scholarly journals Start from Scratch: A Crowdsourcing-Based Data Fusion Approach to Support Location-Aware Applications

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4518 ◽  
Author(s):  
Yonghang Jiang ◽  
Bingyi Liu ◽  
Ze Wang ◽  
Xiaoquan Yi
Keyword(s):  
Indoor Localization ◽  
Daily Lives ◽  
Indoor Location ◽  
Sensory Data ◽  
Location Aware ◽  
Multiple Dimensions ◽  
Crowdsourced Data ◽  
Data Fusing ◽  
The Internet Of Things ◽  
Fusion Approach

As one of the most important breakthroughs for modern transportation, the indoor location-based technology has been gradually penetrating into our daily lives and underlines the foundation of the Internet of Things (IoT). To improve the positioning accuracy and efficiency, crowdsourcing has been widely applied in indoor localization in recent years. However, the crowdsourced data can hardly be fused easily to enable usable applications for the reason that the data are collected by different users, in different locations, at different times, with different noises and distortions. Although different data fusing methods have been implemented in different crowdsourcing services, we find that they may not fully leverage the data collected from multiple dimensions that can potentially lead to a better fusion results. In order to address this problem, we propose a more general solution, which can fuse the multi-dimensional crowdsourced data together and align them with the consistent time and location stamps, by using the features of the sensory data only, and thus build high quality crowdsourcing services from the raw data samplings collected from the environment. Finally, we conduct extensive evaluations and experiments using different commercial devices to validate the effectiveness of the method we proposed.

A Location-Aware Architecture for an IoT-Based Smart Museum

2020 ◽  
pp. 413-432
Author(s):  
Giuseppe Del Fiore ◽  
Luca Mainetti ◽  
Vincenzo Mighali ◽  
Luigi Patrono ◽  
Stefano Alletto ◽  
...  
Keyword(s):  
Internet Of Things ◽  
User Experience ◽  
Image Recognition ◽  
Innovation Process ◽  
Modern Society ◽  
The Internet ◽  
Indoor Location ◽  
Location Aware ◽  
Art And Culture ◽  
The Internet Of Things

The Internet of Things, whose main goal is to automatically predict users' desires, can find very interesting opportunities in the art and culture field, as the tourism is one of the main driving engines of the modern society. Currently, the innovation process in this field is growing at a slower pace, so the cultural heritage is a prerogative of a restricted category of users. To address this issue, a significant technological improvement is necessary in the culture-dedicated locations, which do not usually allow the installation of hardware infrastructures. In this paper, we design and validate a no-invasive indoor location-aware architecture able to enhance the user experience in a museum. The system relies on the user's smartphone and a wearable device (with image recognition and localization capabilities) to automatically deliver personalized cultural contents related to the observed artworks. The proposal was validated in the MUST museum in Lecce (Italy).

A Location-Aware Architecture for an IoT-Based Smart Museum

2016 ◽  
Vol 12 (2) ◽  
pp. 39-55 ◽  
Author(s):  
Giuseppe Del Fiore ◽  
Luca Mainetti ◽  
Vincenzo Mighali ◽  
Luigi Patrono ◽  
Stefano Alletto ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Image Recognition ◽  
Innovation Process ◽  
Modern Society ◽  
The Internet ◽  
Indoor Location ◽  
Location Aware ◽  
Technological Improvement ◽  
Art And Culture ◽  
The Internet Of Things

The Internet of Things, whose main goal is to automatically predict users' desires, can find very interesting opportunities in the art and culture field, as the tourism is one of the main driving engines of the modern society. Currently, the innovation process in this field is growing at a slower pace, so the cultural heritage is a prerogative of a restricted category of users. To address this issue, a significant technological improvement is necessary in the culture-dedicated locations, which do not usually allow the installation of hardware infrastructures. In this paper, we design and validate a no-invasive indoor location-aware architecture able to enhance the user experience in a museum. The system relies on the user's smartphone and a wearable device (with image recognition and localization capabilities) to automatically deliver personalized cultural contents related to the observed artworks. The proposal was validated in the MUST museum in Lecce (Italy).

scholarly journals Privacy vs. Reward in Indoor Location-Based Services

2016 ◽  
Vol 2016 (4) ◽  
pp. 102-122 ◽  
Author(s):  
Kassem Fawaz ◽  
Kyu-Han Kim ◽  
Kang G. Shin
Keyword(s):  
Location Privacy ◽  
Indoor Localization ◽  
Service Providers ◽  
Location Based Services ◽  
Location Information ◽  
Privacy Concerns ◽  
Indoor Location ◽  
Location Data ◽  
Personalized Services ◽  
Privacy Risks

AbstractWith the advance of indoor localization technology, indoor location-based services (ILBS) are gaining popularity. They, however, accompany privacy concerns. ILBS providers track the users’ mobility to learn more about their behavior, and then provide them with improved and personalized services. Our survey of 200 individuals highlighted their concerns about this tracking for potential leakage of their personal/private traits, but also showed their willingness to accept reduced tracking for improved service. In this paper, we propose PR-LBS (Privacy vs. Reward for Location-Based Service), a system that addresses these seemingly conflicting requirements by balancing the users’ privacy concerns and the benefits of sharing location information in indoor location tracking environments. PR-LBS relies on a novel location-privacy criterion to quantify the privacy risks pertaining to sharing indoor location information. It also employs a repeated play model to ensure that the received service is proportionate to the privacy risk. We implement and evaluate PR-LBS extensively with various real-world user mobility traces. Results show that PR-LBS has low overhead, protects the users’ privacy, and makes a good tradeoff between the quality of service for the users and the utility of shared location data for service providers.

