Optimization of Wi-Fi Access Point Placement for Indoor Localization

The popularity of location based applications is undiminished today. They require accurate location information which is a challenging issue in indoor environments. Wireless technologies can help derive indoor positioning data. Especially, the Wi-Fi technology is a promising candidate due to the existing and almost ubiquitous Wi-Fi infrastructure. The already deployed Wi-Fi devices can also serve as reference points for localization eliminating the cost of setting up a dedicated system. However, the primary purpose of these Wi-Fi systems is data communication and not providing location services. Thus their positioning accuracy might be insufficient. This accuracy can be increased by carefully placing the Wi-Fi access points to cover the given territory properly. In this paper, our contribution is a method based on simulated annealing, what we propose to find the optimal number and placement of Wi-Fi access points with regard to indoor positioning. We investigate its performance in a real environment scenario via simulations

On the Placement of Wi-Fi Access Points for Indoor Localization

Nowadays, the more and more popular location based applications require accurate position information even in indoor environments. Wireless technologies can be used to derive positioning data. Especially, the Wi-Fi technology is popular for indoor localization because the existing and almost ubiquitous worldwide Wi-Fi infrastructure can be reused lowering the expenses. However, the primary purpose of these Wi-Fi systems is different from being used for positioning services, thus the accuracy they provide might be low. This accuracy can be increased by carefully placing the Wi-Fi access points to cover the given territory appropriately. In this paper, we propose a simulated annealing based method to find, in a given area, the optimal number and placement of Wi-Fi access points to be used for indoor positioning. We investigate the performance of our method via simulations

Improved Localization Algorithms in Indoor Wireless Environment

Localization has been considered as an important precondition for the location-dependent applications such as mobile tracking and navigation.To obtain specific location information, we usually make use of Global Positioning System(GPS), which is the most common plat- form to acquire localization information in outdoor environments. When targets are in indoor environment, however, the GPS signal is usually blocked, so we also consider other assisted positioning techniques in order to obtain accurate position of targets. In this thesis, three different schemes in indoor environment are proposed to minimize localization error by placing refer- ence nodes in optimum locations, combining the localization information from accelerometer sensor in smartphone with Received Signal Strength (RSS) from reference nodes, and utilizing frequency diversity in Wireless Fidelity (WiFi) environment. Deployments of reference nodes are vital for locating nearby targets since they are used to estimate the distances from them to the targets. A reference nodes’ placement scheme based on minimizing the average mean square error of localization over a certain region is proposed in this thesis first and is applied in different localization regions which are circular, square and hexagonal for illustration of the flexibility of the proposed scheme. Equipped with accelerometer sensor, smartphone provides useful information which out- puts accelerations in three different directions. Combining acceleration information from smart- phones and signal strength information from reference nodes to prevent the accumulated error from accelerometer is studied in this thesis. The combined locating error is narrowed by as- signing different weights to localization information from accelerometer and reference nodes. In indoor environment, RSS technology based localization is the most common way to imply since it require less additional hardware compared to other localization technologies. However, RSS can be affected greatly by complex circumstance as well as carrier frequency. Utilization of diverse frequencies to improve localization performance is proposed in the end of this thesis along with some experiments applied on Software Defined Platform (SDR)

AmIE: An Ambient Intelligent Environment for Assisted Living

In the modern world of technology Internet-of-things (IoT) systems strives to provide an extensive interconnected and automated solutions for almost every life aspect. This paper proposes an IoT context-aware system to present an Ambient Intelligence (AmI) environment; such as an apartment, house, or a building; to assist blind, visually-impaired, and elderly people. The proposed system aims at providing an easy-to-utilize voice-controlled system to locate, navigate and assist users indoors. The main purpose of the system is to provide indoor positioning, assisted navigation, outside weather information, room temperature, people availability, phone calls and emergency evacuation when needed. The system enhances the user's awareness of the surrounding environment by feeding them with relevant information through a wearable device to assist them. In addition, the system is voice-controlled in both English and Arabic languages and the information are displayed as audio messages in both languages. The system design, implementation, and evaluation consider the constraints in common types of premises in Kuwait and in challenges, such as the training needed by the users. This paper presents cost-effective implementation options by the adoption of a Raspberry Pi microcomputer, Bluetooth Low Energy devices and an Android smart watch.Comment: 6 pages, 8 figures, 1 tabl

Novel iBeacon Placement for Indoor Positioning in IoT

© 2018 IEEE. Indoor positioning and location estimation inside the buildings is still challenging in the Internet of Things platform. However, the GPS signals could successfully solve the outdoor localization problem. A recently introduced RSS-based device, named iBeacon, paves the way to estimate the users location inside the buildings. Due to the complexity of indoor RF environments, the positioning accuracy is affected by the placement of the iBeacons. Inadvertently, the concept of iBeacon placement for improving the accuracy remains unattended by the current research. This paper provides a comprehensive analysis and experiments on the importance of iBeacon placement, and factors impacting the beacon signal quality. Moreover, we propose a novel beacon placement strategy, Crystal-shape iBeacon Placement. As another contribution, a customized application for android is developed which is used for recording and analyzing the iBeacon signals. Our proposed placement strategy could achieve 21.7% higher precision than the existing normal iBeacon placement