Fuzzy logic monitoring and control of depth of anaesthesia

Internet of things (IoT) and fuzzy logic are very useful in increasing the efficiency and effectiveness of a system; this study applies both to the street lighting systems. The prototype of a street lighting control and monitoring system has been completed. The status of lights that are on or off and the value of the light intensity can be monitored by using IoT. The intensity of the light is fuzzy controlled by utilizing the presence of vehicles and pedestrians around the lights. The prototype is made with a scale against real conditions. Data is processed and transmitted using a microcontroller and Wi-Fi on the IoT module. Mobile applications have been used on smartphone interfaces to monitor and control lamps wherever they are connected to the Internet. Changes in the status of lights to turn on or off are done by the relay module. The fuzzy light intensity control system uses sensors and microcontrollers by utilizing the presence of vehicles and pedestrians around the lights. Performance evaluation has been carried out on a miniature street lighting with the results of monitoring and control following its function. An analysis of the resulting energy savings has been demonstrated.

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Fuzzy logic decission maker for automatic feeder and water quality monitoring system

International Journal of Informatics and Communication Technology (IJ-ICT) ◽

10.11591/ijict.v10i1.pp37-45 ◽

2021 ◽

Vol 10 (1) ◽

pp. 37

Author(s):

Vivien Arief Wardhany ◽

Herman Yuliandoko ◽

Subono Subono ◽

A Wildan J ◽

Tomy Iskandar ◽

...

Keyword(s):

Fuzzy Logic ◽

Water Quality Monitoring ◽

Feeding Time ◽

Monitoring And Control ◽

Shrimp Culture ◽

Monitoring And Control System ◽

Oxygen Levels ◽

Automatic Feeder ◽

Decision Making System ◽

And Control

<span>Feeding is one of the most important factors in vanammei shrimp culture. Feeding time must be scheduled regulary and it is prohibit from being late. Because it can affect to the development and growth of vanammei shrimp. The Research of monitoring and control system of vanammei shrimp feeding continues to be developed. The development of hardware and software in this study prioritizes monitoring of pH conditions, oxygen levels, and pond temperatures. The measurement results of pH, oxygen levels and pond temperature can be used as decision makers for vanammei shrimp feeding schedules. The decision making system using the Fuzzy Logic method. The development of control devices for feeding aims to set a schedule for feeding automatically. The use of monitoring devices and automatic Feeder control of shrimp feeding can reduce the accumulation of leftover shrimp feed, so that feeding can be more efficient.</span>

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A survey of fuzzy logic monitoring and control utilisation in medicine

Artificial Intelligence in Medicine ◽

10.1016/s0933-3657(00)00072-5 ◽

2001 ◽

Vol 21 (1-3) ◽

pp. 27-42 ◽

Cited By ~ 75

Author(s):

M Mahfouf ◽

M.F Abbod ◽

D.A Linkens

Keyword(s):

Fuzzy Logic ◽

Monitoring And Control ◽

And Control

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THE MONITORING AND CONTROL OF AN ARM CRANK SYSTEM USING FUZZY LOGIC FOR MULTI-HANDICAPPED YOUTHS WITH MENTAL RETARDATION

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237202000292 ◽

2002 ◽

Vol 14 (05) ◽

pp. 197-203

Author(s):

JIANN-SHING SHIEH ◽

JEN-TSANG HUNG

Keyword(s):

Fuzzy Logic ◽

Mental Retardation ◽

Fuzzy Logic Controller ◽

Physical Therapist ◽

Rotation Velocity ◽

Manual Control ◽

Control Group ◽

Monitoring And Control ◽

Significant Difference ◽

And Control

In this paper, we try to cope with National Special School in Taoyuan in order to fit the special requirements for multi-handicapped youths with mental retardation using current high technology, such as microcomputer control, sensing technology, and fuzzy logic control. The prototype device of this paper is focused on designing an arm crank system using a fuzzy logic controller (FLC) to exercise for the upper limb. The rotation velocity of this system was controlled via adjusting the electric current of the brake in order to increase the training motivation. Hence, a FLC was designed into this system in comparison with a manual control by an expert (i.e., physical therapist). Fifteen multi-handicapped youth with mental retardation were treated using the manual control as a control group, and another fifteen youths were treated using FLC as an experimental group. The root mean square deviation (RMSD) of the change of rotation velocity of arm crank was no significant difference (p > 0.05) using Student t test analysis. It means that FLC can be replaced the manual control by the qualified physical therapist. Therefore, it can be seen as a demonstration of feasibility of the applicability of this FLC for monitoring and control the velocity of the arm crank. But, it still needs a longer series of multi-handicapped youths with mental retardation, perhaps to refine the rule-bases, and certainly to see how widely they are applicable.

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