An Indoor Location-Aware System for an IoT-Based Smart Museum

2016 ◽  
Vol 3 (2) ◽  
pp. 244-253 ◽  
Author(s):  
Stefano Alletto ◽  
Rita Cucchiara ◽  
Giuseppe Del Fiore ◽  
Luca Mainetti ◽  
Vincenzo Mighali ◽  
...  
Keyword(s):  
Indoor Location ◽  
Location Aware

Deep learning approach for UHF RFID-based indoor localization

2021 ◽  
pp. 1-13
Author(s):  
Haishu Ma ◽  
Zongzheng Ma ◽  
Lixia Li ◽  
Ya Gao
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Estimation Error ◽  
Research Direction ◽  
Linear Interpolation ◽  
Linear Mapping ◽  
Uhf Rfid ◽  
Indoor Location ◽  
Main Research

Due to the proliferation of the IoT devices, indoor location-based service is bringing huge business values and potentials. The positioning accuracy is restricted by the variability and complexity of the indoor environment. Radio Frequency Identification (RFID), as a key technology of the Internet of Things, has became the main research direction in the field of indoor positioning because of its non-contact, non-line-of-sight and strong anti-interference abilities. This paper proposes the deep leaning approach for RFID based indoor localization. Since the measured Received Signal Strength Indicator (RSSI) can be influenced by many indoor environment factors, Kalman filter is applied to erase the fluctuation. Furthermore, linear interpolation is adopted to increase the density of the reference tags. In order to improve the processing ability of the fingerprint database, deep neural network is adopted together with the fingerprinting method to optimize the non-linear mapping between fingerprints and indoor coordinates. The experimental results show that the proposed method achieves high accuracy with a mean estimation error of 0.347 m.

scholarly journals Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach

Sensors ◽  
2017 ◽  
Vol 17 (12) ◽  
pp. 2847 ◽  
Author(s):  
Mengyun Liu ◽  
Ruizhi Chen ◽  
Deren Li ◽  
Yujin Chen ◽  
Guangyi Guo ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Indoor Localization ◽  
Scene Recognition ◽  
Fusion Approach

Indoor localization and navigation using smartphone sensory data

2017 ◽  
Vol 265 (2) ◽  
pp. 187-204 ◽  
Author(s):  
Hui-Huang Hsu ◽  
Jung-Kuei Chang ◽  
Wei-Jan Peng ◽  
Timothy K. Shih ◽  
Tun-Wen Pai ◽  
...  
Keyword(s):  
Indoor Localization ◽  
Sensory Data

scholarly journals Research of long radius technology for implementation of solutions of the Іnternet of things

Connectivity ◽  
2020 ◽  
Vol 148 (6) ◽  
Author(s):  
S. A. Zhezhkun ◽  
◽  
L. B. Veksler ◽  
S. M. Brezitsʹkyy ◽  
B. O. Tarasyuk
Keyword(s):  
Internet Of Things ◽  
Third Party ◽  
Security And Privacy ◽  
The Internet ◽  
Daily Lives ◽  
Advantages And Disadvantages ◽  
Iot Applications ◽  
Security Properties ◽  
Technical Features ◽  
The Internet Of Things

This article focuses on the analysis of promising technologies for long-range traffic transmission for the implementation of the Internet of Things. The result of the review of technical features of technologies, their advantages and disadvantages is given. A comparative analysis was performed. An analysis is made that in the future heterogeneous structures based on the integration of many used radio technologies will play a crucial role in the implementation of fifth generation networks and systems. The Internet of Things (IoT) is heavily affecting our daily lives in many domains, ranging from tiny wearable devices to large industrial systems. Consequently, a wide variety of IoT applications have been developed and deployed using different IoT frameworks. An IoT framework is a set of guiding rules, protocols, and standards which simplify the implementation of IoT applications. The success of these applications mainly depends on the ecosystem characteristics of the IoT framework, with the emphasis on the security mechanisms employed in it, where issues related to security and privacy are pivotal. In this paper, we survey the security of the main IoT frameworks, a total of 8 frameworks are considered. For each framework, we clarify the proposed architecture, the essentials of developing third-party smart apps, the compatible hardware, and the security features. Comparing security architectures shows that the same standards used for securing communications, whereas different methodologies followed for providing other security properties.

scholarly journals Thing Theory

2017 ◽  
pp. 249-265 ◽  
Author(s):  
Sally A. Applin ◽  
Michael D. Fischer
Keyword(s):  
Big Data ◽  
Communication Technologies ◽  
Social Awareness ◽  
The Internet ◽  
Smart Environment ◽  
Thing Theory ◽  
Making Sense ◽  
Location Aware ◽  
Resultant Data ◽  
The Internet Of Things

As healthcare professionals and others embrace the Internet of Things (IoT) and smart environment paradigms, developers will bear the brunt of constructing the IT relationships within these, making sense of the big data produced as a result, and managing the relationships between people and technologies. This chapter explores how PolySocial Reality (PoSR), a framework for representing how people, devices and communication technologies interact, can be applied to developing use cases combining IoT and smart environment paradigms, giving special consideration to the nature of location-aware messaging from sensors and the resultant data collection in a healthcare environment. Based on this discussion, the authors suggest ways to enable more robust intra-sensor messaging through leveraging social awareness by software agents applied in carefully considered healthcare contexts.

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