A comprehensive multi-factor analysis on RFID localization capability

Zhou, Jian; Shi, Jing

doi:10.1016/j.aei.2010.05.006

Cited by 53 publications

(36 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Detection technologies typically include cameras [47], CO2 sensors [48], cellular phone control-channel traffic sensors [49], humidity sensors [50], infrared (IR) sensors [51], light sensors [52], motion sensors [53], radio frequency identification (RFID) [54], sound sensors [55], switch door sensors [56], telephone sensors [57], temperature sensors [50], ultra-wideband (UWB) [58], wireless sensor networks (WSN) [59], and Wi-Fi infrastructures [60]. These detection technologies can be divided to two main groups [61]: (1) precise technologies with incomplete coverage (e.g., cameras); and (2) imprecise technologies with full coverage (e.g., Wi-Fi infrastructures).…”

Section: Monitoring Occupant-specific Energy Consumptionmentioning

confidence: 99%

A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings

2015

View full text Add to dashboard Cite

Abstract:Buildings currently account for 30-40 percent of total global energy consumption. In particular, commercial buildings are responsible for about 12 percent of global energy use and 21 percent of the United States' energy use, and the energy demand of this sector continues to grow faster than other sectors. This increasing rate therefore raises a critical concern about improving the energy performance of commercial buildings. Recently, researchers have investigated ways in which understanding and improving occupants' energy-consuming behaviors could function as a cost-effective approach to decreasing commercial buildings' energy demands. The objective of this paper is to present a detailed, up-to-date review of various algorithms, models, and techniques employed in the pursuit of understanding and improving occupants' energy-use behaviors in commercial buildings. Previous related studies are introduced and three main approaches are identified: (1) monitoring occupant-specific energy consumption; (2) Simulating occupant energy consumption behavior; and (3) improving occupant energy consumption behavior. The first approach employs intrusive and non-intrusive load-monitoring techniques to estimate the energy use of individual occupants. The second approach models diverse characteristics related to occupants' energy-consuming behaviors in order to assess and predict such characteristics' impacts on the energy performance of commercial buildings; this approach mostly utilizes agent-based modeling techniques to simulate actions and interactions between occupants and their built environment. The third approach employs occupancy-focused interventions to change OPEN ACCESSEnergies 2015, 8 10997 occupants' energy-use characteristics. Based on the detailed review of each approach, critical issues and current gaps in knowledge in the existing literature are discussed, and directions for future research opportunities in this field are provided.

show abstract

Section: Monitoring Occupant-specific Energy Consumptionmentioning

confidence: 99%

A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings

2015

View full text Add to dashboard Cite

show abstract

“…[9] is employed adaptive k value to enhance positioning accuracy. [10] gives an comprehensive analysis of accuracy-influence factors. This paper presents the state-of-art technology of RFID location algorithm and some improvements.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fitting Reference Frame for 2-D Indoor Localization Based on RFID

Yang¹,

Chen²

2014

IJET

View full text Add to dashboard Cite

Abstract-Indoor localization information is important to many different industries. Ever-rising demand from both custom and supplier pose great challenge for indoor localization technology. The emergence of rapid development of Radio Frequency Identification (RFID) technology enriches indoor positioning methodology. Traditional indoor localization algorithm mainly based on the signal propagation property. Among all of positioning algorithm, LANDMARC is most promising one but still has some limitation such as multipath effect, noise form environment and quantity constrain of tags. This paper identifies previous RFID-based indoor localization algorithm and proposes a new algorithm aiming at delivering above limitation to estimate objective position indoor environment. It use RSS propagation curve to obtain RSS value of virtual reference tag, and then estimate target tags position. To evaluate its performance, a comparison between LANDMARC and proposed algorithm was conducted. Experiment result show proposed algorithm is more accurate than LANDMARC.

show abstract

“…Here can be fixed at 4 dB, which is the average reported standard deviations for wireless communications. And the path loss exponent is usually between 1.6 and 6.5 based on actual measurement [20]. Until now, the measurement model of RFID tracking system was obtained.…”

Section: System Model With the Irregularly Sampled Measurementsmentioning

confidence: 99%

“…where 0 is the close-in reference distance, ( 0 ) is the RSSI in dBm units with the reference distance 0 , and is the path loss exponent [20]. Let x,ẋ , andẍ be the target location, velocity, and acceleration along the horizontal axis, while y,ẏ , andÿ are the corresponding variables along the longitudinal axis.…”

Section: System Model With the Irregularly Sampled Measurementsmentioning

confidence: 99%

Parallel Irregular Fusion Estimation Based on Nonlinear Filter for Indoor RFID Tracking System

Jin

Dou

et al. 2016

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

In practical RFID tracking systems, usually it is impossible that the readers are placed right with a "grid" structure, so effective estimation method is required to obtain the accurate trajectory. Due to the data-driven mechanism, measurement of RFID system is sampled irregularly; therefore the traditional recursive estimation may fail from to + 1 sampling point. Moreover, because the distribution density of the readers is nonuniform and multiple measurements might be implemented simultaneously, fusion of estimations also needs to be considered. In this paper, an irregular estimation strategy with parallel structure was developed, where the dynamic model update and states fusion estimation were processed synchronously to achieve real-time indoor RFID tracking. Two nonlinear estimation methods were proposed based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF), respectively. The tracking performances were compared, and the simulation results show that the developed UKF method got lower covariance in indoor RFID tracking while the EKF one cost less calculating time.

show abstract

A comprehensive multi-factor analysis on RFID localization capability

Cited by 53 publications

References 25 publications

A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings

A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings

Adaptive Fitting Reference Frame for 2-D Indoor Localization Based on RFID

Parallel Irregular Fusion Estimation Based on Nonlinear Filter for Indoor RFID Tracking System

Contact Info

Product

Resources

About