LANDMARC: indoor location sensing using active RFID

Ni, Lionel M.; Liu, Yunhao; Lau, Yiu Cho; Patil, Ashwini

doi:10.1109/percom.2003.1192765

Cited by 1,494 publications

(348 citation statements)

References 4 publications

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“…In the active positioning system, active tags are mounted within the building while the reader is mobile. For example, in the works of Ni, Liu, Lau, and Patil (2003), C. Wang, Wu, and Tzeng (2007) and Daqiang Zhang et al (2016), an active positioning system with the active tags stationary and the reader mobile, was implemented. Because the active tags use batteries, they have wider coverage area, and hence fewer tags are used compared with the passive system (Ni et al, 2003;C.…”

Section: Rfid-based Positioning Systemmentioning

confidence: 99%

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

Sakpere

Oshin

Mlitwa

2017

SACJ

149

129

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The research and use of positioning and navigation technologies outdoors has seen a steady and exponential growth. Based on this success, there have been attempts to implement these technologies indoors, leading to numerous studies. Most of the algorithms, techniques and technologies used have been implemented outdoors. However, how they fare indoors is different altogether. Thus, several technologies have been proposed and implemented to improve positioning and navigation indoors. Among them are Infrared (IR), Ultrasound, Audible Sound, Magnetic, Optical and Vision, Radio Frequency (RF), Visible Light, Pedestrian Dead Reckoning (PDR)/Inertial Navigation System (INS) and Hybrid. The RF technologies include Bluetooth, Ultra-wideband (UWB), Wireless Sensor Network (WSN), Wireless Local Area Network (WLAN), Radio-Frequency Identification (RFID) and Near Field Communication (NFC). In addition, positioning techniques applied in indoor positioning systems include the signal properties and positioning algorithms. The prevalent signal properties are Angle of Arrival (AOA), Time of Arrival (TOA), Time Difference of Arrival (TDOA) and Received Signal Strength Indication (RSSI), while the positioning algorithms are Triangulation, Trilateration, Proximity and Scene Analysis/ Fingerprinting. This paper presents a state-of-the-art survey of indoor positioning and navigation systems and technologies, and their use in various scenarios. It analyses distinct positioning technology metrics such as accuracy, complexity, cost, privacy, scalability and usability. This paper has profound implications for future studies of positioning and navigation.

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Section: Rfid-based Positioning Systemmentioning

confidence: 99%

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

Sakpere

Oshin

Mlitwa

2017

SACJ

149

129

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“…Active RFID tags are battery-powered and have a reading range between 0 and 50 meters. Most commonly RFIDbased positioning is implemented using a system called LANDMARC [14]. LANDMARC is based on RSSI.…”

Section: Radio Frequency Identification (Rfid)mentioning

confidence: 99%

Localizing operators in the smart factory: A review of existing techniques and systems

Syberfeldt

Ayani

Holm

et al. 2016

2016 International Symposium on Flexible Automation (ISFA)

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The aim of this paper to give a comprehensive overview of existing techniques and state-of-the-art systems for indoor localization that could be adopted in smart factories of the future. We present different techniques for calculating the position of a moving object using signal transmission and signal measurement, and compare their advantages and disadvantages. The paper also includes a discussion of various localization systems available in the market and compares their most important features. It ends with a discussion of important issues to consider in future work in order to fully implement indoor, real-time localization of operators in the smart factory. INTRODUCTIONThe term "smart factory" refers to the fourth industrial revolution (also called Industry 4.0) and a groundbreaking technological evolution towards cyber-physical systems [1]. With smart factories comes a paradigm shift from centralized to decentralized production which is enabled through the concept of the "Internet-of-Things" [2]. The Internet-of-Things basically means that all objects in a factory (such as machines, tools, products, and human operators) are connected to the Internet and share information with each other [3]. When all objects are online, entirely new possibilities emerge for developing intelligent and adaptive IT-based support systems that can make shop floor operators more flexible and efficient. For example, instead of using traditional, static user interfaces it becomes possible to dynamically download the user interface from the Internet and adapt the information content based on the operator's location. This requires that the positions of all operators are tracked in real-time, which creates a requirement for efficient

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“…In principle, two groups of methods can be used for localisation: active methods, in which the person is tagged with a transponder [1,2,3,4] and passive methods, in which observations rely on the physical properties of the person [5,6,7,8,9].…”

Section: A Location and Identification Systemsmentioning

confidence: 99%