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Fuzzy logic type-2 microcontroller design to control automatic washing machine using Raspberry PI

تصميم متحكم منطق ضبابي Type-2 للتحكم بغسالة أتوماتيكية باستخدام Raspberry PI

1974   0   21   0.0 ( 0 )
 Publication date 2019
and research's language is العربية
 Created by Shamra Editor




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As we enter the age of artificial intelligence, the need for intelligent home appliances has become very important for what this smart equipment can provide in the provision of electrical energy and water resources that are treasures should human preservation, in addition to the contribution of this equipment to protect the environment from pollution, where we face the challenges next: High prices of electrical equipment.  The number of hours of electricity supply in many areas is low because of the current conditions in our country. - Water shortage. - The rise in prices of materials used in daily life in general and household detergents in particular - Great waste of electricity. - Pollution of the environment and groundwater with detergents used in the laundry process. Moreover, the unjust economic blockade imposed on our country is pushing us to work to produce low-cost national housing equipment that competes with foreign products in order to alleviate the material burden on the citizens and promote the national economy. In order to accomplish this smart washing machine, we have written a code for f type-2 fuzzy microcontroller, using the Python programming language. This controller has received four entries, which are: The first income (clothing color), obtained by taking a picture of the clothes that we need to wash by a camera with a resolution of 8 megapixels, analyzed using OpenCV library, and the second income (clothing type), determined by the local binary pattern algorithm, which is common digital image processing algorithm that widely used to identify shapes that follow specific pattern and structure, the third income (degree of dirt), and was identified by taking a picture of the clothes after soaking them with water for two minutes. The image was then analyzed by the OpenCV library and the fourth (washing weight) that getting From the Load Cell, which measures the physical weights. The readings were converted to digital values via the HX711 digital analogue converter and then sent to Arduino UNO to determine the weight. The weight values were eventually sent to the Raspberry PI for use in the controller. The system generates three exits: washing time (the length of time the laundry was washed), the temperature required for washing, and the amount of detergent required. After selecting all the previous values, we transferred to control Wattar washing machine model 402, where the water valve was controlled to allow the water to pass into the powder box and from it to the washing basin. The water heater was controlled, which heated the water to the temperature determined by the Fuzzy algorithm, The temperature was monitored by the DS18B20 temperature sensor, which gives a signal to the Raspberry PI at the arrival of the temperature to the required value, and the washing machine engine is controlled for a third of the time specified in the Fuzzy algorithm and we controlled the pump Water to empty basin Washing from water, the process repeated for three consecutive times, we control using a software interface designed using TKinter library  We have been able to design a smart Fuzzy logic type-2 controller with the following advantages: o save electricity consumption o Provide quantity of detergents o Shortenwashingtime  We have been able to control the following physical components within the washing machine: o Control the water pump o control Water valve o controlMotor o controlTemperaturesensor o controlLCDscreen  We have built a smart washing machine with the following characteristics: o Have the ability to recognize the condition of clothes o Identify the type of clothing o Identify the color of clothes o Dothewashingwithoutusingapredefinedprogram.  The controller we designed gives good results to calculate the following: o Washingtime o Quantity of detergents o Temperature All diagrams appear in the case of the incremental gradient with an increased degree of dirt and as values correspond to each type of clothing. Keywords: smart washing machine, saving electricity, saving detergent, shortening washing time, color and clothing distinction, artificial intelligence, fuzzy logic type-2, Raspberry PI, control, Python programming language, HX711.


Artificial intelligence review:
Research summary
البحث يتناول تصميم متحكم منطق ضبابي من النمط الثاني باستخدام حاسوب Raspberry Pi للتحكم بغسالة أوتوماتيكية. يهدف البحث إلى تحسين كفاءة الغسالات من خلال تقليل استهلاك الطاقة الكهربائية وكمية المنظفات وزمن الغسيل. يتم ذلك عبر استخدام خوارزمية المنطق الضبابي التي تعتمد على أربعة مداخل: لون الملابس، نوع الملابس، درجة الاتساخ، ووزن الغسيل. تم استخدام لغة البرمجة بايثون ومكتبة OpenCV لمعالجة الصور، بالإضافة إلى خوارزمية تمييز الأنماط المحلية LBP لتحديد نوع الملابس. النتائج أظهرت أن النظام المصمم يوفر في استهلاك الطاقة والمنظفات ويقلل من زمن الغسيل، مما يجعله مناسبًا للاستخدام في البيئات ذات الموارد المحدودة.
Critical review
البحث يقدم إسهامًا مهمًا في مجال الأتمتة الصناعية وتحسين كفاءة الغسالات الأوتوماتيكية. ومع ذلك، هناك بعض النقاط التي يمكن تحسينها. أولاً، البحث يعتمد بشكل كبير على مكونات إلكترونية قد تكون مكلفة وصعبة الحصول عليها في بعض المناطق، مما قد يحد من إمكانية تطبيقه على نطاق واسع. ثانياً، لم يتم التطرق بشكل كافٍ إلى كيفية التعامل مع الأخطاء المحتملة في قراءة المستشعرات أو معالجة الصور، مما قد يؤثر على دقة النظام. أخيرًا، يمكن تحسين خوارزمية معالجة الصور المستخدمة لتحديد نوع الملابس، حيث تم الاعتماد على خوارزمية موجودة مسبقًا دون تحسينها.
Questions related to the research
  1. ما هي المداخل الأربعة التي يعتمد عليها النظام المصمم في البحث؟

    النظام يعتمد على أربعة مداخل هي: لون الملابس، نوع الملابس، درجة الاتساخ، ووزن الغسيل.

  2. ما هي اللغة البرمجية المستخدمة في تصميم النظام؟

    تم استخدام لغة البرمجة بايثون في تصميم النظام.

  3. ما هي الفوائد الرئيسية للنظام المصمم كما ذكر في البحث؟

    الفوائد الرئيسية هي توفير استهلاك الطاقة الكهربائية، تقليل كمية المنظفات، وتقصير زمن الغسيل.

  4. ما هي التوصيات التي قدمها الباحثون لتحسين النظام؟

    التوصيات تشمل تحسين خوارزمية معالجة الصور المستخدمة في التعرف على نوع الملابس، ودراسة استجابة النظام عند تبديل أشكال توابع العضوية الضبابية للوصول إلى النوع الأفضل.


References used
Anindyaguna,K.; Basjaruddin, N. C.; Saefudin, D.; Overtaking Assistant System (OAS) with Fuzzy Logic Method Using Camera Sensor. 2nd, IEEE, International Conference of Industrial, Mechanical, Electrical, Chemical Engineering (ICIMECE), 2016, 6
Dash, K. S.; Mohanty, G.; Mohanty, A.; Intelligent Air Conditioning System using Fuzzy, International Journal of Scientific & Engineering Research Volume 3, Issue 12, December-2012, 6
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