Order-of-Arrival of Tagged Objects

Bartoletti, Stefania; Decarli, Nicolò; Dardari, Davide; Chiani, Marco; Conti, Andrea

doi:10.1109/jrfid.2018.2881708

Cited by 6 publications

(5 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the online stage, the signal is received through the multipath channel as given by (1). We stack the received signals of N subcarriers and M antennas and express the multipath CFR as a vector form…”

Section: B Online Stage: Toa and Aoa Estimationmentioning

confidence: 99%

“…The increasing popularity of mobile devices, coupled with the rise of the Internet of Things (IoT), has resulted in the prevalence of location-based service (LBS) applications, e.g., emergency calls, navigation, object tracking, marketing, and a range of information services [1][2][3]. Global positioning system (GPS) is currently the de facto positioning technology, with approximately 10m accuracy in outdoor environments but its performance in indoor environments is severely degraded due to the lack of line-of-sight (LoS) of the satellites.…”

Section: Introductionmentioning

confidence: 99%

“…For most LBSs, the required indoor positioning accuracy is typically less than 3m, which is unfortunately very difficult to achieve by GPS. To overcome this problem, researchers have investigated many indoor positioning systems (IPSs) in recent years [1][2][3][4][5][6][7][8][9][10][11][12][13]. The considered media for IPSs include RF-based signals (e.g., 5G, Wi-Fi, Bluetooth, ZigBee, and LPWAN) [1,2,4] and non-RF-based signals (e.g., Li-Fi, optical camera communication, and light detection and ranging) [14,15].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Angle-of-Arrival Estimation With Practical Phone Antenna Configurations

Shih

Wen

Jin

et al. 2023

IEEE Internet Things J.

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With the advances in Internet of Things (IoT) and mobile connectivity, location-based services (LBSs) are increasingly popular and continue to enhance our experience. Multiple antennas have been pivotal for the provision of reliable wireless communications and high-resolution localization. However, in the real world, mobile handsets tend to have very limited space and the incorporation of multiple antennas hardly obeys the rule of half-wavelength separation between antenna elements, resulting in complex mutual coupling. More often than not, antennas are placed not to affect negatively the artistic design and handling of the device. The irregular 3D radiation pattern of each antenna element further impairs the capability of the antenna array for localization. In this paper, we propose a generic parametric model that can incorporate the actual antenna responses into the angleof-arrival (AoA) estimation. As a result, we present an efficient algorithm to enable 3D AoA estimation on mobile phones based on the proposed model, and test it on a 5G phone at a midband spectrum with 100MHz channel bandwidth. Our results reveal promising performance with over 90% scenarios where the AoA estimation errors are lower than 10 • on a mobile phone.

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Section: B Online Stage: Toa and Aoa Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Angle-of-Arrival Estimation With Practical Phone Antenna Configurations

Shih

Wen

Jin

et al. 2023

IEEE Internet Things J.

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“…Generally, RFID technology consists of a reader, tags, and a computer [2,26]. RFID technologies are based on an active tag technology [28,127] and passive tag technology [25,124,128,129]. Active tags have a larger detecting range using high power consumption and higher cost, although the passive tags are appropriate for short distance static point location, and only applicable for a small space [38].…”

Section: Rfid Technologymentioning

confidence: 99%

Review of Indoor Positioning: Radio Wave Technology

et al. 2020

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The indoor positioning system (IPS) is becoming increasing important in accurately determining the locations of objects by the utilization of micro-electro-mechanical-systems (MEMS) involving smartphone sensors, embedded sources, mapping localizations, and wireless communication networks. Generally, a global positioning system (GPS) may not be effective in servicing the reality of a complex indoor environment, due to the limitations of the line-of-sight (LoS) path from the satellite. Different techniques have been used in indoor localization services (ILSs) in order to solve particular issues, such as multipath environments, the energy inefficiency of long-term battery usage, intensive labour and the resources of offline information collection and the estimation of accumulated positioning errors. Moreover, advanced algorithms, machine learning, and valuable algorithms have given rise to effective ways in determining indoor locations. This paper presents a comprehensive review on the positioning algorithms for indoors, based on advances reported in radio wave, infrared, visible light, sound, and magnetic field technologies. The traditional ranging parameters in addition to advanced parameters such as channel state information (CSI), reference signal received power (RSRP), and reference signal received quality (RSRQ) are also presented for distance estimation in localization systems. In summary, the recent advanced algorithms can offer precise positioning behaviour for an unknown environment in indoor locations.

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“…Thanks to the current advances in RFID-based automatic monitoring of objects [16] and even of people [17], the authors recently proposed the use of RFID technology for monitoring the ripening of avocado packaged for final customer distribution in stores [18]. The system comprises intelligent packaging integrating a single passive UHF RFID tag and a customized reader.…”

Section: Introductionmentioning

confidence: 99%

Automatic Monitoring of Fruit Ripening Rooms by UHF RFID Sensor Network and Machine Learning

Occhiuzzi,

Camera,

D'Orazio

et al. 2022

Preprint

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Accelerated ripening through the exposure of fruits to controlled environmental conditions and gases is nowadays one of the most assessed food technologies, especially for climacteric and exotic products. However, a fine granularity control of the process and consequently of the quality of the goods is still missing, so the management of the ripening rooms is mainly based on qualitative estimations only. Following the modern paradigms of Industry 4.0, this contribution proposes a nondestructive RFID-based system for the automatic evaluation of the live ripening of avocados. The system, coupled with a properly trained automatic classification algorithm based on Support Vector Machines (SVMs), can discriminate the stage of ripening with an accuracy greater than 85%.

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Order-of-Arrival of Tagged Objects

Cited by 6 publications

References 46 publications

Angle-of-Arrival Estimation With Practical Phone Antenna Configurations

Angle-of-Arrival Estimation With Practical Phone Antenna Configurations

Review of Indoor Positioning: Radio Wave Technology

Automatic Monitoring of Fruit Ripening Rooms by UHF RFID Sensor Network and Machine Learning

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