The Use of Fuzzy Logic for Online Monitoring of Manufacturing Machine: An Intelligent System

2017 ◽  
Vol 2 (11) ◽  
pp. 31-39 ◽  
Author(s):  
Ashner Gerald P. Novilla ◽  
August Anthony N. Balute ◽  
Dennis B. Gonzales
Keyword(s):  
Fuzzy Logic ◽  
Embedded System ◽  
Monitoring System ◽  
Intelligent System ◽  
Human Labor ◽  
The Status ◽  
Fuzzy Logic Approach ◽  
Iot Devices ◽  
Mean Time ◽  
Manufacturing Machine

Internet of Things (IoT) has positioned itself at the front of rapid technological advancements in order to lessen human labor. The concept of making the world smart arises from the basis that “things” can be connected using the Internet. In this paper, the researchers will be describing an effective implementation of an intelligent monitoring system for manufacturing machine unit which is used in industry environment. The propose system design can be installed in manufacturing machines in order to solve management problems, maintenance, shortens the mean time to repair and predict mean time to fail. The researchers have designed a system based on internet of thing for monitoring using the fuzzy logic approach. It consists of monitoring the normal activities of the manufacturing machines in order to build a reference of its condition; then a real-time monitoring and analysis of gathered data from the sensors is accomplished. The status is carried out using a Fuzzy Logic based network. It will give the users the current activity of the manufacturing machine and will also provide information about health status. This system had been incorporated through internet using host, network, Ethernet module, embedded system gateway, sensors, microcontroller unit (MCU) and other components. This paper discusses how monitoring system can be implemented and how the use of cloud computing technology along with IoT devices can be used so that the data collected by these devices can be safely stored, monitored and analyzed.

scholarly journals GPS Data Correction Based on Fuzzy Logic for Tracking Land Vehicles

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2818
Author(s):  
Pedro J. Correa-Caicedo ◽  
Horacio Rostro-González ◽  
Martin A. Rodriguez-Licea ◽  
Óscar Octavio Gutiérrez-Frías ◽  
Carlos Alonso Herrera-Ramírez ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Embedded System ◽  
Fuzzy Systems ◽  
Intelligent System ◽  
Unscented Kalman Filter ◽  
The Other ◽  
Linear Functions ◽  
Sensor Technology ◽  
Raspberry Pi ◽  
Land Vehicles

GPS sensors are widely used to know a vehicle’s location and to track its route. Although GPS sensor technology is advancing, they present systematic failures depending on the environmental conditions to which they are subjected. To tackle this problem, we propose an intelligent system based on fuzzy logic, which takes the information from the sensors and correct the vehicle’s absolute position according to its latitude and longitude. This correction is performed by two fuzzy systems, one to correct the latitude and the other to correct the longitude, which are trained using the MATLAB ANFIS tool. The positioning correction system is trained and tested with two different datasets. One of them collected with a Pmod GPS sensor and the other a public dataset, which was taken from routes in Brazil. To compare our proposal, an unscented Kalman filter (UKF) was implemented. The main finding is that the proposed fuzzy systems achieve a performance of 69.2% higher than the UKF. Furthermore, fuzzy systems are suitable to implement in an embedded system such as the Raspberry Pi 4. Another finding is that the logical operations facilitate the creation of non-linear functions because of the ‘if else’ structure. Finally, the existence justification of each fuzzy system section is easy to understand.

Large Apparatus and Tele-Monitoring System Based on Embedded System

2014 ◽  
Vol 912-914 ◽  
pp. 1283-1286
Author(s):  
Zhi Ping Zhang ◽  
Chang Xu Jiang ◽  
Rong Nian Tang
Keyword(s):  
Embedded System ◽  
Mobile Phone ◽  
Monitoring System ◽  
Large Scale ◽  
Laboratory Staff ◽  
The Status ◽  
Long Time ◽  
The Embedded System ◽  
And Control ◽  
Tele Monitoring

Large-scale instrumentation equipment usually runs a long time, sometimes even runs all night long. If not arrange the laboratory staff guard it, when equipment fails, it can only be allowed to develop, and in severe cases can cause the large instrument and equipment damage; To address this issue, propose a large apparatus and tele-monitoring system based on embedded system and through the HD camera collects the status of the indicator lamps of the large instrument, and through the algorithms identification of the embedded system, and the JPEG encoding and control, and using GPRS module sends images to the experimenter's mobile phone to achieve the remote monitoring of equipment; And researchers can the control the system via mobile phone to send instructions to achieve the remote control.

scholarly journals Context-Aware Winter Sports Based on Multivariate Sequence Learning

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3296 ◽  
Author(s):  
Byung-Kil Han ◽  
Je-Kwang Ryu ◽  
Seung-Chan Kim
Keyword(s):  
Neural Network ◽  
Embedded System ◽  
Short Term Memory ◽  
Intelligent System ◽  
Multivariate Time Series ◽  
Ground Surface ◽  
Physical Interaction ◽  
Winter Sports ◽  
The Status ◽  
Gated Recurrent Units

In this paper, we present an intelligent system that is capable of estimating the status of a player engaging in winter activities based on the sequence analysis of multivariate time-series sensor signals. Among the winter activities, this paper mainly focuses on downhill winter sports such as alpine skiing and snowboarding. Assuming that the mechanical vibrations generated by physical interaction between the ground surface and ski/snowboard in motion can describe the ground conditions and playing contexts, we utilize inertial and vibration signals to categorize the motion context. For example, the proposed system estimates whether the player is sitting on a ski lift or standing on the escalator, or skiing on wet or snowy ground, etc. To measure the movement of a player during a game or on the move, we develop a custom embedded system comprising a motion sensor and piezo transducer. The captured multivariate sequence signals are then trained in a supervised fashion. We adopt artificial neural network approaches (e.g., 1D convolutional neural network, and gated recurrent neural networks, such as long short-term memory and gated recurrent units). The experimental results validate the feasibility of the proposed approach.

scholarly journals A Fuzzy Logic Based Intelligent System for Measuring Customer Loyalty and Decision Making

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 761 ◽  
Author(s):  
Usman Ghani ◽  
Imran Bajwa ◽  
Aimen Ashfaq
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Intelligent System ◽  
Online Reviews ◽  
Data Set ◽  
Specific Product ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Customer's Loyalty ◽  
Intelligent Approach

In this paper, an intelligent approach is presented to measure customers’ loyalty to a specific product and assist new customers regarding a product’s key features. Our approach uses an aggregated sentiment score of a set of reviews in a dataset and then uses a fuzzy logic model to measure customer’s loyalty to a product. Our approach uses a novel idea of measuring customer’s loyalty to a product and can assist a new customer to take a decision about a particular product considering its various features and reviews of previous customers. In this study, we use a large sized data set of online reviews of customers from Amazon.com to test the performance of the customer’s reviews. The proposed approach pre-processes the input text via tokenization, Lemmatization and removal of stop words and then applies fuzzy logic approach to take decisions. To find similarity and relevance to a topic, various libraries and API are used in this work such as SentiWordNet, Stanford Core NLP, etc. The approach utilized focuses on identifying polarity of the reviews that may be positive, negative and neutral. To find customer’s loyalty and help in decision making, the fuzzy logic approach is applied using a set of membership functions and rule-based system of fuzzy sets that classify data in various types of loyalty. The implementation of the approach provides high accuracy of 94% of correct loyalty to the e-commerce products that outperforms the previous approaches.

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