A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals

Castañón–Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Luis T.; Gaxiola–Pacheco, Carelia; Licea, Guillermo

doi:10.3390/s151229791

Cited by 12 publications

(6 citation statements)

References 23 publications

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“…The influence radius, r a is sufficient for most studies with acceptable results ranged 0.1 to 0.7 [48,50]. A lower r a generates more clusters, these clusters be closer to each other and this would result in less errors.…”

Section: Fuzzy Clustering Subractivementioning

confidence: 99%

An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus

et al. 2018

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Abstract:Optimal operation is an important aspect of energy efficiency that can be employed to reduce power consumption. In cooling systems, the chillers consume a large amount of electricity, especially if they are not optimally operated, therefore, they cannot produce the required or rated cooling load capacity. The objective of this paper is to improve coefficient of performance (COP) for the operation of chillers and to reduce power consumption. Two contributions in this work are: (1) the prediction of a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Fuzzy Clustering Subtractive (FCS), and (2) the classification and optimization of the predicted models by using an Accelerated Particle Swarm Optimization (APSO) algorithm. Particularly, in contribution (1), two models are developed to predict/assess power consumption and cooling load capacity. While in contribution (2), the predictive model's data obtained are used to classify the operating performance of the chiller and to optimize the model in order to reduce power consumption and cooling capacity. Therefore, data classification by APSO is used to enhance the coefficient of performance (COP). The proposed technique reduces the total power consumption by 33.2% and meets the cooling demand requirements. Also, it improves the cooling performance based on COP, thus resulting in a 15.95% increase in efficiency compared to the existing cooling system. The studied ANFIS-based FCS outperforms the ANFIS-based fuzzy C-means clustering in terms of the regression. Then, the algorithm-based classifier APSO has better results compared to the conventional particle swarm optimization (PSO). The data was acquired from the District Cooling System (DCS) at the Universiti Teknologi Petronas (UTP) campus in Malaysia.

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Section: Fuzzy Clustering Subractivementioning

confidence: 99%

An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus

et al. 2018

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“…Surprisingly, none of these databases produced results by utilizing type-2 fuzzy in the problem of localization (of course using a specific set of keywords for both). Some studies in the field have been reported in [131][132][133][134]. Thus, the absence of such notification is justified from different viewpoints.…”

Section: Parametric Measures and Evaluationsmentioning

confidence: 99%

A survey of fuzzy logic in wireless localization

Alakhras

Oussalah

Hussein

2020

J Wireless Com Network

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Positioning and location estimation of targets either for mobile or stationary nodes is very important, especially after the astonishing developments of the wired and/or wireless communications, as well as the popularity of handheld devices. To assist in accessing services or managing resources, numerous users, application developers, and service providers require accurate position information. Owing to the boom of multisensory systems, wireless technology, and autonomous systems, many positioning systems have been proposed. These positioning systems differ based on the adopted technology, type of sensory information, communication protocol, algorithm, and accuracy level. These different approaches impose a non-negligible amount of uncertainty and challenges; in such case, fuzzy-logic-based localization systems offer an attractive and feasible approach to overcome some of the reported challenges and handle uncertainties, depending on its proven mathematical framework for handling vagueness and uncertainty. Intuitively, fuzzy sets and fuzzy inference systems are initially intended to incorporate granularity and flexibility of human knowledge, which characterize complex system behaviors without explicitly requiring precise mathematical models or when a complete and exhaustive list of comprehending factors are ill known. This study demonstrates the benefits of fuzzy sets, fuzzy logic, and fuzzy inference systems in wireless positioning problems. Notably, as a way to benefit both the academic community and practitioners of system positioning, we review and investigate various fuzzy-related techniques and methodologies. To the best of our knowledge, this is the first comprehensive review that focuses solely on fuzzy-based positioning systems.

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“…However, PDR results estimated from inertial measurement unit (IMU) data have errors that are accumulated over time. Thus, many methods have been proposed for correcting PDR positioning errors, such as combining various sensors and wireless devices for error correction [2,3] and conducting algorithmic advancements for obtaining heading direction and step length estimations [9][10][11][12][13][14][15][16]. This study optimised the PDR algorithm by using the difference magnetic fingerprint between real-time measurement and magnetic fingerprint map data to calculate the weight then put in a particle filter method (in this study call modified particle filter) to get the position of user.…”

Section: Introductionmentioning

confidence: 99%

Combining a Modified Particle Filter Method and Indoor Magnetic Fingerprint Map to Assist Pedestrian Dead Reckoning for Indoor Positioning and Navigation

Ning

Chen

2019

Sensors

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Although advancement has been observed in global navigation satellite systems and these systems are widely used, they cannot provide effective navigation and positioning services in covered areas and areas that lack strong signals, such as indoor environments. Therefore, in recent years, indoor positioning technology has become the focus of research and development. The magnetic field of the Earth is quite stable in an open environment. Due to differences in building and internal structures, this type of three-dimensional vector magnetic field is widely available indoors for indoor positioning. A smartphone magnetometer was used in this study to collect magnetic field data for constructing indoor magnetic field maps. Moreover, an acceleration sensor and a gyroscope were used to identify the position of a mobile phone and detect the number of steps travelled by users with the phone. This study designed a procedure for measuring the step length of users. All obtained information was input into a pedestrian dead reckoning (PDR) algorithm for calculating the position of the device. The indoor positioning accuracy of the PDR algorithm was optimised using magnetic gradients of magnetic field maps with a modified particle filter algorithm. Experimental results reveal that the indoor positioning accuracy was between 0.6 and 0.8 m for a testing area that was 85 m long and 33 m wide. This study effectively improved the indoor positioning accuracy and efficiency by using the particle filter method in combination with the PDR algorithm with the magnetic fingerprint map.Sensors 2020, 20, 185 2 of 15 that provides all necessary factors. We should identify user requirements and combine different technologies to address those requirements with the lowest cost, highest range, and highest accuracy possible. Table 1 presents the current indoor positioning technologies [1], and Table 2 compares the more frequent use of wireless indoor position technologies [3].

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A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals

Cited by 12 publications

References 23 publications

An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus

An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus

A survey of fuzzy logic in wireless localization

Combining a Modified Particle Filter Method and Indoor Magnetic Fingerprint Map to Assist Pedestrian Dead Reckoning for Indoor Positioning and Navigation

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