Physical Sciences › Computer Science › Computer Networks and Communications
Energy Efficient Wireless Sensor Networks
11 artículos indexados
Este asunto y su jerarquía proceden de la clasificación OpenAlex, el catálogo abierto de la investigación científica mundial.
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- Energy-efficient operation of neural operators for virtual sensing
Jason Yoo, Samrendra Roy, Souvik Chakraborty, Syed Bahauddin Alam · 28 de septiembre de 2026
Virtual sensing repeatedly reconstructs physical fields from changing observations, often on a fixed geometry. We investigate how shared spatial computation reduces the energy of these updates while retaining the selected checkpoint and its evaluated predictions. In a heat-exchanger service, standar…
- A Recommendation System Approach for Interference-Robust Sensor Subset Selection
Kaan Buyukkalayci, Kyle Pak, Merve Karakas, Christina Fragouli · 12 de agosto de 2026
This paper develops a method for sensor-subset selection for tracking. Prior work showed that low-cost acoustic Received Signal Strength Indicator (RSSI) measurements can be used to recommend subsets of sensor nodes whose expensive sensing modalities, such as cameras, can achieve high tracking accur…
- ToDMA: Large Model-Driven Massive Token Communications for Semantic Multiple Access
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao, Robert Schober, Deniz G\"und\"uz · 10 de julio de 2026
Token communications (TokenCom) is an emerging generative semantic communication paradigm, where tokens serve as compact representation units across modalities. Their contextual dependencies can be exploited by pretrained large models for semantic recovery. In this paper, we propose token-domain mul…
- Virtual Sensing to Enable Real-Time Monitoring of Inaccessible Locations & Unmeasurable Parameters
Kazuma Kobayashi, Farid Ahmed, Jaewan Park, Subhankar Sarkar, Souvik Chakraborty, Syed Bahauddin Alam · 16 de junio de 2026
Real-time monitoring of safety-critical interior states remains an open problem in energy systems where physical instrumentation is infeasible. Existing approaches rely on explicit governing equations, finite-dimensional state vectors, or per-instance retraining, which prevents mesh-independent, fie…
- Solved in Unit Domain: JacobiNet for Differentiable Coordinate-Transformed PINNs
Xi Chen, Jianchuan Yang, Junjie Zhang, Runnan Yang, Xu Liu, Hong Wang, Tinghui Zheng, Ziyu Ren, Wenqi Hu · 29 de mayo de 2026
Physics-Informed Neural Networks (PINNs) offer a powerful framework for solving PDEs by embedding physical laws into the learning process. However, when applied to domains with irregular boundaries, PINNs often suffer from instability and slow convergence, which stems from (1) inconsistent normaliza…
- IGADA-IoT: IoT Sensor Energy Optimization in Wireless Sensor Networks Driven by Automatic Data Augmentation
Mingchun Sun, Rongqiang Zhao, Muhammad Abdul Munnaf, Jie Liu · 28 de mayo de 2026
In wireless sensor networks (WSNs), data augmentation is a novel method to improve sampling-frequency decision performance, thereby enabling energy optimization for IoT (Internet of Things) sensors. However, existing methods rely on a single generator and empirically determined quantities, failing t…
- Towards Auto-Building of Embedded FPGA-based Soft Sensors for Wastewater Flow Estimation
Tianheng Ling, Chao Qian, Gregor Schiele · 22 de abril de 2026
Executing flow estimation using Deep Learning (DL)-based soft sensors on resource-limited IoT devices has demonstrated promise in terms of reliability and energy efficiency. However, its application in the field of wastewater flow estimation remains underexplored due to: (1) a lack of available data…
- MoGERNN: An Inductive Traffic Predictor for Unobserved Locations
Qishen Zhou, Yifan Zhang, Michail A. Makridis, Anastasios Kouvelas, Yibing Wang, Simon Hu · 21 de abril de 2026
Given a partially observed road network, how can we predict the traffic state of interested unobserved locations? Traffic prediction is crucial for advanced traffic management systems, with deep learning approaches showing exceptional performance. However, most existing approaches assume sensors are…
- PCA-Driven Adaptive Sensor Triage for Edge AI Inference
Ankit Hemant Lade, Sai Krishna Jasti, Nikhil Sinha, Indar Kumar, Akanksha Tiwari · 8 de abril de 2026
Multi-channel sensor networks in industrial IoT often exceed available bandwidth. We propose PCA-Triage, a streaming algorithm that converts incremental PCA loadings into proportional per-channel sampling rates under a bandwidth budget. PCA-Triage runs in O(wdk) time with zero trainable parameters (…
- Leveraging Wireless Sensor Networks for Real-Time Monitoring and Control of Industrial Environments
Muhammad Junaid Asif, Abdul Rehman, Asim Mehmood, Rana Fayyaz Ahmad, Shazia Saqib · 7 de abril de 2026
This research proposes an extensive technique for monitoring and controlling the industrial parameters using Internet of Things (IoT) technology based on wireless communication. We proposed a system based on NRF transceivers to establish a strong Wireless Sensor Network (WSN), enabling transfer of r…
