A State-of-the-Art Survey of Indoor Positioning and Navigation Systems and Technologies

Sakpere, Wilson; Oshin, Michael Adeyeye; Mlitwa, Nhlanhla Bw

doi:10.18489/sacj.v29i3.452

Cited by 143 publications

(129 citation statements)

References 149 publications

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“…We searched for available MAT solutions to help PVI before and during the shopping process. We found that the shopping process is divided into two parts: the first part is how to prepare the shopping list to make shopping easy and fast; the second part is dealing with how to navigate and identify products during the shopping process, as shown in Figure 2 [38][39][40][41][42][43][44][45][46][47]. It is also shown in the figure that MATs during the shopping process are classified into three categories, based on the technology that was used: tag based, Computer Vision (CV) based, and hybrid systems.…”

Section: Mat Solutions For Pvi Shoppingmentioning

confidence: 99%

Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies

2019

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People with visual impairment face various difficulties in their daily activities in comparison to people without visual impairment. Much research has been done to find smart solutions using mobile devices to help people with visual impairment perform tasks like shopping. One of the most challenging tasks for researchers is to create a solution that offers a good quality of life for people with visual impairment. It is also essential to develop solutions that encourage people with visual impairment to participate in social life. This study provides an overview of the various technologies that have been developed in recent years to assist people with visual impairment in shopping tasks. It gives an introduction to the latest direction in this area, which will help developers to incorporate such solutions into their research.

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Section: Mat Solutions For Pvi Shoppingmentioning

confidence: 99%

Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies

2019

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“…The indoor positioning systems are based on various signal technologies, for example Radio-frequency Identification (RFID), radio-based Wireless Local Area Networks (WLAN), Ultra-Wideband (UWB), Infrared (IR), ultrasound or images (vision-based systems). An overview of different systems is given amongst others in Blankenbach (2017) or Sakpere, Adeyeye-Oshin, and Mlitwa (2017). For example, RFID is used for the position determination of objects or pedestrians (Ni et al 2003;Hightower, Want, and Borriello 2000;Xu et al 2017).…”

Section: State Of the Artmentioning

confidence: 99%

Indoor localization for pedestrians with real-time capability using multi-sensor smartphones

Ehrlich

Blankenbach

2019

Geo-spatial Information Science

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The localization of persons or objects usually refers to a position determined in a spatial reference system. Outdoors, this is usually accomplished with Global Navigation Satellite Systems (GNSS). However, the automatic positioning of people in GNSS-free environments, especially inside of buildings (indoors) poses a huge challenge. Indoors, satellite signals are attenuated, shielded or reflected by building components (e.g. walls or ceilings). For selected applications, the automatic indoor positioning is possible based on different technologies (e.g. WiFi, RFID, or UWB). However, a standard solution is still not available. Many indoor positioning systems are only suitable for specific applications or are deployed under certain conditions, e.g. additional infrastructures or sensor technologies. Smartphones, as popular cost-effective multi-sensor systems, is a promising indoor localization platform for the mass-market and is increasingly coming into focus. Today's devices are equipped with a variety of sensors that can be used for indoor positioning. In this contribution, an approach to smartphone-based pedestrian indoor localization is presented. The novelty of this approach refers to a holistic, real-time pedestrian localization inside of buildings based on multisensor smartphones and easy-to-install local positioning systems. For this purpose, the barometric altitude is estimated in order to derive the floor on which the user is located. The 2D position is determined subsequently using the principle of pedestrian dead reckoning based on user's movements extracted from the smartphone sensors. In order to minimize the strong error accumulation in the localization caused by various sensor errors, additional information is integrated into the position estimation. The building model is used to identify permissible (e.g. rooms, passageways) and impermissible (e.g. walls) building areas for the pedestrian. Several technologies contributing to higher precision and robustness are also included. For the fusion of different linear and non-linear data, an advanced algorithm based on the Sequential Monte Carlo method is presented.

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“…Various standards of the positioning technologies [6,[22][23][24], for example, the Received Signal Strength Indicator (RSSI), Channel State Information (CSI), fingerprinting/scene analysis, Angle of Arrival (AoA), Time of Arrival (ToA), Time Difference of Arrival (TDoA), Return Time of Flight (RToF), and Phase of Arrival (PoA) of the received signal, have been proposed to enhance the indoor positioning accuracy. We adapted from [6,25,26] to summarize the signal properties, as shown in Table 1.…”

Section: A Comparison Of the Radio Frequency (Rf-based) Indoor Positimentioning

confidence: 99%

Developing a BLE Beacon-Based Location System Using Location Fingerprint Positioning for Smart Home Power Management

Chan

et al. 2018

Energies

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In recent years, smart homes have begun to use various sensors to detect the location of users indoors. However, such sensors may not be stable, resulting in high detection error rates. Thus, how to improve indoor positioning accuracy has become an important topic. This study explored Bluetooth Low Energy (BLE) Beacon indoor positioning for smart home power management. A novel system framework using BLE Beacon was proposed to detect the user location, and to perform power management in the home through a mobile device application. Since the BLE Beacon may produce a multipath effect, this study used the positioning algorithm and hardware configuration to reduce the error rate. Location fingerprint positioning algorithm and filter modification were used to establish a positioning method for facilitating deployment, and to reduce the required computing resources. The experiments included an observation of the Received Signal Strength Indicators (RSSI) and selecting filters and a discussion of the relationship between the characteristics of the BLE Beacon signal accuracy and the number of the BLE Beacons deployed in the observation space. The BLE Beacon multilateration positioning was combined with the In-Snergy intelligent energy management system for smart home power management. The contribution of this study is to allow users to enjoy smart home services based on their location within the home using a mobile device application.

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A State-of-the-Art Survey of Indoor Positioning and Navigation Systems and Technologies

Cited by 143 publications

References 149 publications

Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies

Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies

Indoor localization for pedestrians with real-time capability using multi-sensor smartphones

Developing a BLE Beacon-Based Location System Using Location Fingerprint Positioning for Smart Home Power Management

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