environments. Additionally, the integrity of the position solutions was guaranteed in such environments during more than 90% of the navigation time, taking into consideration the identified integrity thresholds (Horizontal Alert Limits (HAL)=11 m). This positioning performance has outperformed the existing GPS/EGNOS service which was implemented at the MU in all scenarios and environments. In addition, utilising a simulation evaluation facility the developed positioning model performance was quantified with reference to a hybrid positioning service that will be offered by future Galileo Open Service (OS) along with GPS/EGNOS. Using the statistical t-test, it was concluded that there is no significant difference in terms of the position samples’ accuracy achieved from the developed positioning model and the hybrid system at a particular navigation environment described as rural area. The p-value was 0.08 and the level of significance used was 0.05. However, a significant difference in terms of the service integrity for the advantage of the hybrid system was experienced in all remaining scenarios and environments more especially the urban areas due to surrounding obstacles and conditions

Exploring Techniques for Providing Privacy in Location-Based Services Nearest Neighbor Query

Increasing numbers of people are subscribing to location-based services, but as the popularity grows so are the privacy concerns. Varieties of research exist to address these privacy concerns. Each technique tries to address different models with which location-based services respond to subscribers. In this work, we present ideas to address privacy concerns for the two main models namely: the snapshot nearest neighbor query model and the continuous nearest neighbor query model. First, we address snapshot nearest neighbor query model where location-based services response represents a snapshot of point in time. In this model, we introduce a novel idea based on the concept of an open set in a topological space where points belongs to a subset called neighborhood of a point. We extend this concept to provide anonymity to real objects where each object belongs to a disjointed neighborhood such that each neighborhood contains a single object. To help identify the objects, we implement a database which dynamically scales in direct proportion with the size of the neighborhood. To retrieve information secretly and allow the database to expose only requested information, private information retrieval protocols are executed twice on the data. Our study of the implementation shows that the concept of a single object neighborhood is able to efficiently scale the database with the objects in the area. The size of the database grows with the size of the grid and the objects covered by the location-based services. Typically, creating neighborhoods, computing distances between objects in the area, and running private information retrieval protocols causes the CPU to respond slowly with this increase in database size. In order to handle a large number of objects, we explore the concept of kernel and parallel computing in GPU. We develop GPU parallel implementation of the snapshot query to handle large number of objects. In our experiment, we exploit parameter tuning. The results show that with parameter tuning and parallel computing power of GPU we are able to significantly reduce the response time as the number of objects increases. To determine response time of an application without knowledge of the intricacies of GPU architecture, we extend our analysis to predict GPU execution time. We develop the run time equation for an operation and extrapolate the run time for a problem set based on the equation, and then we provide a model to predict GPU response time. As an alternative, the snapshot nearest neighbor query privacy problem can be addressed using secure hardware computing which can eliminate the need for protecting the rest of the sub-system, minimize resource usage and network transmission time. In this approach, a secure coprocessor is used to provide privacy. We process all information inside the coprocessor to deny adversaries access to any private information. To obfuscate access pattern to external memory location, we use oblivious random access memory methodology to access the server. Experimental evaluation shows that using a secure coprocessor reduces resource usage and query response time as the size of the coverage area and objects increases. Second, we address privacy concerns in the continuous nearest neighbor query model where location-based services automatically respond to a change in object*s location. In this model, we present solutions for two different types known as moving query static object and moving query moving object. For the solutions, we propose plane partition using a Voronoi diagram, and a continuous fractal space filling curve using a Hilbert curve order to create a continuous nearest neighbor relationship between the points of interest in a path. Specifically, space filling curve results in multi-dimensional to 1-dimensional object mapping where values are assigned to the objects based on proximity. To prevent subscribers from issuing a query each time there is a change in location and to reduce the response time, we introduce the concept of transition and update time to indicate where and when the nearest neighbor changes. We also introduce a database that dynamically scales with the size of the objects in a path to help obscure and relate objects. By executing the private information retrieval protocol twice on the data, the user secretly retrieves requested information from the database. The results of our experiment show that using plane partitioning and a fractal space filling curve to create nearest neighbor relationships with transition time between objects reduces the total response time