في السنوات الأخيرة، أدى التقدم التكنولوجي في إنترنت الأشياء (IoT) وأجهزة الاستشعار الذكية إلى فتح اتجاهات جديدة وإعطاء حلول عملية في مختلف قطاعات الحياة. يتم التعرف على إنترنت الأشياء كتنولوجيا حديثة تربط بين مختلف انواع الشبكات. تم تحسين أنواع مختلفة من قطاعات الرعاية الصحية في المجال الطبي بناءً على هذه التكنولوجيا. أحد هذه القطاعات الهامة هو نظام مراقبة الصحة (HMS). تعتبر مراقبة المريض عن بعد لاسلكيًا وبتكلفة منخفضة أمرًا بالغ الأهمية في هذا المجال. في هذا العمل، تم اقتراح نظام مراقبة صحة المريض في الوقت الحقيقي وبتكلفة منخفضة. يتم دمج أنواع مختلفة من أجهزة الاستشعار في شبكة اتصالات لاسلكية لجمع الإشارات الفسيولوجية للمريض عن بعد وإرسالها إلى المختص في أسرع وقت ممكن. يتكون االنظام المقترح من عدد من أجهزة الاستشعار الذكية التي تقيس معلمات مختلفة وهي: عدد نبضات القلب بالدقيقة، درجة حرارة الجسم، وSPO2 (تشبع الأكسجين). تُستخدم هذه الحساسات لحساب معدل ضربات قلب المريض ودرجة حرارة الجسم ونسبة تشبع الأكسجين للمريض على التوالي. يتم عرض حالة المريض اما على شاشة OLED اوباستخدام تطبيق Blynk. في هذا النظام نستخدم لوحة Raspberry Pi Pico W كوحدة تحكم دقيقة مع مفهوم الحوسبة السحابية. بحيث يتم استخدام لوحة Raspberry Pi Pico W لنقل البيانات لاسلكيًا على تقنية إنترنت الأشياء باستخدام تطبيق Blynk. يتم نقل المعلمات الحيوية للمريض عن بعد عبر شبكة Wi-Fi مما يساعد في مراقبة المعلومات الصحية للمرضى لاسلكيًا وفي الوقت الحقيقي. من خلال النتائج التي تم الحصول عليها وجد ان البيانات التي تم الحصول عليها من المريض يتم نقلها بسرعة كبيرة ويمكننا فحص العديد من المرضى عن بعد من خلال الحفاظ على مسافة مناسبة مع المرضى. تم مقارنة النظام المقترح مع الانظمة الموجودة عن طريق قياس العلامات الحيوية لعدد من الأشخاص وأظهرت النتائج أن البيانات التي تم الحصول عليها من الأشخاص متقاربة جدا. علاوة على ذلك، فقد وجد أن النظام المقترح ذو تكلفة منخفضة مقارنة بالأجهزة الأخرى المتوفرة تجاريا.
Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.
 
... Show MoreProducts’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers. In this research, we pr
... Show MoreThis paper presents an enhancement technique for tracking and regulating the blood glucose level for diabetic patients using an intelligent auto-tuning Proportional-Integral-Derivative PID controller. The proposed controller aims to generate the best insulin control action responsible for regulating the blood glucose level precisely, accurately, and quickly. The tuning control algorithm used the Dolphin Echolocation Optimization (DEO) algorithm for obtaining the near-optimal PID controller parameters with a proposed time domain specification performance index. The MATLAB simulation results for three different patients showed that the effectiveness and the robustness of the proposed control algorithm in terms of fast gene
... Show MoreThe present study dealt with the removal of methylene blue from wastewater by using peanut hulls (PNH) as adsorbent. Two modes of operation were used in the present work, batch mode and inverse fluidized bed mode. In batch experiment, the effect of peanut hulls doses 2, 4, 8, 12 and 16 g, with constant initial pH =5.6, concentration 20 mg/L and particle size 2-3.35 mm were studied. The results showed that the percent removal of methylene blue increased with the increase of peanut hulls dose. Batch kinetics experiments showed that equilibrium time was about 3 hours, isotherm models (Langmuir and Freundlich) were used to correlate these results. The results showed that the (Freundlich) model gave the best fitting for adsorption capacity. D
... Show MoreThe traditional centralized network management approach presents severe efficiency and scalability limitations in large scale networks. The process of data collection and analysis typically involves huge transfers of management data to the manager which cause considerable network throughput and bottlenecks at the manager side. All these problems processed using the Agent technology as a solution to distribute the management functionality over the network elements. The proposed system consists of the server agent that is working together with clients agents to monitor the logging (off, on) of the clients computers and which user is working on it. file system watcher mechanism is used to indicate any change in files. The results were presente
... Show MoreAgent technology has a widespread usage in most of computerized systems. In this paper agent technology has been applied to monitor wear test for an aluminium silicon alloy which is used in automotive parts and gears of light loads. In addition to wear test monitoring، porosity effect on
wear resistance has been investigated. To get a controlled amount of porosity, the specimens have
been made by powder metallurgy process with various pressures (100, 200 and 600) MPa. The aim of
this investigation is a proactive step to avoid the failure occurrence by the porosity.
A dry wear tests have been achieved by subjecting three reciprocated loads (1000, 1500 and 2000)g
for three periods (10, 45 and 90)min. The weight difference a