Context Aware Handover Algorithms For Mobile Positioning Systems

This work proposes context aware handover algorithms for mobile positioning systems. The algorithms perform handover among positioning systems based on important contextual factors related to position determination with efficient use of battery. The proposed solution is implemented in the form of an Android application named Locate@nav6. The performance of the proposed solution was tested in selected experimental areas. The handover performance was compared with other existing location applications. The proposed solution performed correct handover among positioning systems in 95 percent of cases studied while two other applications performed correct handover in only 50 percent of cases studied. Battery usage of the proposed solution is less than one third of the battery usage of two other applications. The analysis of the positioning error of the applications demonstrated that, the proposed solution is able to reduce positioning error indirectly by handing over the task of positioning to an appropriate positioning system. This kept the average error of positioning below 42.1 meters for Locate@nav6 while the average error for two other applications namely Google Latitude and Malaysia maps was between 92.7 and 171.13 meters

Context Aware Handover Algorithms for Mobile Positioning Systems

Abstract: This work proposes context aware handover algorithms for mobile positioning systems. The algorithms perform handover among positioning systems based on important contextual factors related to position determination with efficient use of battery. The proposed solution which consists of the algorithms is implemented in the form of an Android application named Locate@nav6. The performance of the proposed solution was tested in selected experimental areas. The handover performance was compared with other existing location applications. The proposed solution performed correct handover among positioning systems in 95% of cases studied while two other applications performed correct handover in only 50% of cases studied. Battery usage of the proposed solution is less than one third of the battery usage of two other applications. The analysis of the positioning error of the applications demonstrated that, the proposed solution is able to reduce positioning error indirectly by handing over the task of positioning to an appropriate positioning system. This kept the average error of positioning below 42.1 meters for Locate@nav6 while the average error for two other applications namely Google Latitude and Malaysia maps was between 92.7 and 171.13 meters

An Implementation Approach and Performance Analysis of Image Sensor Based Multilateral Indoor Localization and Navigation System

Optical camera communication (OCC) exhibits considerable importance nowadays in various indoor camera based services such as smart home and robot-based automation. An android smart phone camera that is mounted on a mobile robot (MR) offers a uniform communication distance when the camera remains at the same level that can reduce the communication error rate. Indoor mobile robot navigation (MRN) is considered to be a promising OCC application in which the white light emitting diodes (LEDs) and an MR camera are used as transmitters and receiver respectively. Positioning is a key issue in MRN systems in terms of accuracy, data rate, and distance. We propose an indoor navigation and positioning combined algorithm and further evaluate its performance. An android application is developed to support data acquisition from multiple simultaneous transmitter links. Experimentally, we received data from four links which are required to ensure a higher positioning accuracy

NAVIO - A Navigation Service for Pedestrains

In the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environments) at our university (Vienna University of Technology), we are working on the improvement of navigation services for pedestrians. We are mainly focusing on the information aspect of location-based services, i.e., on the user\u27s task at hand and the support of the user\u27s decisions by information provided by navigation services. Specifications allow us to select appropriate sensor data and to integrate data when and where needed, to propose context-dependent routes fitting to partly conflicting interests and goals as well as to select appropriate communication methods in terms of supporting the user by various multimedia cartography forms. In this paper, these tasks are addressed in three different work packages: Integrated positioning, Pedestrian route modeling, and Multimedia route communication. In this paper we will concentrate on the findings of the first work package. For continuous positioning of a pedestrian suitable location, technologies include GNSS and indoor location techniques, cellular phone positioning, dead reckoning sensors (e.g. magnetic compass, gyro and accelerometers) for measurement of heading and travelled distance as well as barometric pressure sensors for height determination. The integration of these sensors in a modern multi-sensor system can be performed using an adapted Kalman filter. To test and to demonstrate our approach, we take a use case scenario into account, i.e., the guidance of visitors to departments of the University. The results of simulation studies and practical tests will confirm whether such a service can achieve a high level of performance for the guidance of pedestrians in urban areas and in mixed indoor and outdoor environments

