본문 바로가기
KERD
논문KCI 등재

무선 센서를 위한 가중 트리기반 신호 분석

Weighted Tree-based Signal Analysis for Wireless Sensors

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류기계공학

초록

Wireless sensor systems are primarily used for monitoring natural environments or industrial automation. The physical environment where these systems are installed is often unstable, making it difficult to replenish sensor energy immediately. Complex and harsh conditions can impact the network's structure, affecting monitoring performance. Wireless sensor systems consist of hundreds of sensors that collect data from hazardous environments and transmit information to a central system. However, due to the system's physical structure, information delays or losses may occur. This paper proposes a distance-based tree structure to address these issues in wireless sensor systems, and experimental results confirm its superior performance.

Abstract

Wireless sensor systems are primarily used for monitoring natural environments or industrial automation. The physical environment where these systems are installed is often unstable, making it difficult to replenish sensor energy immediately. Complex and harsh conditions can impact the network's structure, affecting monitoring performance. Wireless sensor systems consist of hundreds of sensors that collect data from hazardous environments and transmit information to a central system. However, due to the system's physical structure, information delays or losses may occur. This paper proposes a distance-based tree structure to address these issues in wireless sensor systems, and experimental results confirm its superior performance.

참고문헌 (12)

  1. P. P. Ray, "Internet of things for disaster management : State-of-the-art and prospects", IEEE Access, 5 (2017)
  2. E. Sisinni, "Industrial internet of things : Challenges, opportunities, and directions", IEEE Industrial Informatics, 14 (2018)
  3. G. Han, "A Multi-Charger Cooperative Energy Provision Algorithm Based on Density Clustering in the Industrial Internet of Things", IEEE Internet of Things, 6 (2019)
  4. E. Sisinni, "Industrial internet of things : Challenges, opportunities, and directions", IEEE Industrial Informatics, 14 (2018)
  5. Q. Wei, "An Improved Approach for Wireless Sensor Networks With Mobile Sink Using Dynamic Minimum Spanning Tree", IEEE Sensors, 22 (2022)
  6. L. Liu, "Boundary Tracking of Continuous Objects Based on Binary Tree Structured SVM for Industrial Wireless Sensor Networks", IEEE Computing, 21 (2022)
  7. Yang Liu, "Mesh-Based Consensus Distributed Particle Filtering for Sensor Networks", IEEE Signal and Information Processing over Networks, 9 (2023)
  8. Z. Nurlan, "Resource Allocation Approach for Optimal Routing in IoT Wireless Mesh Networks", IEEE Access, 9 (2021)
  9. Z. Wei, "The Performance Analysis of Spectrum Sharing Between UAV Enabled Wireless Mesh Networks and Ground Networks", IEEE Sensors, 21 (2021)
  10. S. Mahajan, "Prediction of Network Traffic in Wireless Mesh Networks Using Hybrid Deep Learning Model", IEEE Access, 10 (2022)
  11. Z. Nurlan, "Wireless Sensor Network as a Mesh : Vision and Challenges", IEEE Access, 10 (2022)
  12. L. Liu, "Fault-Tolerant Event Region Detection on Trajectory Pattern Extraction for Industrial Wireless Sensor Networks", IEEE Industrial Informatics, 16 (2020)

관련 논문AI추천

이 간행물의 다른 논문 (49건)