scholarly journals IOT ENABLED INDOOR NAVIGATION SYSTEM DESIGN FOR EMERGENCIES

2019 ◽  
Vol XLII-4/W12 ◽  
pp. 61-64
Author(s):  
A. Duru ◽  
I. R. Karas
Keyword(s):  
System Design ◽  
Navigation System ◽  
Signal Propagation ◽  
Satellite System ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Positioning Accuracy ◽  
Indoor Navigation System ◽  
Global Navigation Satellite ◽  
High Building

<p><strong>Abstract.</strong> Global Navigation Satellite System is widely accepted and it has good positioning accuracy for outdoor applications. However, it does not provide sufficient positioning accuracy for inside of buildings. Signals are attenuated inside of buildings or dense high building areas because various materials between satellites and receiver create interference to the signal propagation. Thus, indoor positioning technologies have emerged to cover the problem. In this paper, indoor positioning technologies have been investigated and UWB based indoor positioning technology has been chosen between them. In addition to indoor positioning, accelerometer and Wi-Fi connection has been added to the system for mobility. The accelerometer detects emergency cases and alerts relatives of an intended person by using web service. Hereby, remote navigation system design is presented for first aid of the user. The system can detect emergencies, especially falls using the accelerometer and it can locate patients anywhere in the world. The designed system showed that it is possible to detect emergencies and transfer to the web with a 24.17&amp;thinsp;cm average positioning error. Also, it is an assuring system for future remote positioning applications.</p>

Design of Continuous Indoor Navigation System Based on INS and Wifi

2013 ◽  
Vol 303-306 ◽  
pp. 2046-2049 ◽  
Author(s):  
Yi Hu ◽  
Lei Sheng ◽  
Shan Jun Zhang
Keyword(s):  
Navigation System ◽  
Smart Phone ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
High Price ◽  
Position Information ◽  
Positioning Method ◽  
Indoor Navigation System ◽  
Navigation Service

The application of navigation, such as guidance of pedestrians, requires a certain accuracy of continuous outdoor and indoor positioning. In outdoor environments GPS system has proved to be effective. However in indoor it is challenging to control the accuracy within 2 to 3 meters. At present several approaches have been developed for indoor positioning, such as RFID. But they are mainly been implemented in professional areas, for general user such as tourists and visual incapable users it is difficult to take advantage of these technologies because of the high price of terminal and the navigation service covered area is extremely limited. In this paper, a new approach of indoor navigation method is proposed to solve the problems of traditional methods. It is based on INS and wifi positioning technology. As hardware, wifi receiver, smart phone built-in accelerometer and digital compass are selected and investigated. User’s indoor position is first estimated by dead reckoning method with INS navigation system and then be recalibrated by wifi position information. Several experiments performed in the test verified the effectiveness of this indoor continuous positioning method described in this paper.

scholarly journals INTEGRATION OF PDR AND IMAGE-BASED POSITIONING AIDED BY ARTIFICIAL NEURAL NETWORKS IN INDOOR ENVIRONMENT

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 181-185
Author(s):  
M. C. Hung ◽  
K. W. Chiang
Keyword(s):  
Dead Reckoning ◽  
Satellite System ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Positioning Method ◽  
Pros And Cons ◽  
Positioning Technique ◽  
The Mean ◽  
Global Navigation Satellite ◽  
The Cost

Abstract. Location based service (LBS) is a popular issue in recent years, which can be applied widely. The most common one is providing the local information and the guide of the Point of Interesting (POI) to users, which means positioning is the necessary technique to put LBS into practice. In an outdoor scenario, the user’s position can be obtained relying on the Global Navigation Satellite System (GNSS), however, the signal of GNSS might be blocked in a building. So, many indoor positioning techniques are developed in the decades, which have the pros and cons respectively. This paper proposes an indoor positioning technique by integrating Pedestrian Dead Reckoning (PDR) with the image-based positioning method, which can decrease the cost significantly because it only needs a camera built-in the smartphone. In the first experiment, we verify the accuracy of positioning by the proposed method, that the mean error in the horizontal direction is about 0.25 meters. In the following experiment, comparing with the misclosure of PDR only and PDR integrated with the proposed method, it can decrease from 8.53% to 1.44%. The improvement is about 83%, therefore, this method is suitable for applying to indoor navigation.

scholarly journals Cost Effective and Easily Configurable Indoor Navigation System

2021 ◽  
Vol 5 (1) ◽  
pp. 60-72
Author(s):  
Mohammed Yaseen Taha ◽  
Qahhar Muhammad Qadir
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Navigation System ◽  
Industry 4.0 ◽  
Cost Effective ◽  
Indoor Positioning ◽  
Path Selection ◽  
Indoor Navigation ◽  
Positioning Systems ◽  
Indoor Navigation System