Distributed and adaptive location identification system for mobile devices

Indoor location identification and navigation need to be as simple, seamless, and ubiquitous as its outdoor GPS-based counterpart is. It would be of great convenience to the mobile user to be able to continue navigating seamlessly as he or she moves from a GPS-clear outdoor environment into an indoor environment or a GPS-obstructed outdoor environment such as a tunnel or forest. Existing infrastructure-based indoor localization systems lack such capability, on top of potentially facing several critical technical challenges such as increased cost of installation, centralization, lack of reliability, poor localization accuracy, poor adaptation to the dynamics of the surrounding environment, latency, system-level and computational complexities, repetitive labor-intensive parameter tuning, and user privacy. To this end, this paper presents a novel mechanism with the potential to overcome most (if not all) of the abovementioned challenges. The proposed mechanism is simple, distributed, adaptive, collaborative, and cost-effective. Based on the proposed algorithm, a mobile blind device can potentially utilize, as GPS-like reference nodes, either in-range location-aware compatible mobile devices or preinstalled low-cost infrastructure-less location-aware beacon nodes. The proposed approach is model-based and calibration-free that uses the received signal strength to periodically and collaboratively measure and update the radio frequency characteristics of the operating environment to estimate the distances to the reference nodes. Trilateration is then used by the blind device to identify its own location, similar to that used in the GPS-based system. Simulation and empirical testing ascertained that the proposed approach can potentially be the core of future indoor and GPS-obstructed environments

Wi-Fi Fingerprinting for Indoor Positioning

Wireless Fidelity (Wi-Fi) Fingerprinting is a remarkable approach developed by modern science to detect the user’s location efficiently. Today, the Global Positioning System (GPS) is used to keep track of our current location for outdoor positioning. In GPS technology, satellite signals cannot reach indoor environments as they are shielded from obstructions so that indoor environments with a lack of Line of Sight (LoS) do not provide enough satellite signal accuracy. Since indoor environments are very difficult to track, thus, a wide variety of techniques for dealing with them have been suggested. The best way to offer an indoor positioning service with the current technology is Wi-Fi since the most commercial infrastructure is well equipped with Wi-Fi routers. For indoor positioning systems (IPS), Wi-Fi fingerprinting approaches are being extremely popular. In this paper, all the approaches for Wi-Fi fingerprinting have been reviewed for indoor position localization. Related to Wi-Fi fingerprinting, most of the algorithms have been interpreted and the previous works of other researchers have been critically analyzed in this paper to get a clear view of the Wi-Fi fingerprinting process

Wi-Fi Fingerprinting for Indoor Positioning

Wireless Fidelity (Wi-Fi) Fingerprinting is a remarkable approach developed by modern science to detect the user’s location efficiently. Today, the Global Positioning System (GPS) is used to keep track of our current location for outdoor positioning. In GPS technology, satellite signals cannot reach indoor environments as they are shielded from obstructions so that indoor environments with a lack of Line of Sight (LoS) do not provide enough satellite signal accuracy. Since indoor environments are very difficult to track, thus, a wide variety of techniques for dealing with them have been suggested. The best way to offer an indoor positioning service with the current technology is Wi-Fi since the most commercial infrastructure is well equipped with Wi-Fi routers. For indoor positioning systems (IPS), Wi-Fi fingerprinting approaches are being extremely popular. In this paper, all the approaches for Wi-Fi fingerprinting have been reviewed for indoor position localization. Related to Wi-Fi fingerprinting, most of the algorithms have been interpreted and the previous works of other researchers have been critically analyzed in this paper to get a clear view of the Wi-Fi fingerprinting process

RSSI Fingerprinting Approach for Location-Based Services

Location information is becoming increasingly important in many pervasive computing applications and it has been widely used in various industries as location aware that can provide functions such as navigation aids, geographic contextual information, movement tracking, emergency location, geographically selective communication and many other useful functions. The objective of this project is to implement Location Based Services (LBS) for medical facilities such as hospitals and asylums in order to improve their operations. For the first half of the project duration which is this semester, I mainly focus on the problem of localization. Therefore, based on my knowledge and developed tools in localization, I can further develop a locationbased service system. In order to performthis project, I will create a simulation whereby I will select one area probably my hostel house to study the problem of localization. My goal is to locate a person when she/he is walking around the house. To achieve the goal, we will encounter a lot of problems such as, how to collect the signals from the wireless access points, how to process the data, how to choose and apply the algorithm in order to use the collected signals and so on. Every problem mentioned will affectthe accuracy in localization. Therefore in this report, we will introduce how we can solve this problems