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Journals / EMO Bilimsel Dergi / 2024 / Cilt: 14 Sayı: 2

Robust and Energy-Aware Path Planning by Autonomous Underwater Vehicle in Underwater Wireless Sensor Networks for Monitoring Maritime Transportation

Deniz Taşımacılığı İzlemek için Sualtı Kablosuz Sensör Ağlarında Otonom Sualtı Aracı ile Dayanıklı ve Enerji Farkında Yol Planlama

Ömer Melih Gül(İSTANBUL TEKNİK ÜNİVERSİTESİ)
Tayfun Acarer(PİRİ REİS ÜNİVERSİTESİ, DENİZCİLİK YÜKSEKOKULU)
Pages
71–85
Publication Date
2024-07-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Communicating sensors closer minimises their energy usage and improves UWSN network lifetime.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Since it’s cheaper, sea transportation has been preferred for international and intercontinental trade.
📊
Key Findings & Data:However, ship mishaps are possible dangers.
💡
Conclusion & Impact:Communicating sensors closer minimises their energy usage and improves UWSN network lifetime.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:otonom su altı aracı · sualtı kablosuz sensör ağları · enerjiye duyarlı yol planlaması

Abstract

Since it’s cheaper, sea transportation has been preferred for international and intercontinental trade. However, ship mishaps are possible dangers. Underwater wireless sensor networks (UWSN) can monitor the maritime environment to reduce maritime traffic risks. Energy is crucial for UWSNs in adverse areas with limited power. So UWSN can last, energy constraints must be handled to enable continuous environmental monitoring and surveillance data gathering and communication. Path planning and energy-saving autonomous underwater vehicle (AUV) charging for underwater sensor nodes can solve UWSN energy and battery replacement issues. This paper uses nearest neighbour algorithm to solve the energy-aware path planning problem with AUV. AUV path planning simulations show that the nearest neighbour algorithm converges faster and produces a better solution than the genetic algorithm and grey wolf optimizer algorithm. We offer robust and energy-efficient path planning algorithms to swiftly collect sensor data with less energy, allowing the monitoring system to respond faster to ship disaster hazards. Communicating sensors closer minimises their energy usage and improves UWSN network lifetime.

Özet

Daha ucuz olması nedeniyle uluslararası ve kıtalararası ticarette deniz taşımacılığı tercih edilmektedir. Ancak gemi kazaları olası tehlikelerdir. Sualtı kablosuz sensör ağları (SKSA), deniz trafiği risklerini azaltmak için deniz ortamını izleyebilir. Enerji, sınırlı güce sahip olumsuz bölgelerdeki SKSA’lar için hayati öneme sahiptir. SKSA’nın uzun süre dayanabilmesi için, sürekli çevresel izleme ve gözetleme verilerinin toplanması ve iletişimini sağlamak amacıyla enerji kısıtlamalarının ele alınması gerekir. Su altı sensör düğümleri için yol planlama ve enerji tasarruflu otonom su altı aracı (OSA) şarjı, SKSA enerji ve pil değiştirme sorunlarını çözebilir. Bu makale, OSA ile enerjiye duyarlı yol planlama problemini çözmek için en yakın komşu algoritmasını kullanmaktadır. OSA yol planlama simülasyonları, en yakın komşu algoritmasının genetik algoritmaya ve bozkurt eniyileştirme algoritmasına göre daha hızlı yakınsadığını ve daha iyi bir çözüm ürettiğini göstermektedir. Sensör verilerini daha az enerjiyle hızlı bir şekilde toplamak için sağlam ve enerji açısından verimli yol planlama algoritmaları sunarak izleme sisteminin gemi felaket tehlikelerine daha hızlı yanıt vermesini sağlıyoruz. Sensörlerin daha yakından iletişim kurması enerji kullanımını en aza indirir ve SKSA ağınının ömrünü artırır.

🔖

Cite This Article

Gül, Ö. M., Acarer, T. (2024). Robust and Energy-Aware Path Planning by Autonomous Underwater Vehicle in Underwater Wireless Sensor Networks for Monitoring Maritime Transportation. EMO Bilimsel Dergi, Cilt: 14 Sayı: 2, 71–85. https://ajindex.com/articles/1390297

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