With the advent of Industry 4.0, the trend of its implementation in current factories has increased tremendously. Using autonomous mobile robots that are capable of navigating and handling material in a warehouse is one of the important pillars to convert the current warehouse inventory control to more automated and smart processes to be aligned with Industry 4.0 needs. Navigating a robot’s indoor positioning in addition to finding materials are examples of location-based services (LBS), and are some major aspects of Industry 4.0 implementation in warehouses that should be considered. Global positioning satellites (GPS) are accurate and reliable for outdoor navigation and positioning while they are not suitable for indoor use. Indoor positioning systems (IPS) have been proposed in order to overcome this shortcoming and extend this valuable service to indoor navigation and positioning. This paper proposes a simple, cost effective and easily configurable indoor navigation system with the help of an optical path following, unmanned ground vehicle (UGV) robot augmented by image processing and computer vision deep machine learning algorithms. The proposed system prototype is capable of navigating in a warehouse as an example of an indoor area, by tracking and following a predefined traced path that covers all inventory zones in a warehouse, through the usage of infrared reflective sensors that can detect black traced path lines on bright ground. As metionded before, this general navigation mechanism is augmented and enhanced by artificial intelligence (AI) computer vision tasks to be able to select the path to the required inventory zone as its destination, and locate the requested material within this inventory zone. The adopted AI computer vision tasks that are used in the proposed prototype are deep machine learning object recognition algorithms for path selection and quick response (QR) detection.

scholarly journals Radar and Visual Odometry Integrated System Aided Navigation for UAVS in GNSS Denied Environment

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2776 ◽  
Author(s):  
Mostafa Mostafa ◽  
Shady Zahran ◽  
Adel Moussa ◽  
Naser El-Sheimy ◽  
Abu Sesay
Keyword(s):  
Navigation System ◽  
Visual Odometry ◽  
Satellite System ◽  
Integrated System ◽  
Measurement Unit ◽  
Integrated Navigation ◽  
Positioning Accuracy ◽  
Integrated Navigation System ◽  
Gnss Measurements ◽  
Global Navigation Satellite

Drones are becoming increasingly significant for vast applications, such as firefighting, and rescue. While flying in challenging environments, reliable Global Navigation Satellite System (GNSS) measurements cannot be guaranteed all the time, and the Inertial Navigation System (INS) navigation solution will deteriorate dramatically. Although different aiding sensors, such as cameras, are proposed to reduce the effect of these drift errors, the positioning accuracy by using these techniques is still affected by some challenges, such as the lack of the observed features, inconsistent matches, illumination, and environmental conditions. This paper presents an integrated navigation system for Unmanned Aerial Vehicles (UAVs) in GNSS denied environments based on a Radar Odometry (RO) and an enhanced Visual Odometry (VO) to handle such challenges since the radar is immune against these issues. The estimated forward velocities of a vehicle from both the RO and the enhanced VO are fused with the Inertial Measurement Unit (IMU), barometer, and magnetometer measurements via an Extended Kalman Filter (EKF) to enhance the navigation accuracy during GNSS signal outages. The RO and VO are integrated into one integrated system to help overcome their limitations, since the RO measurements are affected while flying over non-flat terrain. Therefore, the integration of the VO is important in such scenarios. The experimental results demonstrate the proposed system’s ability to significantly enhance the 3D positioning accuracy during the GNSS signal outage.

scholarly journals Developing an Error Map for Cognitive Navigation System

2021 ◽  
Vol 3 ◽  
Author(s):  
Atsushi Ito ◽  
Yosuke Nakamura ◽  
Yuko Hiramatsu ◽  
Tomoya Kitani ◽  
Hiroyuki Hatano
Keyword(s):  
Navigation System ◽  
Intelligent Transportation System ◽  
Low Cost ◽  
Satellite System ◽  
Navigation Systems ◽  
Positioning Accuracy ◽  
Gnss Positioning ◽  
Gnss Receivers ◽  
Global Navigation Satellite ◽  
User Friendly

Global Navigation Satellite System (GNSS) positioning is a widely used and a key intelligent transportation system (ITS) technology. An automotive navigation system is necessary when driving to an unfamiliar location. One difficulty regarding GNSS positioning occurs when an error is caused by various factors, which reduces the positioning accuracy and impacts the performance of applications such as navigation systems. However, there is no way for users to be aware of the magnitude of the error. In this paper, we propose a cognitive navigation system that uses an error map to provide users with information about the magnitude of errors to better understand the positioning accuracy. This technology can allow us to develop a new navigation system that offers a more user-friendly interface. We propose that the method will develop an error map by using two low-cost GNSS receivers to provide information about the magnitude of errors. We also recommend some applications that will work with the error map.

Indoor Navigation System of Omni-Directional Mobile Robot Based on Static Obstacles Avoidance

2020 ◽  
Vol 13 (1) ◽  
pp. 27
Author(s):  
Shaaban Ali Salman ◽  
Qais A. Khasawneh ◽  
Mohammad A. Jaradat ◽  
Mansour Y. Alramlawi
Keyword(s):  
Mobile Robot ◽  
Navigation System ◽  
Indoor Navigation ◽  
Indoor Navigation System
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