A Security System and Employees Performance Evaluation Using RFID Sensors and Fuzzy Logic

Morsi, Iman; Elsherief, Yasser; Zawawi, Amr El

doi:10.1109/computationworld.2009.112

Cited by 7 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The reason that fuzzy set theory is so well suited to widespread applications is that it generates results based on uncertain information. It has been applied and studied in several fields, including the cost-effectiveness of adding drugs to prescriptions (Cheng et al 2007), the selection of products according to a wide number of variables (Wang et al 2009), and to compare the time employees spent working or dawdling (Morsi et al 2009). In this research, fuzzy inference will be used to determine the dangerous degree of the user to a certain dangerous object or location.…”

Section: Related Workmentioning

confidence: 99%

“…There are a few commonly used methods for defuzzification: modified center average, center of sums, mean of maxima and center of gravity. Center of gravity is chosen for defuzzification of the output variable-the dangerous degree, because it has lower computational complexity and is easy to understand (Cheng et al 2007;Morsi et al 2009). The defuzzified dangerous degree can be found by the following equation.…”

Section: Fuzzy Inference For Danger Warningmentioning

confidence: 99%

See 1 more Smart Citation

Danger warning via fuzzy inference in an RFID-deployed environment

Hsu

Chen

Lin

et al. 2011

J Ambient Intell Human Comput

View full text Add to dashboard Cite

The population structure of some developed countries has been changed. Aged population with fewer kids is the main problem. To relieve the burden for caring elder people and kids at home, automatic mechanisms for homecare are needed. In this research, we focus on home safety with the elders and the kids. We aim at developing a RFID-based system that can detect the movement of the user at home. When the user approaches a dangerous location or a dangerous object, the system issues a warning to the caregiver to prevent possible dangerous situations. An active RFID tag is placed at each location and near each object. The user carries an RFID reader which detects the signal strengths of all tags and transmits them to the system in real time. The system issues a warning to the caregiver when the dangerous degree for a dangerous location/object is above the predefined level. A dangerous situation can be prevented if the caregiver watches out beforehand. The dangerous degree is determined through fuzzy inference on the user age and the signal strengths which reflect the distance of the user to a dangerous location/object. Fuzzy membership functions and fuzzy rules are defined in this system. A feedback mechanism is also designed to provide personalized services, which simply modifies the default fuzzy membership function of the corresponding location or object. Experimental results demonstrate that the system is promising in this application.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Fuzzy Inference For Danger Warningmentioning

confidence: 99%

Danger warning via fuzzy inference in an RFID-deployed environment

Hsu

Chen

Lin

et al. 2011

J Ambient Intell Human Comput

View full text Add to dashboard Cite

show abstract

“…Read rate of sensor tags is decided by the speed of tags fall into the downhole and turbulent eddies. Average read rate of each tag is 60 to 79 percent [7]. It can rise to 100 percent by placing at least 10 of the same tags into downhole.The new target tracking problems are often concerned about moving curve of the goal accompanied by a large number of monitoring information, such as ambient pressure, temperature, humidity, etc.RFID reader, which involved in RFID sensor networks, is responsible for detecting and deciding the location of current moving target, as well as the direction of movement.…”

Section: Research On the Sensor Tags Moving Target Tracking Technologymentioning

confidence: 99%

Research on Method for Monitoring the Pressure of Liquid Interface Based on Fuzzy Controller

Yin

Gan

Yang

2013

AMM

View full text Add to dashboard Cite

The monitor system of liquid interface is analyzed as a time-variant, non-linear and multi-disturbance complex system to keep track of RFID tags pose in the environment. In this work, with the input signal of dispersed pressure information, which is obtained by RFID tags from different density liquid, a decision method for the pressure of liquid interface is proposed base on fuzzy control. The simulation results are be tested by using MATLAB software. The simulation results can be shown from figure that output quantity depends on the input quantity of liquid pressure differential. It can be concluded that the fuzzy control theory is used to determine the liquid level pressure changes.

show abstract

“…The first model is the system security hierarchical evaluation model [8][9][10], which proposes an RFID system security assessment based on a fuzzy comprehensive method. This model divides the security levels into the object layer, criterion layer, and indicator layer.…”

Section: Phase Correlation Methodsmentioning

confidence: 99%

“…For instance, the atomic node possibility in Table 5 is calculated via variation coefficient method with formulas (6) to (9), considering the four related parameters that are level of attack cost, level of technical difficulty, level of attack discovered, and time cost. And according to formulas (10) to (12), the probability AND operation in Table 5 is represented as "×, " the probability OR operation is expressed as "⊕, " and the probability SAND operation is expressed as "⊗. "…”

Section: Attack Tree Sequencesmentioning

confidence: 99%

RFID Privacy Risk Evaluation Based on Synthetic Method of Extended Attack Tree and Information Feature Entropy

Chen

et al. 2015

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Evaluation of security risks in radio frequency identification (RFID) systems is a challenging problem in Internet of Things (IoT). This paper proposes an extended attack tree (EAT) model to identify RFID system's flaws and vulnerabilities. A corresponding formal description of the model is described which adds a probability SAND node together with the probability attribute of the node attack. In addition, we model the process of an RFID data privacy attack based on EAT, taking a sensitive information theft attack on an RFID tag as an example. To resolve the problem of assessing the risk probability of each node in EAT, we present the information feature entropy evaluation method for RFID privacy assessment. Finally, an evaluation is carried out to calculate the RFID privacy attack tree sequences and information feature entropy of the atomic node. Analysis shows that our scheme can calculate the overall risk evaluation result value for RFID privacy and comprehensively determine the risk of the weakest atomic node in RFID system.

show abstract

A Security System and Employees Performance Evaluation Using RFID Sensors and Fuzzy Logic

Cited by 7 publications

References 15 publications

Danger warning via fuzzy inference in an RFID-deployed environment

Danger warning via fuzzy inference in an RFID-deployed environment

Research on Method for Monitoring the Pressure of Liquid Interface Based on Fuzzy Controller

RFID Privacy Risk Evaluation Based on Synthetic Method of Extended Attack Tree and Information Feature Entropy

Contact Info

Product

Resources

About