- Wireless communication empowers online scheduling of partially-observable transportation multi-robot systems in a smart factory
Yaxin Liao, Qimei Cui, Kwang-Cheng Chen, Xiong Li, Jinlian Chen, Xiyu Zhao, Xiaofeng Tao, Ping Zhang · 26 de marzo de 2026
Achieving agile and reconfigurable production flows in smart factories depends on online multi-robot task assignment (MRTA), which requires online collision-free and congestion-free route scheduling of transportation multi-robot systems (T-MRS), e.g., collaborative automatic guided vehicles (AGVs). …
- PlugSI: Plug-and-Play Test-Time Graph Adaptation for Spatial Interpolation
Xuhang Wu, Zhuoxuan Liang, Wei Li, Xiaohua Jia, Sumi Helal · 11 de febrero de 2026
With the rapid advancement of IoT and edge computing, sensor networks have become indispensable, driving the need for large-scale sensor deployment. However, the high deployment cost hinders their scalability. To tackle the issues, Spatial Interpolation (SI) introduces virtual sensors to infer readi…
- Smart Routing with Precise Link Estimation: DSEE-Based Anypath Routing for Reliable Wireless Networking
Narjes Nourzad, Bhaskar Krishnamachari · 2 de febrero de 2026
In dynamic and resource-constrained environments, such as multi-hop wireless mesh networks, traditional routing protocols often falter by relying on predetermined paths that prove ineffective in unpredictable link conditions. Shortest Anypath routing offers a solution by adapting routing decisions b…
- Learnable WSN Deployment of Evidential Collaborative Sensing Model
Ruijie Liu, Tianxiang Zhan, Zhen Li, Yong Deng · 30 de diciembre de 2025
In wireless sensor networks (WSNs), coverage and deployment are two most crucial issues when conducting detection tasks. However, the detection information collected from sensors is oftentimes not fully utilized and efficiently integrated. Such sensing model and deployment strategy, thereby, cannot …
- Machine Learning to Predict Slot Usage in TSCH Wireless Sensor Networks
Stefano Scanzio, Gabriele Formis, Tullio Facchinetti, Gianluca Cena · 4 de diciembre de 2025
Wireless sensor networks (WSNs) are employed across a wide range of industrial applications where ultra-low power consumption is a critical prerequisite. At the same time, these systems must maintain a certain level of determinism to ensure reliable and predictable operation. In this view, time slot…
- Convergence of Shallow ReLU Networks on Weakly Interacting Data
L\'eo Dana (SIERRA), Francis Bach (SIERRA), Loucas Pillaud-Vivien (ENPC, CERMICS) · 2 de diciembre de 2025
We analyse the convergence of one-hidden-layer ReLU networks trained by gradient flow on $n$ data points. Our main contribution leverages the high dimensionality of the ambient space, which implies low correlation of the input samples, to demonstrate that a network with width of order $\log(n)$ neur…
- HiFiNet: Hierarchical Fault Identification in Wireless Sensor Networks via Edge-Based Classification and Graph Aggregation
Nguyen Van Son, Nguyen Tri Nghia, Nguyen Thi Hanh, Huynh Thi Thanh Binh · 25 de noviembre de 2025
Wireless Sensor Networks (WSN) are the backbone of essential monitoring applications, but their deployment in unfavourable conditions increases the risk to data integrity and system reliability. Traditional fault detection methods often struggle to effectively balance accuracy and energy consumption…
- Dynamic and Distributed Routing in IoT Networks based on Multi-Objective Q-Learning
Shubham Vaishnav, Praveen Kumar Donta, Sindri Magn\'usson · 18 de noviembre de 2025
IoT networks often face conflicting routing goals such as maximizing packet delivery, minimizing delay, and conserving limited battery energy. These priorities can also change dynamically: for example, an emergency alert requires high reliability, while routine monitoring prioritizes energy efficien…
- K-DAREK: Distance Aware Error for Kurkova Kolmogorov Networks
Masoud Ataei, Vikas Dhiman, Mohammad Javad Khojasteh · 28 de octubre de 2025
Neural networks are parametric and powerful tools for function approximation, and the choice of architecture heavily influences their interpretability, efficiency, and generalization. In contrast, Gaussian processes (GPs) are nonparametric probabilistic models that define distributions over function…
- PhySense: Sensor Placement Optimization for Accurate Physics Sensing
Yuezhou Ma, Haixu Wu, Hang Zhou, Huikun Weng, Jianmin Wang, Mingsheng Long · 28 de octubre de 2025
Physics sensing plays a central role in many scientific and engineering domains, which inherently involves two coupled tasks: reconstructing dense physical fields from sparse observations and optimizing scattered sensor placements to observe maximum information. While deep learning has made rapid ad…
- Enhanced Evolutionary Multi-Objective Deep Reinforcement Learning for Reliable and Efficient Wireless Rechargeable Sensor Networks
Bowei Tong, Hui Kang, Jiahui Li, Geng Sun, Jiacheng Wang, Yaoqi Yang, Bo Xu, Dusit Niyato · 27 de octubre de 2025
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