Enhancing Routing, and Data Aggregation in WSNs Using Artificial Intelligence: A Survey
DOI:
https://doi.org/10.65405/tqvjbc06الكلمات المفتاحية:
شبكات الاستشعار اللاسلكية (WSNs)، التوجيه، الذكاء الاصطناعي (AI)، تجميع البيانات، قابلية التوسعالملخص
تُظهر هذه الدراسة أن بناء شبكة استشعار لاسلكية فعّالة يتطلب اختيار أفضل سيناريو للنشر والتركيز على عدة عوامل مهمة. أهم هذه العوامل هو إطالة عمر الشبكة من خلال تمكين عقد الاستشعار من العمل لأطول فترة ممكنة. يكتسب هذا الأمر أهمية خاصة نظرًا لأن شبكات الاستشعار اللاسلكية غالبًا ما تُنشر في مناطق نائية ويصعب الوصول إليها.
لتحقيق ذلك، يجب تحديد معايير تصميم واضحة، والحد من نقاط ضعف النظام باستخدام تقنيات الذكاء الاصطناعي المناسبة. يمكن لهذه الخوارزميات تحسين أداء الشبكة، لا سيما في التوجيه وتجميع البيانات، مع توفير الطاقة.
تُستخدم شبكات الاستشعار اللاسلكية في العديد من التطبيقات اليومية، ولكل تطبيق متطلباته الخاصة. على سبيل المثال، في الزراعة، قد لا يكون أمن البيانات مصدر قلق رئيسي، ولكن دقة البيانات وكفاءة استهلاك الطاقة أمران بالغا الأهمية. في مثل هذه الحالات، تُستخدم خوارزميات الذكاء الاصطناعي لتقليل استهلاك الطاقة أثناء نقل البيانات مع الحفاظ على موثوقية البيانات ودقتها.
التنزيلات
المراجع
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