Indoor Positioning Using WiFi RSSI Trilateration and INS Sensor Fusion System Simulation

El-Naggar, Abdelrahman; Wassal, Amr G.; Sharaf, K.

doi:10.1145/3365245.3365261

Cited by 13 publications

(12 citation statements)

References 12 publications

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“…Cellular, GNSS, Thermal [147], [148], [184] Traffic Sickness trend prediction Predict sickness trends in specific areas AI [223] services to enable social distancing. The most common and easiest way for indoor positioning is to calculate the user's location based on the RSSI of the received signals from the user device [54], [55]. However, the accuracy of this solution much depends on the propagation model.…”

Section: ) Crowd Detectionmentioning

confidence: 99%

“…After that, the user's location will be derived by using the trilateration mechanism. Differently, the authors in [55] propose to adopt the inertial navigation system (INS) to significantly increase the accuracy of conventional RSSI-based methods. The key idea of this solution is using a Kalman filter to combine and fill the signal database with the INS data.…”

Section: The Key Idea Of This Solution Is Continuously Determiningmentioning

confidence: 99%

“…Second, with recent advances in Wi-Fi-based indoor positioning, Wi-Fi can provide reliable and precise location services to enable social distancing. The most common and easiest way for indoor positioning is to calculate the user’s location based on the RSSI of the received signals from the user device [53] , [54] . However, the accuracy of this solution much depends on the propagation model.…”

Section: Wireless Technologies For Social Distancingmentioning

confidence: 99%

See 2 more Smart Citations

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies

et al. 2020

View full text Add to dashboard Cite

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effective and can be widely adopted in practice to keep distance, encourage, and enforce social distancing in general. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II [1] surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacypreserving, scheduling, and incentive mechanisms) in implementing social distancing in practice.

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Section: ) Crowd Detectionmentioning

confidence: 99%

Section: The Key Idea Of This Solution Is Continuously Determiningmentioning

confidence: 99%

Section: Wireless Technologies For Social Distancingmentioning

confidence: 99%

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A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies

et al. 2020

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“…Nowadays, more sophisticated software-based hybrid approaches can also offer better accuracy [25], [26]. For example, the use of Kalman Filters can reduce time delays upon location fingerprinting for point data, collection in the presence of WiFi network where GPS fails to provide adequate service [27], [28]. Particle filters, on the other hand, can be used for , positioning based on cellular phone measurements for integrated navigation in aircraft and cars [29].…”

Section: Wifi Based Positioningmentioning

confidence: 99%

COVID-19 Contact Tracing: Challenges and Future Directions

et al. 2020

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Contact tracing has become a vital tool for public health officials to effectively combat the spread of new diseases, such as the novel coronavirus disease COVID-19. Contact tracing is not new to epidemiologist rather, it used manual or semi-manual approaches that are incredibly time-consuming, costly and inefficient. It mostly relies on human memory while scalability is a significant challenge in tackling pandemics. The unprecedented health and socio-economic impacts led researchers and practitioners around the world to search for technology-based approaches for providing scalable and timely answers. Smartphones and associated digital technologies have the potential to provide a better approach due to their high level of penetration, coupled with mobility. While data-driven solutions are extremely powerful, the fear among citizens is that information like location or proximity associated with other personal data can be weaponised by the states to enforce surveillance. Low adoption rate of such apps due to the lack of trust questioned the efficacy and demanded researchers to find innovative solution for building digital-trust, and appropriately balancing privacy and accuracy of data. In this paper, we have critically reviewed such protocols and apps to identify the strength and weakness of each approach. Finally, we have penned down our recommendations to make the future contact tracing mechanisms more universally inter-operable and privacy-preserving.

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“…Second, with recent advances in Wi-Fi based indoor positioning, Wi-Fi can provide reliable and precise location services to enable social distancing. The most common and easiest way for indoor positioning is calculating the user's location based on the RSSI of the received signals from the user device [41], [42].…”

Section: A Wi-fimentioning

confidence: 99%

Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey and Open Problems

Nguyen,

Saputra,

Van Huynh

et al. 2020

Preprint

View full text Add to dashboard Cite

Social distancing is crucial for preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the closely physical contact between people, we can reduce chances of catching the virus and spreading it to the community. This paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, AI can enable, encourage, and even enforce social distancing. To that end, we provide a fundamental background of social distancing including basic concepts, measurements, models and propose practical scenarios. We then discuss enabling wireless technologies which are especially effective and can be widely adopted in practice to keep distance and monitor people. After that, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we provide important open issues and challenges (e.g., privacy-preserving, cybersecurity) in implementing social distancing in practice.

show abstract

Indoor Positioning Using WiFi RSSI Trilateration and INS Sensor Fusion System Simulation

Cited by 13 publications

References 12 publications

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies

COVID-19 Contact Tracing: Challenges and Future Directions

Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey and Open Problems

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